From 9e22223040c7dc1bffe0b04de13a411ddd06646e Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 10:36:58 +0800
Subject: [PATCH 01/40] Record MiniCPM transfer constraints and CPU-reference
 speaker diagnostics

Refs #49

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 src/inferrsi/catalog.py                       |   5 +-
 src/inferrsi/data/knowledge_packs/README.md   |   4 +
 .../audio/streaming-transfer-constraints.json | 103 ++++++++++++++++++
 .../inference-optimization-casebook/SKILL.md  |   3 +
 .../cases/minicpm-speaker-cpu-reference.json  |  30 +++++
 .../cases/minicpm-speaker-cpu-reference.md    |  62 +++++++++++
 6 files changed, 206 insertions(+), 1 deletion(-)
 create mode 100644 src/inferrsi/data/knowledge_packs/peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json
 create mode 100644 src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
 create mode 100644 src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md

diff --git a/src/inferrsi/catalog.py b/src/inferrsi/catalog.py
index d27c9fe9a..51861cbf1 100644
--- a/src/inferrsi/catalog.py
+++ b/src/inferrsi/catalog.py
@@ -16,7 +16,10 @@
     "dependency": (
         "flashinfer", "flashattention", "pytorch", "triton", "diffusers", "transformers"
     ),
-    "peer": ("sglang", "tensorrt_llm", "lmdeploy", "xdit", "cache_dit", "qwen3_tts_engine"),
+    "peer": (
+        "sglang", "tensorrt_llm", "lmdeploy", "xdit", "cache_dit",
+        "qwen3_tts_engine", "minicpmo_single_gpu_engine",
+    ),
 }
 KNOWLEDGE_REPOS = tuple(
     dict.fromkeys(repo for repos in KNOWLEDGE_SCOPES.values() for repo in repos)
diff --git a/src/inferrsi/data/knowledge_packs/README.md b/src/inferrsi/data/knowledge_packs/README.md
index 366a150cc..355c09b88 100644
--- a/src/inferrsi/data/knowledge_packs/README.md
+++ b/src/inferrsi/data/knowledge_packs/README.md
@@ -152,3 +152,7 @@ All remain imported and locally unverified; downstream support requires separate
 | peer | qwen3_tts_engine | [Qwen3-TTS codec: cache fixed codebooks and retain request-owned causal state](peer/qwen3_tts_engine/ascend/audio/codec-constants-and-state.json) |
 | peer | qwen3_tts_engine | [Qwen3-TTS NPU graphs: batch prefill while preserving request state](peer/qwen3_tts_engine/ascend/audio/graph-batching-state-ownership.json) |
 | peer | qwen3_tts_engine | [Qwen3-TTS CustomVoice: cache only model-fixed prompt embeddings](peer/qwen3_tts_engine/ascend/audio/fixed-customvoice-prompt.json) |
+
+## MiniCPM-o 4.5 single-GPU source import
+
+[Streaming transfer constraints](peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json) records source-backed batching, overlap, metric and quality lessons. It preserves negative results and the source profile's incomplete quality qualification; it does not claim a locally reproduced downstream speedup.
diff --git a/src/inferrsi/data/knowledge_packs/peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json b/src/inferrsi/data/knowledge_packs/peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json
new file mode 100644
index 000000000..062737e60
--- /dev/null
+++ b/src/inferrsi/data/knowledge_packs/peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json
@@ -0,0 +1,103 @@
+{
+  "schema_version": 1,
+  "id": "minicpmo_single_gpu_engine.cuda.audio.streaming_transfer_constraints",
+  "tier": "peer",
+  "repo": "minicpmo_single_gpu_engine",
+  "backend": "cuda",
+  "component": "audio",
+  "scenario": "audio.tts",
+  "title": "MiniCPM-o 4.5: streaming batching, launch overlap and quality-constrained transfer",
+  "status": "imported",
+  "summary": "Transfer hypotheses for streaming MiniCPM-o serving: measure complete audio delivery, preserve request-owned state, and qualify combined numerical changes separately from isolated kernels.",
+  "tags": [
+    "minicpm-o",
+    "streaming",
+    "cuda_graph",
+    "mps",
+    "code2wav",
+    "throughput",
+    "quality"
+  ],
+  "sources": [
+    {
+      "url": "https://github.com/InferMatrixLab/minicpm-o-4.5-single-gpu-engine/blob/a4f4778f312791c2d190b48e521141887ed160c8/docs/optimizations.md",
+      "type": "documentation",
+      "commit": "a4f4778f312791c2d190b48e521141887ed160c8",
+      "accessed_at": "2026-10-21",
+      "content_sha256": "54a836ed42d64f5212bcf040256abf4a38f6d92b2bb0582b8e16099d0f1d0565"
+    },
+    {
+      "url": "https://github.com/InferMatrixLab/minicpm-o-4.5-single-gpu-engine/blob/a4f4778f312791c2d190b48e521141887ed160c8/docs/baselines.md",
+      "type": "documentation",
+      "commit": "a4f4778f312791c2d190b48e521141887ed160c8",
+      "accessed_at": "2026-10-21",
+      "content_sha256": "f56647d01348ea76b57b22457172fa06efec2b6edab980e25ed0aa2cb155c62b"
+    },
+    {
+      "url": "https://github.com/InferMatrixLab/minicpm-o-4.5-single-gpu-engine/blob/a4f4778f312791c2d190b48e521141887ed160c8/bench/metrics.py",
+      "type": "source_code",
+      "commit": "a4f4778f312791c2d190b48e521141887ed160c8",
+      "accessed_at": "2026-10-21",
+      "content_sha256": "ef40121126464c9b120bd37710b145895a0a784a4caab5319d3f535b64ab35a0"
+    },
+    {
+      "url": "https://github.com/InferMatrixLab/minicpm-o-4.5-single-gpu-engine/blob/a4f4778f312791c2d190b48e521141887ed160c8/bench/protocol.py",
+      "type": "source_code",
+      "commit": "a4f4778f312791c2d190b48e521141887ed160c8",
+      "accessed_at": "2026-10-21",
+      "content_sha256": "c739883456a14c0717121af1c1d7e6fd0ec6601f9a657c1d0d577a27f23dab74"
+    }
+  ],
+  "applicability": {
+    "hardware": [
+      "NVIDIA L20X source campaign; other devices need independent qualification"
+    ],
+    "software": [
+      "openbmb/MiniCPM-o-4_5",
+      "Dedicated single-GPU engine source snapshot; downstream vLLM-Omni and SGLang-Omni revisions must be checked independently"
+    ],
+    "conditions": [
+      "Fixed checkpoint bytes, sampling parameters, reference audio and workload across comparisons.",
+      "Separate tuning/evaluation requests and consistent warmup/cache policies."
+    ]
+  },
+  "claims": [
+    {
+      "kind": "upstream_reported",
+      "description": "The source reports separating Token2Wav into an MPS worker, batching streaming windows, graph replay and asynchronous host-to-device preparation."
+    },
+    {
+      "kind": "upstream_reported",
+      "description": "The measured fast profile is not quality-qualified: combining TF32 HiFT and batched setup exceeded a chunk error bound despite individual mechanisms passing their checks."
+    },
+    {
+      "kind": "upstream_reported",
+      "description": "Several plausible launch reductions measured neutral or negative at service level, including larger HiFT graph buckets and asynchronous Token2Wav results."
+    }
+  ],
+  "downstream_impact": [
+    "Inspect current vLLM-Omni implementation before porting: it may already provide fused CFM, cross-reference batching and graph replay absent from historical measurements.",
+    "Keep reference extraction, setup, decode, output delivery and queueing distinct when profiling.",
+    "MPS and graph bucket choices are device/workload tuning hypotheses, not universally optimal defaults."
+  ],
+  "recommendations": [
+    "Report frames/s as 25 times delivered audio seconds divided by wall time, TTFA from first delivered samples, and request RTF from last delivered samples. Preserve chunk counts and failures.",
+    "Label a one-waveform response non-streaming; its TTFA is close to full-response latency and differs semantically from an incremental stream.",
+    "Compare lossless execution/configuration changes first; numerical precision, smaller first windows and sampling changes require separate quality qualification."
+  ],
+  "validation_plan": [
+    "Pin source and dependency identities; verify that editable imports do not escape the tested checkout.",
+    "Run disjoint warmup and evaluation prompts at every reported concurrency; retain per-request audio, timing, failures and run-level variability.",
+    "Use numerical/state tests plus complete served WER, speaker similarity and quality scoring; test combinations, not just each mechanism alone.",
+    "Compare paired baseline/candidate service runs with equivalent caches and devices; keep microbench and imported results separate."
+  ],
+  "limitations": [
+    "Source-backed import only; no locally verified downstream acceleration.",
+    "Historical vLLM-Omni plateau and SGLang non-streaming observations apply only to their pinned source campaign revisions.",
+    "A dedicated engine schedule cannot be transplanted as a deployment parameter; state and runtime ownership differ."
+  ],
+  "verification": {
+    "locally_verified": false,
+    "evidence_level": "guidance"
+  }
+}
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md
index abf4d37d1..9a745a495 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md
@@ -80,6 +80,9 @@ Source: perf-optimization-casebook @ f33e0e5f, §how-to-use.
 
 Current owner-local records retain rejected directions alongside their limits:
 
+- [MiniCPM-o speaker extraction](cases/minicpm-speaker-cpu-reference.md): CPU
+  graph optimizer semantics, short-input numerical rejection and component/service boundaries.
+
 - [Qwen B300](cases/qwen-b300-rejected-directions.md): full-image rejection,
   graph/copy overhead, unintegrated leads and confounded trials.
 - [Qwen Ascend](cases/qwen-ascend-rejected-directions.md): reported OOM,
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
new file mode 100644
index 000000000..e97e597f9
--- /dev/null
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
@@ -0,0 +1,30 @@
+{
+  "id": "case.minicpm-speaker-cpu-reference",
+  "kind": "case",
+  "origin": [
+    "internal"
+  ],
+  "state": "historical_observation",
+  "content": "minicpm-speaker-cpu-reference.md",
+  "sources": [
+    {
+      "type": "internal",
+      "issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+      "run": "minicpmo45-l20x-20261021",
+      "artifact": "speaker-candidate-micro.json",
+      "sha256": "e8b7b49fd51662d7fde58cd10306e64fde318f5ae9c857a1482ef7a6db4a94cd",
+      "integrity_status": "rehashed",
+      "evidence_path": "evidence/minicpmo45-l20x-20261021/results/speaker-candidate-micro.json"
+    }
+  ],
+  "applicability": [
+    "CUDA CAM++ voice-cloning speaker extraction",
+    "Optimized CPU reference graphs with partial pooling windows"
+  ],
+  "limitations": [
+    "Component PASS is not service PASS",
+    "English workload on one GPU family",
+    "Raw evidence remains owned by the campaign"
+  ],
+  "attribution": "InferRSI issue #49 local diagnostic evidence"
+}
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
new file mode 100644
index 000000000..583c0a240
--- /dev/null
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
@@ -0,0 +1,62 @@
+# MiniCPM-o speaker extraction: preserve the executed reference graph
+
+This is a scoped diagnostic from [acceptance issue #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
+The isolated component gate passed; service and generated-speech qualification
+remain separate. Raw measurements belong to the campaign evidence tree.
+
+## Observation
+
+Concurrent voice cloning repeatedly prepares distinct reference audio. A host
+stack sample concentrated in CPU CAM++ extraction, but profiling perturbed the
+service and cannot establish its wall-time share. An isolated synchronized
+benchmark confirmed substantial CPU extraction cost. Moving the original ONNX
+graph to either Torch or TensorRT changed normalized speaker embeddings, most
+strongly on short inputs. Disabling TF32 did not remove that discrepancy.
+
+## Confirmed mechanism
+
+The reference CPU ONNX Runtime session optimizes the graph. Its BASIC PadFusion
+folds zero Pad into ceil-mode AveragePool and changes `count_include_pad` for
+partial windows. An unfused conversion preserves the original graph rather
+than the currently executed CPU semantics. Comparing optimization-disabled and
+BASIC/ALL sessions, plus a minimal all-ones pooling regression, isolated this
+difference from floating-point precision.
+
+The candidate exports the portable BASIC-optimized graph, keys it by model
+content and ONNX Runtime version, and builds a separate IEEE FP32 TensorRT
+engine. This met the predeclared component tolerance on the sampled normal
+and short reference inputs. It is not a proof of bitwise waveform identity or
+service-quality equivalence.
+
+## Reuse procedure
+
+1. Pin model assets, runtime optimizer version, preprocessing and reference
+   lengths. Include partial pooling windows and short inputs.
+2. Compare intermediate outputs with graph optimizations disabled and enabled
+   before attributing differences to TF32, quantization or checkpoint drift.
+3. Export only portable operators; keep derived artifacts outside model files
+   and isolate caches by content, backend version and precision policy.
+4. Measure the component with explicit synchronization and warmup, then run
+   matched service workloads with the same concurrency and reference diversity.
+5. Evaluate WER, speaker similarity and perceptual quality independently.
+   Do not promote a component PASS to a service or accuracy PASS.
+
+## Counter-signals and rejected alternatives
+
+MPS, runtime encoder capture and a larger CFM microbatch did not improve both
+high-concurrency tuning cells in the initial scan. This does not blacklist
+those mechanisms: after removing a host bottleneck, accelerator contention
+and batching may become relevant. MRv2 traded lower first-audio latency for
+lower throughput on this workload; select against the requested objective.
+
+The original-ONNX GPU conversions failed the numerical gate even though their
+component latency was lower. The cause was graph semantics, so retrying only
+with different precision would repeat the wrong experiment. Short reference
+inputs were discriminating; long references alone understated the error.
+
+## Limits
+
+Evidence covers one CUDA GPU family, one official model revision and an English
+voice-cloning workload. TensorRT is optional, engine startup cost is separate,
+and the optimized graph must be revalidated when ONNX Runtime changes. The
+case is diagnostic guidance, not an automatic backend-selection rule.

From 5706384dd940e9ada8cc9e0683e135455372c395 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 10:44:18 +0800
Subject: [PATCH 02/40] Archive pinned MiniCPM baselines and reproducible
 candidate validation

Refs #49. Campaign remains INCONCLUSIVE pending held-out service and quality results.

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |  118 +
 .../patch/candidate.json                      |   11 +
 .../patch/speaker-only.yaml                   |    5 +
 .../plan/baseline-plan.json                   |   40 +
 .../plan/cache-semantics.json                 |   12 +
 .../plan/candidate-packages.json              |    6 +
 .../plan/dataset-manifest.json                | 4359 +++++++++++++++++
 .../plan/main-profile-control.json            |   14 +
 .../plan/model-hf-check.json                  |   18 +
 .../plan/model-manifest.json                  |   18 +
 .../plan/model-metadata-check.json            |   47 +
 .../plan/mps-runspec-redacted.json            |   61 +
 .../plan/official-model-manifest.json         |  121 +
 .../plan/search-plan.json                     |   44 +
 .../plan/sglang-packages.json                 |  283 ++
 .../plan/speaker-device-hypothesis.json       |   22 +
 .../plan/speaker-microbatch-control.json      |   19 +
 .../plan/speaker-mrv2-control.json            |   18 +
 .../plan/vllm-main-resolved-config.json       |  179 +
 .../plan/vllm-packages.json                   |  524 ++
 .../results/baseline-quality.json.gz          |  Bin 0 -> 145204 bytes
 .../results/baseline-table.json               |  210 +
 .../results/environment-attempts.json         |   35 +
 .../excluded-local-checkpoint-scan.json       |   43 +
 .../results/mrv2-host-profile.json            |   13 +
 .../results/resource-snapshot.json            |   33 +
 .../results/sglang-exploratory.json.gz        |  Bin 0 -> 85296 bytes
 .../results/sglang-main-repeated.json.gz      |  Bin 0 -> 743128 bytes
 .../results/speaker-candidate-micro.json      |  327 ++
 .../results/speaker-torch-ieee-micro.json     |  326 ++
 .../results/speaker-torch-micro.json          |  326 ++
 .../results/speaker-trt-ieee-micro.json       |  326 ++
 .../results/speaker-trt-micro.json            |  326 ++
 .../speaker-trt-ort-compatible-micro.json     |  326 ++
 .../results/stage-attribution.json            |   49 +
 .../results/status.json                       |   20 +
 .../results/tuning-table.json                 | 1422 ++++++
 .../results/vllm-encoder-tuning.json.gz       |  Bin 0 -> 123545 bytes
 .../results/vllm-exploratory.json.gz          |  Bin 0 -> 123220 bytes
 .../results/vllm-main-repeated.json.gz        |  Bin 0 -> 1102808 bytes
 .../results/vllm-main-tuning.json.gz          |  Bin 0 -> 122984 bytes
 .../results/vllm-microbatch-tuning.json.gz    |  Bin 0 -> 47885 bytes
 .../results/vllm-mps-tuning.json.gz           |  Bin 0 -> 123028 bytes
 .../results/vllm-mrv2-tuning.json.gz          |  Bin 0 -> 120983 bytes
 .../results/vllm-speaker-tuning.json.gz       |  Bin 0 -> 122722 bytes
 .../validator/.gitkeep                        |    0
 .../validator/bench_speaker.py                |   52 +
 .../validator/benchmark-sources.json          |   20 +
 .../validator/driver-revisions.json           |   28 +
 .../validator/export_metrics.py               |   29 +
 .../validator/graph-tests.json                |   14 +
 .../validator/rsi-checks.json                 |   14 +
 .../validator/run_baseline.py                 |   49 +
 .../validator/run_baseline_v1.py              |   45 +
 .../validator/score_outputs.py                |   71 +
 .../validator/scorer-model-hashes.json        |   62 +
 .../validator/speaker-tests.json              |    8 +
 .../validator/speaker_trt_ieee.py             |  158 +
 .../validator/summarize_results.py            |   77 +
 .../repo_packs/inferrsi/knowledge/README.md   |    4 +-
 .../ascend-aclgraph-capture-replay.json       |    4 +-
 .../ascend/skills/ascend-device-health.json   |    4 +-
 .../skills/ascend-distributed-parallel.json   |    4 +-
 .../ascend/skills/ascend-graph-mode.json      |    4 +-
 .../skills/ascend-model-adaptation.json       |    4 +-
 .../skills/ascend-operator-profiling.json     |    4 +-
 .../ascend/skills/ascend-operator-tuning.json |    4 +-
 .../skills/ascend-optimization-casebook.json  |    4 +-
 .../skills/ascend-performance-analysis.json   |    4 +-
 .../ascend/skills/ascendc-tiling-design.json  |    4 +-
 .../skills/cann-attribution-overlap.json      |    4 +-
 .../torchnpu-device-memory-lifecycle.json     |    4 +-
 ...torchnpu-pinned-host-memory-lifecycle.json |    4 +-
 .../skills/assess-serving-preemption.json     |    4 +-
 .../assess-split-backward-schedule.json       |    4 +-
 .../skills/audit-vllm-kv-lifetimes.json       |    4 +-
 .../skills/calibrate-serving-simulation.json  |    4 +-
 .../skills/cgroup-resource-controls.json      |    4 +-
 .../checkpoint-recovery-consistency.json      |    4 +-
 .../skills/choose-parallel-training-plan.json |    4 +-
 .../skills/cite-check-downstream-pr.json      |    4 +-
 .../common/skills/claim-contract.json         |    4 +-
 .../common/skills/competitor-scan.json        |    4 +-
 .../skills/dcp-async-save-performance.json    |    4 +-
 .../skills/dense-performance-evidence.json    |    4 +-
 .../diagnose-vllm-admission-pressure.json     |    4 +-
 .../common/skills/draft-acceptance-issue.json |    4 +-
 .../evaluate-elastic-serving-placement.json   |    4 +-
 .../common/skills/host-memory-management.json |    4 +-
 .../skills/host-overhead-optimization.json    |    4 +-
 .../skills/inference-benchmark-design.json    |    4 +-
 .../inference-optimization-casebook.json      |   12 +-
 .../common/skills/kernel-writing-guide.json   |    4 +-
 .../common/skills/kv-tier-management.json     |    4 +-
 .../common/skills/npu-skill-factory.json      |    4 +-
 .../skills/optimization-search-policy.json    |    4 +-
 .../common/skills/os-process-placement.json   |    4 +-
 .../skills/performance-ceiling-analysis.json  |    4 +-
 .../skills/plan-activation-residency.json     |    4 +-
 .../skills/repository-evolution-analysis.json |    4 +-
 .../knowledge/common/skills/rsi-evidence.json |    4 +-
 .../skills/skill-evolution-playbook.json      |    4 +-
 .../common/skills/storage-io-measurement.json |    4 +-
 .../skills/training-input-pipeline.json       |    4 +-
 .../skills/training-resource-budget.json      |    4 +-
 .../skills/weight-loading-optimization.json   |    4 +-
 .../diagnose-attention-bottlenecks.json       |    4 +-
 .../cuda/skills/host-overhead-profiling.json  |    4 +-
 108 files changed, 10432 insertions(+), 100 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/README.md
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/candidate.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/speaker-only.yaml
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/baseline-plan.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/cache-semantics.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/candidate-packages.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/dataset-manifest.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/main-profile-control.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/model-hf-check.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/model-manifest.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/model-metadata-check.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/mps-runspec-redacted.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/official-model-manifest.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/search-plan.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/sglang-packages.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/speaker-device-hypothesis.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/speaker-microbatch-control.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/speaker-mrv2-control.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/vllm-main-resolved-config.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/vllm-packages.json
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diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
new file mode 100644
index 000000000..d2e9cbef0
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -0,0 +1,118 @@
+# MiniCPM-o 4.5: single-L20X throughput study
+
+Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
+
+**Current verdict: INCONCLUSIVE.** Baselines are complete; candidate service and speech-quality qualification is in progress. Component PASS does not establish service PASS.
+
+## Scope and controls
+
+- One NVIDIA L20X (143771 MiB) per serving engine; shared host, reserved GPUs. vLLM baseline and speaker candidate use the same physical GPU. Other comparisons use the same GPU SKU.
+- Official model revision and all asset hashes: `plan/official-model-manifest.json`. The initially discovered local checkpoint had different metadata and was excluded.
+- Current main revisions are frozen in `plan/baseline-plan.json`. Main means those fetched snapshots, not a moving branch.
+- Seed-TTS English voice cloning: disjoint warmup, tuning and evaluation pools; source metadata and reference WAV hashes are frozen.
+- Concurrency 1, 2, 4, 8, 16, 32. Each baseline cell has 320 requests per repeat, one discarded run, then three measured repeats. Warmup uses 2 × concurrency separate rows.
+- Persistent-server steady state: caches are not reset between runs/cells. `cache_policy: none` means no reset procedure, not disabled caches. This is not the peer engine strict cold-cache certification; C32 uses 320 rather than its 640 requests.
+- Throughput is 25 × delivered audio seconds / measured wall time; it is an audio-frame equivalent, not video fps. The table averages three run throughputs. TTFA percentiles pool 960 requests; RTF is the mean per-request last-audio latency divided by generated duration.
+- vLLM streams audio chunks. SGLang returns a terminal waveform, so its TTFA is effectively completion latency. Do not interpret the two TTFA columns as equivalent streaming capability.
+
+## Main-branch baselines
+
+| Engine | C | Frames/s | TTFA p50 ms | TTFA p95 ms | RTF mean |
+|---|---:|---:|---:|---:|---:|
+| vllm | 1 | 192.6 | 307.5 | 343.1 | 0.132 |
+| vllm | 2 | 295.5 | 410.9 | 534.6 | 0.172 |
+| vllm | 4 | 394.0 | 881.6 | 1000.2 | 0.267 |
+| vllm | 8 | 488.4 | 1375.3 | 1602.6 | 0.426 |
+| vllm | 16 | 513.3 | 1702.7 | 2727.5 | 0.797 |
+| vllm | 32 | 540.2 | 2752.3 | 4732.2 | 1.502 |
+| sglang | 1 | 291.3 | 371.0 | 461.9 | 0.089 |
+| sglang | 2 | 476.6 | 451.3 | 578.7 | 0.109 |
+| sglang | 4 | 713.8 | 599.6 | 799.9 | 0.145 |
+| sglang | 8 | 1043.2 | 835.1 | 1042.6 | 0.198 |
+| sglang | 16 | 1558.5 | 1112.0 | 1411.5 | 0.264 |
+| sglang | 32 | 1918.5 | 1763.5 | 2479.4 | 0.425 |
+
+All 11,520 measured baseline requests completed successfully. Raw per-request metrics, individual run variation and WAV hashes are in `results/*-main-repeated.json.gz`. Generated WAVs, wire payloads and unredacted server logs remain local.
+
+## Reproduction
+
+Set paths explicitly; do not point the benchmark at an unrelated running service. Use separate compatible environments for the two engines, matching the package manifests under `plan/`.
+
+```bash
+export MODEL=/absolute/path/to/pinned-official-model
+export PEER=/absolute/path/to/minicpm-o-4.5-single-gpu-engine
+export SEED_TTS_ROOT=/absolute/path/to/seed-tts-eval
+export EVIDENCE=/absolute/path/to/this/evidence/directory
+export RUNS=/absolute/path/to/output-directory
+export VLLM_OMNI=/absolute/path/to/vllm-omni
+export SGLANG_OMNI=/absolute/path/to/sglang-omni
+```
+
+The peer benchmark revision is recorded in `validator/benchmark-sources.json`; do not silently substitute a newer client. The driver uses explicit adapter sampling and prompt settings from that snapshot.
+
+Baseline vLLM server (activate its environment first, reserve one GPU):
+
+```bash
+python -m vllm_omni.entrypoints.cli.main serve "$MODEL" --omni \
+  --served-model-name openbmb/MiniCPM-o-4_5 --host 127.0.0.1 --port 29161 \
+  --deploy-config "$VLLM_OMNI/vllm_omni/deploy/minicpmo_4_5_turn.yaml" \
+  --trust-remote-code --init-timeout 1800 --stage-init-timeout 1800
+```
+
+Baseline SGLang server (activate its environment first, reserve one GPU; use unused distributed ports and a writable private endpoint directory):
+
+```bash
+python -m sglang_omni.cli serve --model-path "$MODEL" --model-name minicpmo \
+  --thinker.engine.mem_fraction_static .55 --talker.engine.mem_fraction_static .15 \
+  --thinker.engine.dist_init_addr 127.0.0.1:29671 \
+  --talker.engine.dist_init_addr 127.0.0.1:29672 \
+  --thinker.factory.max_seq_len 8192 --endpoints.base_path "$RUNS/endpoints" \
+  --host 127.0.0.1 --port 29171
+```
+
+After readiness, run the matched benchmark client:
+
+```bash
+PYTHONPATH="$PEER" python "$EVIDENCE/validator/run_baseline.py" \
+  --adapter vllm-omni --url http://127.0.0.1:29161 \
+  --out "$RUNS/vllm-main" --concurrency 1 2 4 8 16 32 --requests 320 --repeats 3
+PYTHONPATH="$PEER" python "$EVIDENCE/validator/run_baseline.py" \
+  --adapter sglang-omni --url http://127.0.0.1:29171 \
+  --out "$RUNS/sglang-main" --concurrency 1 2 4 8 16 32 --requests 320 --repeats 3
+```
+
+For tuning use `--id-set tuning --requests 64 --repeats 1`. Do not mix tuning rows with held-out evaluation. Original baselines used driver v1; v2 only adds tuning-pool selection, with unchanged evaluation behavior. File hashes and usage are recorded in `validator/driver-revisions.json`.
+
+## Speaker candidate reproduction
+
+Check out the candidate revision in `patch/candidate.json`; install the optional
+TensorRT package matching CUDA (this run used `tensorrt-cu13==11.4.0.106`).
+Copy `patch/speaker-only.yaml` beside `minicpmo_4_5_turn.yaml` in the vLLM-Omni
+deploy directory. Start the same server with that overlay as `--deploy-config`.
+Set `COSYVOICE3_TRT_CACHE` to a writable persistent directory; first startup
+builds the engine. Use the identical benchmark command against the candidate
+port and a separate output directory. No DiT TensorRT, quantization, cache-size
+or sampling changes are part of this candidate.
+
+## Accuracy and numerical validation
+
+Quality uses existing SGLang-Omni scorers: Qwen3-ASR WER, WavLM speaker similarity (reported ×100), and UTMOS. Scorer weight hashes are frozen in `validator/scorer-model-hashes.json`. Score C1/C16/C32 run1 WAVs after each run has finished saving files; merely seeing `summary.json` is insufficient.
+
+```bash
+PYTHONPATH="$SGLANG_OMNI:$PEER" python "$EVIDENCE/validator/score_outputs.py" \
+  --run "$RUNS/vllm-main/c32/run1" --out "$RUNS/quality-main-c32.json" \
+  --scorers /absolute/path/to/scorer-assets --asr-port 29181 --device cuda:0
+```
+
+The ASR service is a separate Qwen3-ASR-1.7B SGLang-Omni server. The scorer validates nonempty finite audio and retains per-request scores. Public quality artifacts omit generated transcripts but retain WAV hashes and error counts.
+
+Speaker numerical validation uses the checked-in `validator/bench_speaker.py`. It covers 32 tuning references plus short partial-window inputs, with 10 warmups and 30 synchronized latency samples. `speaker_trt_ieee.py` is the preserved historical precision-only diagnostic helper; the final CPU-reference path imports the candidate implementation directly.
+
+```bash
+PYTHONPATH="$PEER:$VLLM_OMNI" python "$EVIDENCE/validator/bench_speaker.py" \
+  --model "$MODEL" --backend trt --cpu-reference --out "$RUNS/speaker-micro.json"
+```
+
+## Interpretation limits
+
+The optimization target is high-concurrency throughput with no speech-quality regression, not a globally optimal configuration. English voice cloning does not establish multilingual, visual, full-duplex or interruption correctness. Historical reference-engine results are prior art, not measurements reproduced by this campaign. Profiling perturbed MRv2 execution, so its stack samples are diagnostic only and excluded from performance tables.
diff --git a/evidence/minicpmo45-l20x-20261021/patch/candidate.json b/evidence/minicpmo45-l20x-20261021/patch/candidate.json
new file mode 100644
index 000000000..b53f9e526
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/candidate.json
@@ -0,0 +1,11 @@
+{
+  "repository": "https://github.com/vllm-project/vllm-omni",
+  "pull_request": "https://github.com/vllm-project/vllm-omni/pull/9188",
+  "candidate_revision": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
+  "measured_runtime_revision": "97efcf5cd8e611038a53d8e063204b2b5fa74085",
+  "later_changes": "Documentation, regression tests and one cache-key comment only; executable implementation unchanged.",
+  "baseline_revision": "aa3fd1d9b7f5c7191dec11975ac0aa7c4c4a18c5",
+  "configuration_delta": {
+    "token2wav_device_spk": true
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/patch/speaker-only.yaml b/evidence/minicpmo45-l20x-20261021/patch/speaker-only.yaml
new file mode 100644
index 000000000..0b1baf04e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/speaker-only.yaml
@@ -0,0 +1,5 @@
+base_config: minicpmo_4_5_turn.yaml
+connectors:
+  connector_of_shared_memory:
+    extra:
+      token2wav_device_spk: true
diff --git a/evidence/minicpmo45-l20x-20261021/plan/baseline-plan.json b/evidence/minicpmo45-l20x-20261021/plan/baseline-plan.json
new file mode 100644
index 000000000..b1a728b00
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/baseline-plan.json
@@ -0,0 +1,40 @@
+{
+  "acceptance_issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+  "objective": "Prioritize high-concurrency throughput while preserving quality; report TTFA p50/p95 and mean RTF",
+  "hardware": {
+    "gpu": "NVIDIA L20X",
+    "gpu_count_per_server": 1,
+    "memory_mib": 143771,
+    "driver": "570.133.20"
+  },
+  "source_revisions": {
+    "vllm_omni": "aa3fd1d9b7f5c7191dec11975ac0aa7c4c4a18c5",
+    "sglang_omni": "dbd923cdd180f8bfe7ec85defd6c6f914af5ae57",
+    "peer_engine": "a4f4778f312791c2d190b48e521141887ed160c8"
+  },
+  "concurrency": [
+    1,
+    2,
+    4,
+    8,
+    16,
+    32
+  ],
+  "workload": "Seed-TTS English voice cloning",
+  "metrics": {
+    "throughput_frames_s": "25 * sum(delivered_audio_seconds) / measured_wall_seconds",
+    "ttfa": "first unique audio sample receipt minus dispatch",
+    "rtf_mean": "mean((last unique audio sample receipt minus dispatch) / audio_duration)"
+  },
+  "state": "baseline_complete_candidate_testing",
+  "verdict": "INCONCLUSIVE",
+  "candidate_search_started": true,
+  "limitations": [
+    "Steady-state repeats do not reset server caches and are not the peer engine cold-cache certification.",
+    "SGLang emits a terminal waveform; vLLM uses streamed chunks, so TTFA semantics differ.",
+    "English voice-clone TTS workload only.",
+    "Initial local-checkpoint scan excluded because config/custom code differed from official metadata."
+  ],
+  "model_revision": "503e754207c94da6bb26850b4469f367c9ea3582",
+  "model_manifest": "official-model-manifest.json"
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/cache-semantics.json b/evidence/minicpmo45-l20x-20261021/plan/cache-semantics.json
new file mode 100644
index 000000000..fc58c2bfe
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/cache-semantics.json
@@ -0,0 +1,12 @@
+{
+  "protocol_cache_policy": "none",
+  "meaning": "No server restart or cache flush between cells. Does NOT mean runtime caches are disabled.",
+  "qualification": "Repeated steady-state exploratory measurement, not reference engine cold-cache certification.",
+  "vllm_main_defaults": {
+    "enable_prefix_caching": false,
+    "token2wav_runtime_prompt_cache_size": 4,
+    "token2wav_setup_cache_size": 1
+  },
+  "comparison_requirement": "Keep repository cache settings identical between baseline and candidate; retain this limitation and check selected high-concurrency gain after fresh launches.",
+  "source": "bench/protocol.py in pinned peer_engine revision"
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/candidate-packages.json b/evidence/minicpmo45-l20x-20261021/plan/candidate-packages.json
new file mode 100644
index 000000000..1db7925b9
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/candidate-packages.json
@@ -0,0 +1,6 @@
+[
+  {
+    "name": "vllm-omni",
+    "version": "0.32.0rc2.dev26+g97efcf5cd"
+  }
+]
diff --git a/evidence/minicpmo45-l20x-20261021/plan/dataset-manifest.json b/evidence/minicpmo45-l20x-20261021/plan/dataset-manifest.json
new file mode 100644
index 000000000..3a74fc06a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/dataset-manifest.json
@@ -0,0 +1,4359 @@
+{
+  "meta_sha256": "7cd29f701743e6c7033edbca764ddc0b979de8c4f4907eff5e5454682114661f",
+  "rows": [
+    {
+      "id": "common_voice_en_10119832-common_voice_en_10119840",
+      "ref_sha256": "af3ac928e98cdb171c9abdc611813f2cc40c52b71167790b785628104f81f389"
+    },
+    {
+      "id": "common_voice_en_10119832-common_voice_en_10119847",
+      "ref_sha256": "af3ac928e98cdb171c9abdc611813f2cc40c52b71167790b785628104f81f389"
+    },
+    {
+      "id": "common_voice_en_103675-common_voice_en_103676",
+      "ref_sha256": "1559628954a0117c81775b1a730ee46dd1c40ce099baaf1cc958bac6dd210330"
+    },
+    {
+      "id": "common_voice_en_103675-common_voice_en_103677",
+      "ref_sha256": "1559628954a0117c81775b1a730ee46dd1c40ce099baaf1cc958bac6dd210330"
+    },
+    {
+      "id": "common_voice_en_10933823-common_voice_en_10933822",
+      "ref_sha256": "0750ca1cccec0515e69bca3907adcfb95335e35e2bb74358e88071426e9accf2"
+    },
+    {
+      "id": "common_voice_en_10933823-common_voice_en_10933825",
+      "ref_sha256": "0750ca1cccec0515e69bca3907adcfb95335e35e2bb74358e88071426e9accf2"
+    },
+    {
+      "id": "common_voice_en_120405-common_voice_en_120402",
+      "ref_sha256": "1ea6c705b6d9cf2564395a8f6c89f39b10585a67e9c0fa81ffe3a202e2e51bba"
+    },
+    {
+      "id": "common_voice_en_120405-common_voice_en_120406",
+      "ref_sha256": "1ea6c705b6d9cf2564395a8f6c89f39b10585a67e9c0fa81ffe3a202e2e51bba"
+    },
+    {
+      "id": "common_voice_en_1205005-common_voice_en_1205007",
+      "ref_sha256": "17e740dd04c5072c440d6ee717f3105eb307f07309fb9db48f4032f7865cfca1"
+    },
+    {
+      "id": "common_voice_en_1205005-common_voice_en_1205008",
+      "ref_sha256": "17e740dd04c5072c440d6ee717f3105eb307f07309fb9db48f4032f7865cfca1"
+    },
+    {
+      "id": "common_voice_en_123125-common_voice_en_123126",
+      "ref_sha256": "7b83861f73dc8f8e90e5d859117941656dfee0e1915e5f19ce45e7f5da312a01"
+    },
+    {
+      "id": "common_voice_en_123125-common_voice_en_123127",
+      "ref_sha256": "7b83861f73dc8f8e90e5d859117941656dfee0e1915e5f19ce45e7f5da312a01"
+    },
+    {
+      "id": "common_voice_en_125386-common_voice_en_125388",
+      "ref_sha256": "148025c5844bbe3a744c5ce422882442bf93f5fdbc95b090aec3eaa20b336bab"
+    },
+    {
+      "id": "common_voice_en_125386-common_voice_en_125389",
+      "ref_sha256": "148025c5844bbe3a744c5ce422882442bf93f5fdbc95b090aec3eaa20b336bab"
+    },
+    {
+      "id": "common_voice_en_137148-common_voice_en_137152",
+      "ref_sha256": "f92d2c69aa3756fb12ca1d44caae8e472e57f06e8d544d0e61758d2bf63225a2"
+    },
+    {
+      "id": "common_voice_en_13900-common_voice_en_13901",
+      "ref_sha256": "bb1af82bc4377c50de1b8f59d6751e04eeaef60a947e97b54a842935d753f4d3"
+    },
+    {
+      "id": "common_voice_en_1416089-common_voice_en_1416090",
+      "ref_sha256": "864870c683eb5f7fdf47b8b79497a948406c2d1ebd3d9044fbd7927ea7f1254a"
+    },
+    {
+      "id": "common_voice_en_1416089-common_voice_en_1416093",
+      "ref_sha256": "864870c683eb5f7fdf47b8b79497a948406c2d1ebd3d9044fbd7927ea7f1254a"
+    },
+    {
+      "id": "common_voice_en_15265-common_voice_en_15266",
+      "ref_sha256": "e9b755e301f5659e48c3f268880a336200437f19e206bd8a21fb5e51b78d26f0"
+    },
+    {
+      "id": "common_voice_en_15265-common_voice_en_15268",
+      "ref_sha256": "e9b755e301f5659e48c3f268880a336200437f19e206bd8a21fb5e51b78d26f0"
+    },
+    {
+      "id": "common_voice_en_153872-common_voice_en_153873",
+      "ref_sha256": "397456ccfb55adaa36d7fd0bbc778fb4c8a5271dde438b1084b0c6d5bdf78515"
+    },
+    {
+      "id": "common_voice_en_153872-common_voice_en_153874",
+      "ref_sha256": "397456ccfb55adaa36d7fd0bbc778fb4c8a5271dde438b1084b0c6d5bdf78515"
+    },
+    {
+      "id": "common_voice_en_155313-common_voice_en_155315",
+      "ref_sha256": "195a6be0eca21041082091f64d8fb8be7028392a4f9b5f019af3c28a1f2390a2"
+    },
+    {
+      "id": "common_voice_en_15734837-common_voice_en_15734838",
+      "ref_sha256": "598e2ecb6da3ca7be04239ab18766bb846f094dff353f3c0e06922449ebf0eb2"
+    },
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+      "ref_sha256": "5bf2eee01e36ce83f8d6499aa2f506bc3fcbab2266aa57afa6764825de4acad1"
+    },
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+      "id": "common_voice_en_621521-common_voice_en_621522",
+      "ref_sha256": "8f9aeb28bbff3da15b4ce9bba83387cdd674c404b7d1dafdfd75b5979c2ae4fe"
+    },
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+      "id": "common_voice_en_628642-common_voice_en_628644",
+      "ref_sha256": "7f52f17595c4fbbb8dfcb53b6901c295fc4baa75edb477372ad928890d56a5ee"
+    },
+    {
+      "id": "common_voice_en_628642-common_voice_en_628645",
+      "ref_sha256": "7f52f17595c4fbbb8dfcb53b6901c295fc4baa75edb477372ad928890d56a5ee"
+    },
+    {
+      "id": "common_voice_en_631730-common_voice_en_631729",
+      "ref_sha256": "a2749f38b0cf3749df4d0b4b85e5363114455cc71e267f10e608003b36a31092"
+    },
+    {
+      "id": "common_voice_en_631730-common_voice_en_631731",
+      "ref_sha256": "a2749f38b0cf3749df4d0b4b85e5363114455cc71e267f10e608003b36a31092"
+    },
+    {
+      "id": "common_voice_en_63703-common_voice_en_63702",
+      "ref_sha256": "1bef2a9c3f3a2daea303c64c7d50c263e5d2abee30dbd1d467cde1c5c997941a"
+    },
+    {
+      "id": "common_voice_en_63703-common_voice_en_63704",
+      "ref_sha256": "1bef2a9c3f3a2daea303c64c7d50c263e5d2abee30dbd1d467cde1c5c997941a"
+    },
+    {
+      "id": "common_voice_en_64065-common_voice_en_64062",
+      "ref_sha256": "35fb3b53b095142c2c90801c4668e3b7865b409c7bf798598279500f6aa1303f"
+    },
+    {
+      "id": "common_voice_en_64065-common_voice_en_64063",
+      "ref_sha256": "35fb3b53b095142c2c90801c4668e3b7865b409c7bf798598279500f6aa1303f"
+    },
+    {
+      "id": "common_voice_en_647713-common_voice_en_647712",
+      "ref_sha256": "54efe5addeb124494325f989acc81e54e2fb4d28718098ba158a144ceffc5fd3"
+    },
+    {
+      "id": "common_voice_en_647713-common_voice_en_647717",
+      "ref_sha256": "54efe5addeb124494325f989acc81e54e2fb4d28718098ba158a144ceffc5fd3"
+    },
+    {
+      "id": "common_voice_en_648428-common_voice_en_648427",
+      "ref_sha256": "03f1d2f02562d29614bd0b50f23fcde101506a281db3409164b010720ec1928a"
+    },
+    {
+      "id": "common_voice_en_648428-common_voice_en_648429",
+      "ref_sha256": "03f1d2f02562d29614bd0b50f23fcde101506a281db3409164b010720ec1928a"
+    },
+    {
+      "id": "common_voice_en_650392-common_voice_en_650389",
+      "ref_sha256": "a56f10b65308d0bad821e9c2c2e64e7f02186f6c15f14eda499cd1a944b642d0"
+    },
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+      "id": "common_voice_en_650392-common_voice_en_650390",
+      "ref_sha256": "a56f10b65308d0bad821e9c2c2e64e7f02186f6c15f14eda499cd1a944b642d0"
+    },
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+      "id": "common_voice_en_652024-common_voice_en_652023",
+      "ref_sha256": "f8a003f48950922e582e0d2834311425f2918db3d16d541db66ba0c211dfc137"
+    },
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+    },
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+      "ref_sha256": "232c99c631add220b49656befc7cfb15508b4aeae24d06e6ee6c2e646b9635f1"
+    },
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+      "ref_sha256": "58ef5d98c3584135d0d504599a7e334c313c61479d1651d6cedb310cb40299b5"
+    },
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+      "id": "common_voice_en_664748-common_voice_en_664751",
+      "ref_sha256": "50b609cd9e5bbbd1bbf2f501603342a0573294d404dbd0ca63c8358834e84959"
+    },
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+      "ref_sha256": "50b609cd9e5bbbd1bbf2f501603342a0573294d404dbd0ca63c8358834e84959"
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+      "ref_sha256": "c7e37bcaad2f65287db41d93d0695488088a465ef7be668e50820299959bea1a"
+    },
+    {
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+      "ref_sha256": "c7e37bcaad2f65287db41d93d0695488088a465ef7be668e50820299959bea1a"
+    },
+    {
+      "id": "common_voice_en_673471-common_voice_en_673472",
+      "ref_sha256": "4b392e305e35232e4fd6000cd4fc0875a6185a0331b47b32148387470697401e"
+    },
+    {
+      "id": "common_voice_en_673471-common_voice_en_673473",
+      "ref_sha256": "4b392e305e35232e4fd6000cd4fc0875a6185a0331b47b32148387470697401e"
+    },
+    {
+      "id": "common_voice_en_674100-common_voice_en_674112",
+      "ref_sha256": "4f5768f262f99fd352ae3d98386b6f0b32e325a013ca0f54820082d2dc00bba4"
+    },
+    {
+      "id": "common_voice_en_674100-common_voice_en_674114",
+      "ref_sha256": "4f5768f262f99fd352ae3d98386b6f0b32e325a013ca0f54820082d2dc00bba4"
+    },
+    {
+      "id": "common_voice_en_678682-common_voice_en_678679",
+      "ref_sha256": "e91ae6873f065bfec9dbb8a23831642609d17373b94fb503ce72a02dc7574eb3"
+    },
+    {
+      "id": "common_voice_en_678682-common_voice_en_678684",
+      "ref_sha256": "e91ae6873f065bfec9dbb8a23831642609d17373b94fb503ce72a02dc7574eb3"
+    },
+    {
+      "id": "common_voice_en_682528-common_voice_en_682530",
+      "ref_sha256": "026b62ebf2faee2c856a33d5c53e4201ba4e9738f9a2a5c6df332b547024968c"
+    },
+    {
+      "id": "common_voice_en_682528-common_voice_en_682536",
+      "ref_sha256": "026b62ebf2faee2c856a33d5c53e4201ba4e9738f9a2a5c6df332b547024968c"
+    },
+    {
+      "id": "common_voice_en_684395-common_voice_en_684398",
+      "ref_sha256": "04f50415737baf990196b5fc8c255b823360a25a53c2d8897fda593749e52646"
+    },
+    {
+      "id": "common_voice_en_684395-common_voice_en_684399",
+      "ref_sha256": "04f50415737baf990196b5fc8c255b823360a25a53c2d8897fda593749e52646"
+    },
+    {
+      "id": "common_voice_en_68569-common_voice_en_68570",
+      "ref_sha256": "2ae528425dfbc1cc78a1a6c72e061ae2cc33dd3c03a9badaacc2f4a66acfd7c3"
+    },
+    {
+      "id": "common_voice_en_68569-common_voice_en_68571",
+      "ref_sha256": "2ae528425dfbc1cc78a1a6c72e061ae2cc33dd3c03a9badaacc2f4a66acfd7c3"
+    },
+    {
+      "id": "common_voice_en_691043-common_voice_en_691044",
+      "ref_sha256": "3ed8cbef09f73f52e64a77083832bde1517f17345be5c24c807be27f61f6407e"
+    },
+    {
+      "id": "common_voice_en_691678-common_voice_en_691680",
+      "ref_sha256": "cd2a997de7ed575b58fb12673c00df16fe24dca0f83b27332645232e66a9641b"
+    },
+    {
+      "id": "common_voice_en_691678-common_voice_en_691681",
+      "ref_sha256": "cd2a997de7ed575b58fb12673c00df16fe24dca0f83b27332645232e66a9641b"
+    },
+    {
+      "id": "common_voice_en_699384-common_voice_en_699385",
+      "ref_sha256": "ce8a365caed3a6de478649ed17d72fde7bcd909f5e35ac12c5eb21260250c569"
+    },
+    {
+      "id": "common_voice_en_699384-common_voice_en_699386",
+      "ref_sha256": "ce8a365caed3a6de478649ed17d72fde7bcd909f5e35ac12c5eb21260250c569"
+    },
+    {
+      "id": "common_voice_en_71427-common_voice_en_71423",
+      "ref_sha256": "bea9305df2b1d412246d5b7c08414f3334b604570e13ff0d84fe6a428ea6a187"
+    },
+    {
+      "id": "common_voice_en_71427-common_voice_en_71425",
+      "ref_sha256": "bea9305df2b1d412246d5b7c08414f3334b604570e13ff0d84fe6a428ea6a187"
+    },
+    {
+      "id": "common_voice_en_75329-common_voice_en_75330",
+      "ref_sha256": "f14760ca31be671c34df5f106b69c492d6b98ca7e44b07a5001005bdedcd414c"
+    },
+    {
+      "id": "common_voice_en_75329-common_voice_en_75332",
+      "ref_sha256": "f14760ca31be671c34df5f106b69c492d6b98ca7e44b07a5001005bdedcd414c"
+    },
+    {
+      "id": "common_voice_en_79862-common_voice_en_79860",
+      "ref_sha256": "3c9bcda465ae248c8af581ff2e5024e71092c840252567fcd30588b75e2d4874"
+    },
+    {
+      "id": "common_voice_en_86172-common_voice_en_86171",
+      "ref_sha256": "d4fbddc671338dae316f14316f31db52fe56c91505d4a51dbba2fb0daaa75456"
+    },
+    {
+      "id": "common_voice_en_86172-common_voice_en_86173",
+      "ref_sha256": "d4fbddc671338dae316f14316f31db52fe56c91505d4a51dbba2fb0daaa75456"
+    },
+    {
+      "id": "common_voice_en_86363-common_voice_en_86360",
+      "ref_sha256": "879f38f41ecccffbf85908dca17eb2856a8a7c8c527bf7acfff470f7e8896f72"
+    },
+    {
+      "id": "common_voice_en_86363-common_voice_en_86365",
+      "ref_sha256": "879f38f41ecccffbf85908dca17eb2856a8a7c8c527bf7acfff470f7e8896f72"
+    },
+    {
+      "id": "common_voice_en_8805512-common_voice_en_8805513",
+      "ref_sha256": "840cad9c31abed4bf2200f848fa00536b915f7efe3fd74645767132846f56f15"
+    },
+    {
+      "id": "common_voice_en_93674-common_voice_en_93672",
+      "ref_sha256": "908fe1c78e959feb66227bd2ff6205d5251a5739c2caaf1fe4988c2dc1ee2a97"
+    },
+    {
+      "id": "common_voice_en_93674-common_voice_en_93675",
+      "ref_sha256": "908fe1c78e959feb66227bd2ff6205d5251a5739c2caaf1fe4988c2dc1ee2a97"
+    },
+    {
+      "id": "common_voice_en_9559-common_voice_en_9560",
+      "ref_sha256": "315a3bc65cdbf3d97e19c6af2bdc4111df4f574addec5164277b426f2e68016b"
+    },
+    {
+      "id": "common_voice_en_9559-common_voice_en_9562",
+      "ref_sha256": "315a3bc65cdbf3d97e19c6af2bdc4111df4f574addec5164277b426f2e68016b"
+    },
+    {
+      "id": "common_voice_en_96260-common_voice_en_96263",
+      "ref_sha256": "a0b83a9286403a32b94c93e3c53e26b546928da7cb8b321f5cf6bc6dd2fc1dd1"
+    }
+  ],
+  "count": 1088,
+  "note": "Local English evaluation data fingerprint; immutable workload split is separately pinned by reference benchmark source."
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/main-profile-control.json b/evidence/minicpmo45-l20x-20261021/plan/main-profile-control.json
new file mode 100644
index 000000000..d1afd1f2e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/main-profile-control.json
@@ -0,0 +1,14 @@
+{
+  "state": "frozen_before_profile_measurement",
+  "kind": "additional existing-main control, not new implementation",
+  "reason": "Current main already ships minicpmo_4_5_turn_mrv2.yaml. A best-performance recommendation must compare this existing profile before attributing improvements to a new change.",
+  "profile": "vllm_omni/deploy/minicpmo_4_5_turn_mrv2.yaml",
+  "changes_already_in_main": [
+    "native model runner v2 on all stages",
+    "Talker and Code2Wav max_num_seqs 8",
+    "CFM TF32 opt-in",
+    "HiFT graph batch buckets 1,2,4,8",
+    "bounded first-chunk express scheduling"
+  ],
+  "measurement": "Same pinned official model, canonical requests and disjoint tuning pool. Quality gates remain unchanged. No new-code gain can be claimed merely by selecting this main profile."
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/model-hf-check.json b/evidence/minicpmo45-l20x-20261021/plan/model-hf-check.json
new file mode 100644
index 000000000..b0d7191ac
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/model-hf-check.json
@@ -0,0 +1,18 @@
+{
+  "model-00001-of-00004.safetensors": {
+    "local": "30c40b9a10386c1bc404568d8829e5aada2e3501d9de6fb46ff80451aff7e077",
+    "expected": "30c40b9a10386c1bc404568d8829e5aada2e3501d9de6fb46ff80451aff7e077"
+  },
+  "model-00002-of-00004.safetensors": {
+    "local": "fe0faef420aca8f771bec1f9fcfaae01206c56b8e64e4429a1ff500c962fbf96",
+    "expected": "fe0faef420aca8f771bec1f9fcfaae01206c56b8e64e4429a1ff500c962fbf96"
+  },
+  "model-00003-of-00004.safetensors": {
+    "local": "5d0b20153f9bfa88ebcd1cb6bbd5b7cac4c217b3cafb137a291a1b380d8b7821",
+    "expected": "5d0b20153f9bfa88ebcd1cb6bbd5b7cac4c217b3cafb137a291a1b380d8b7821"
+  },
+  "model-00004-of-00004.safetensors": {
+    "local": "f61addf4747c94fedcaee059e5d9918ed15543beec494404139a99f2f86c9b31",
+    "expected": "f61addf4747c94fedcaee059e5d9918ed15543beec494404139a99f2f86c9b31"
+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/model-manifest.json b/evidence/minicpmo45-l20x-20261021/plan/model-manifest.json
new file mode 100644
index 000000000..93cbdc879
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/model-manifest.json
@@ -0,0 +1,18 @@
+{
+  "model-00001-of-00004.safetensors": {
+    "size": 5273477136,
+    "sha256": "30c40b9a10386c1bc404568d8829e5aada2e3501d9de6fb46ff80451aff7e077"
+  },
+  "model-00002-of-00004.safetensors": {
+    "size": 5301855080,
+    "sha256": "fe0faef420aca8f771bec1f9fcfaae01206c56b8e64e4429a1ff500c962fbf96"
+  },
+  "model-00003-of-00004.safetensors": {
+    "size": 5301855048,
+    "sha256": "5d0b20153f9bfa88ebcd1cb6bbd5b7cac4c217b3cafb137a291a1b380d8b7821"
+  },
+  "model-00004-of-00004.safetensors": {
+    "size": 2866549964,
+    "sha256": "f61addf4747c94fedcaee059e5d9918ed15543beec494404139a99f2f86c9b31"
+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/model-metadata-check.json b/evidence/minicpmo45-l20x-20261021/plan/model-metadata-check.json
new file mode 100644
index 000000000..11d3dbe98
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/model-metadata-check.json
@@ -0,0 +1,47 @@
+{
+  "config.json": {
+    "local_sha256": "547e5a0675e9ed9bbb1bcd9836e26bf8f5361f6491041b71a915cc56daf0934e",
+    "reference_sha256": "b0c03cf9f0cfc1178ade50e4ba62727ca7a77aa6a6a71eda6668d8f289e96c1d",
+    "matches": false
+  },
+  "generation_config.json": {
+    "local_sha256": "cf29e6aecb72503bd220cccb6d86bde84a9f57e77c741dedb8670036106e2119",
+    "reference_sha256": "cf29e6aecb72503bd220cccb6d86bde84a9f57e77c741dedb8670036106e2119",
+    "matches": true
+  },
+  "tokenizer_config.json": {
+    "local_sha256": "cb1325fdb3b0b9f38b64607399d3e163fbe32bf49c273c229755a0dbce83f813",
+    "reference_sha256": "cb1325fdb3b0b9f38b64607399d3e163fbe32bf49c273c229755a0dbce83f813",
+    "matches": true
+  },
+  "tokenizer.json": {
+    "local_sha256": "6d55eb34389b8c87403763cc1d80447d91c85c7cd39cd5e3c0dc2d49edad989d",
+    "reference_sha256": "6d55eb34389b8c87403763cc1d80447d91c85c7cd39cd5e3c0dc2d49edad989d",
+    "matches": true
+  },
+  "preprocessor_config.json": {
+    "local_sha256": "10350f12d5636b24e19265d72c5543b462251f54ca18afaa147f6f2ece9591e0",
+    "reference_sha256": "10350f12d5636b24e19265d72c5543b462251f54ca18afaa147f6f2ece9591e0",
+    "matches": true
+  },
+  "processing_minicpmo.py": {
+    "local_sha256": "3a1f017339b92c2fa768d7737db76cc4689d2280b68a71866b06f7dedc8ac1c2",
+    "reference_sha256": "3a1f017339b92c2fa768d7737db76cc4689d2280b68a71866b06f7dedc8ac1c2",
+    "matches": true
+  },
+  "configuration_minicpmo.py": {
+    "local_sha256": "78c431da627566c155554a5a2333dcb20bb1fac694f654cb51b56dde338414bd",
+    "reference_sha256": "b0c56c192d4aa57d3dc358338a4a93413b8b68e7c7a7c5b82a5af35afab1d86a",
+    "matches": false
+  },
+  "modeling_minicpmo.py": {
+    "local_sha256": "22fd96cb8195b3f63bd14e324fd726ab7f195faf7d0e1eb494c418a1d3c65ee3",
+    "reference_sha256": "25359f891d1aa81de16b51a24a97b8c8262b83ce3920c36b92be441fde8e4282",
+    "matches": false
+  },
+  "tokenization_minicpmo_fast.py": {
+    "local_sha256": "c9c71d0d7ef0c113829e2d810619c9e0a69cffe04c732c4d80599b40a33bc7bf",
+    "reference_sha256": "c9c71d0d7ef0c113829e2d810619c9e0a69cffe04c732c4d80599b40a33bc7bf",
+    "matches": true
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/mps-runspec-redacted.json b/evidence/minicpmo45-l20x-20261021/plan/mps-runspec-redacted.json
new file mode 100644
index 000000000..2987419fc
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/mps-runspec-redacted.json
@@ -0,0 +1,61 @@
+{
+  "repo": "<VLLM_MAIN>",
+  "baseline_command": [
+    "<BENCH_PYTHON>",
+    "<ARTIFACT_ROOT>/run_baseline.py",
+    "--adapter",
+    "vllm-omni",
+    "--url",
+    "http://127.0.0.1:29161",
+    "--out",
+    "<ARTIFACT_ROOT>/vllm-main-tuning",
+    "--id-set",
+    "tuning",
+    "--requests",
+    "64",
+    "--repeats",
+    "1"
+  ],
+  "candidate_command": [
+    "<BENCH_PYTHON>",
+    "<ARTIFACT_ROOT>/run_baseline.py",
+    "--adapter",
+    "vllm-omni",
+    "--url",
+    "http://127.0.0.1:29191",
+    "--out",
+    "<ARTIFACT_ROOT>/vllm-mps-tuning",
+    "--id-set",
+    "tuning",
+    "--requests",
+    "64",
+    "--repeats",
+    "1"
+  ],
+  "candidate_repo": "<VLLM_MAIN>",
+  "repo_type": "vllm_omni",
+  "backend": "cuda",
+  "scenario": "audio.tts",
+  "mode": "config",
+  "validation_command": null,
+  "metric_key": "throughput_frames_s",
+  "metric_unit": "frames/s",
+  "comparison_scope": "steady_state_served_audio",
+  "direction": "maximize",
+  "repetitions": 1,
+  "min_improvement_pct": 0.0,
+  "max_minutes": 120.0,
+  "workload_id": "seedtts-en-v1-disjoint-tuning-64",
+  "model": "openbmb/MiniCPM-o-4_5",
+  "model_revision": "503e754207c94da6bb26850b4469f367c9ea3582",
+  "agent": "manual",
+  "device_ids": [
+    "6",
+    "1"
+  ],
+  "revision": "aa3fd1d9b7f5c7191dec11975ac0aa7c4c4a18c5",
+  "device": "NVIDIA L20X",
+  "executor": "default",
+  "snapshot_id": "mps-single-plane-screen",
+  "output_dir": "<ARTIFACT_ROOT>/runspec-artifacts"
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/official-model-manifest.json b/evidence/minicpmo45-l20x-20261021/plan/official-model-manifest.json
new file mode 100644
index 000000000..a62963659
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/official-model-manifest.json
@@ -0,0 +1,121 @@
+{
+  "revision": "503e754207c94da6bb26850b4469f367c9ea3582",
+  "files": {
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+    "tokenizer.json": {
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+      "verified_against": "huggingface_lfs_sha256"
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+    "tokenizer_config.json": {
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+      "verified_against": "downloaded_pinned_revision"
+    },
+    "utils.py": {
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+    "vocab.json": {
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+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/search-plan.json b/evidence/minicpmo45-l20x-20261021/plan/search-plan.json
new file mode 100644
index 000000000..f6ef9082d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/search-plan.json
@@ -0,0 +1,44 @@
+{
+  "state": "frozen_before_candidate_measurement",
+  "acceptance_issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+  "primary": "C16 and C32 delivered-audio throughput",
+  "report": [
+    "C1,C2,C4,C8,C16,C32 throughput",
+    "TTFA p50/p95",
+    "RTF mean",
+    "completion coverage",
+    "audio duration",
+    "playback stalls"
+  ],
+  "hypotheses": [
+    {
+      "id": "mps",
+      "plane": "infra",
+      "change": "Enable the existing private cuda_mps daemon for colocated stages.",
+      "rationale": "Test whether separate stage CUDA contexts prevent useful concurrent kernel execution.",
+      "precondition": "Baseline stage timing and load observations completed."
+    },
+    {
+      "id": "encoder-capture",
+      "plane": "model",
+      "change": "Enable existing bounded exact-shape encoder capture after startup, with identical precision and chunk semantics.",
+      "rationale": "Startup continuation capture leaves recurring prompt/tail shapes eager.",
+      "precondition": "Baseline timing/source attribution supports encoder launch overhead; numerical/state checks and memory budget pass."
+    },
+    {
+      "id": "cfm-microbatch",
+      "plane": "model",
+      "change": "Compare existing Whole-Euler micro-batch sizes 4 and 8 with otherwise identical settings.",
+      "rationale": "Larger actual ready batches may amortize graph replay; verify shape/rounding and memory effects.",
+      "precondition": "Baseline demonstrates multirow decode batches; assess quality independently."
+    }
+  ],
+  "quality_gates": {
+    "request_completion": "All measured requests must finish successfully with nonempty finite audio and no missing/duplicated chunks.",
+    "sampling": "Keep checkpoint, prompt construction, sampling and output limits fixed.",
+    "speech": "Use fixed baseline/candidate outputs and identical existing scorer settings. WER must not increase, speaker similarity and available UTMOS must not decrease; report repeat/coverage limitations.",
+    "numerical": "Exact-shape graph-only changes require eager/replay numerical and state-ownership checks."
+  },
+  "performance_gate": "C16/C32 improvement must persist across repeated served comparisons; retain measured variation and latency tradeoffs. No global optimum claim.",
+  "inconclusive": "Missing required quality, environment identity or matched comparison evidence prevents PASS."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/sglang-packages.json b/evidence/minicpmo45-l20x-20261021/plan/sglang-packages.json
new file mode 100644
index 000000000..422fb6317
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/sglang-packages.json
@@ -0,0 +1,283 @@
+{
+  "Cython": "3.3.0",
+  "Jinja2": "3.1.6",
+  "MarkupSafe": "3.0.4",
+  "PyYAML": "6.0.3",
+  "Pygments": "2.21.0",
+  "RapidFuzz": "3.14.6",
+  "WeTextProcessing": "1.2.0",
+  "accelerate": "1.15.0",
+  "addict": "2.4.0",
+  "aiohappyeyeballs": "2.7.1",
+  "aiohttp": "3.14.5",
+  "aiosignal": "1.4.0",
+  "airportsdata": "20260905",
+  "annotated-doc": "0.0.5",
+  "annotated-types": "0.8.0",
+  "anthropic": "1.17.0",
+  "anyio": "4.15.1",
+  "apache-tvm-ffi": "0.1.11",
+  "asttokens": "3.0.2",
+  "attrs": "26.1.0",
+  "audioread": "3.1.0",
+  "av": "19.0.1",
+  "blobfile": "3.0.0",
+  "brotli": "1.2.0",
+  "build": "1.6.1",
+  "cache_dit": "1.3.0",
+  "cdifflib": "1.2.9",
+  "certifi": "2026.10.19",
+  "cffi": "2.1.1",
+  "charset-normalizer": "3.5.2",
+  "click": "8.5.0",
+  "cloudpickle": "3.1.2",
+  "compressed-tensors": "0.18.0",
+  "cryptography": "50.0.2",
+  "cuda-bindings": "13.4.4",
+  "cuda-core": "1.2.2",
+  "cuda-pathfinder": "1.8.3",
+  "cuda-python": "13.4.4",
+  "cuda-tile": "1.6.0rc5",
+  "cuda-toolkit": "13.0.3.0",
+  "datasets": "5.1.0",
+  "decorator": "5.3.1",
+  "decord": "0.6.0",
+  "diffusers": "0.37.0",
+  "dill": "0.4.1",
+  "diskcache": "5.6.3",
+  "distro": "1.9.0",
+  "docstring_parser": "0.18.0",
+  "dots.tts": "0.2.1",
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+  "humming-kernels": "0.1.12",
+  "hydra-core": "1.4.0rc1",
+  "idna": "3.20",
+  "imageio": "2.36.0",
+  "imageio-ffmpeg": "0.5.1",
+  "importlib_metadata": "9.0.1",
+  "importlib_resources": "7.1.0",
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+  "iniconfig": "2.3.1",
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+  "jedi": "0.20.1",
+  "jiter": "0.17.0",
+  "jiwer": "4.0.0",
+  "joblib": "1.6.0",
+  "jsonschema": "4.26.0",
+  "jsonschema-specifications": "2025.9.1",
+  "kernels": "0.14.1",
+  "kernels-data": "0.16.2",
+  "langcodes": "3.5.1",
+  "language_data": "1.4.0",
+  "lark": "1.3.1",
+  "lazy-loader": "0.6",
+  "librosa": "1.0.0",
+  "lingua-language-detector": "2.2.0",
+  "llguidance": "1.9.1",
+  "llvmlite": "0.47.0",
+  "logger": "1.4",
+  "loguru": "0.7.3",
+  "lxml": "7.0.0b1",
+  "marisa-trie": "1.4.1",
+  "markdown-it-py": "4.2.0",
+  "matplotlib-inline": "0.2.2",
+  "mdurl": "0.1.2",
+  "mistral_common": "1.12.0",
+  "ml_dtypes": "0.6.0",
+  "modelscope": "1.40.2",
+  "modelscope-hub": "0.4.6",
+  "mooncake-transfer-engine-cuda13": "0.3.13.post1",
+  "more-itertools": "11.2.1",
+  "mpmath": "1.3.0",
+  "msgpack": "1.2.3",
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+  "narwhals": "2.27.1",
+  "nccl4py": "0.6.0",
+  "nemo_text_processing": "1.2.0",
+  "nest-asyncio": "1.6.0",
+  "networkx": "3.7",
+  "ninja": "1.13.2",
+  "nixl-cu13": "1.5.0",
+  "numba": "0.65.1",
+  "numpy": "2.3.5",
+  "nvidia-cublas": "13.1.1.3",
+  "nvidia-cuda-cccl": "13.3.4.3.1",
+  "nvidia-cuda-crt": "13.4.92",
+  "nvidia-cuda-cupti": "13.0.85",
+  "nvidia-cuda-nvcc": "13.4.92",
+  "nvidia-cuda-nvdisasm": "13.4.92",
+  "nvidia-cuda-nvrtc": "13.0.88",
+  "nvidia-cuda-runtime": "13.0.96",
+  "nvidia-cudnn-cu13": "9.20.0.48",
+  "nvidia-cudnn-frontend": "1.31.0",
+  "nvidia-cufft": "12.0.0.61",
+  "nvidia-cufile": "1.15.1.6",
+  "nvidia-curand": "10.4.0.35",
+  "nvidia-cusolver": "12.0.4.66",
+  "nvidia-cusparse": "12.6.3.3",
+  "nvidia-cusparselt-cu13": "0.8.1",
+  "nvidia-cutlass-dsl": "4.6.2",
+  "nvidia-cutlass-dsl-libs-base": "4.6.2",
+  "nvidia-cutlass-dsl-libs-core": "4.6.2",
+  "nvidia-cutlass-dsl-libs-cu12": "4.6.2",
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+  "nvidia-ml-py": "13.615.71",
+  "nvidia-nccl-cu13": "2.29.7",
+  "nvidia-nvjitlink": "13.4.92",
+  "nvidia-nvshmem-cu13": "3.4.5",
+  "nvidia-nvtx": "13.0.85",
+  "nvidia-nvvm": "13.4.92",
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+  "onnxruntime-gpu": "1.31.0",
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+  "openai-harmony": "0.0.4",
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+  "pyproject_hooks": "1.3.3",
+  "pytest": "9.1.1",
+  "pytest-asyncio": "1.4.0",
+  "python-dateutil": "2.9.0.post0",
+  "python-multipart": "0.0.32",
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+  "smg-grpc-servicer": "0.14.0",
+  "sniffio": "1.3.1",
+  "soundfile": "0.13.1",
+  "sox": "1.5.0",
+  "soxr": "1.1.0",
+  "stack-data": "0.6.3",
+  "starlette": "1.9.0",
+  "sympy": "1.14.0",
+  "tabulate": "0.10.0",
+  "threadpoolctl": "3.7.0",
+  "tiktoken": "0.14.0",
+  "tilelang": "0.1.12",
+  "timm": "1.0.16",
+  "tokenizers": "0.22.2",
+  "tokenspeed-mla": "0.1.8",
+  "tokenspeed-triton": "3.9.10.post20261008",
+  "tomlkit": "0.14.0",
+  "torch": "2.13.0+cu130",
+  "torch-einops-utils": "0.1.37",
+  "torch_c_dlpack_ext": "0.1.5",
+  "torch_memory_saver": "0.0.10",
+  "torchaudio": "2.11.0+cu130",
+  "torchcodec": "0.15.0+cu130",
+  "torchdiffeq": "0.2.5",
+  "torchvision": "0.28.0+cu130",
+  "tqdm": "4.70.1",
+  "traitlets": "5.16.1",
+  "transformers": "5.12.1",
+  "triton": "3.7.1",
+  "truststore": "0.10.5",
+  "typeguard": "4.6.0",
+  "typer": "0.27.3",
+  "typing-inspection": "0.4.4",
+  "typing_extensions": "4.16.0",
+  "urllib3": "2.8.0",
+  "uvicorn": "0.54.0",
+  "uvloop": "0.23.0",
+  "watchfiles": "1.3.0",
+  "wcwidth": "0.9.3",
+  "websockets": "17.3",
+  "wget": "3.2",
+  "wrapt": "2.5.2rc1",
+  "x-transformers": "2.31.8",
+  "xgrammar": "0.2.7",
+  "xxhash": "4.0.2",
+  "yarl": "1.25.1",
+  "z3-solver": "4.15.4.0",
+  "zhon": "2.1.1",
+  "zipp": "4.1.1",
+  "zstandard": "0.25.0"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/speaker-device-hypothesis.json b/evidence/minicpmo45-l20x-20261021/plan/speaker-device-hypothesis.json
new file mode 100644
index 000000000..dec60d338
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/speaker-device-hypothesis.json
@@ -0,0 +1,22 @@
+{
+  "state": "frozen_before_candidate_measurement",
+  "plane": "model",
+  "hypothesis": "CUDA MiniCPM Code2Wav currently leaves CAM++ speaker extraction on a single-threaded CPU ONNX session unless the entire DiT TensorRT path is enabled. Decoupling the existing speaker-only TensorRT backend can remove serial prompt setup work without changing DiT, HiFT, chunks, or sampling.",
+  "source_paths": [
+    "vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py:_build_backend",
+    "vllm_omni/model_executor/models/step_audio2/step_audio2_token2wav.py:spk_model",
+    "vllm_omni/model_executor/models/step_audio2/step_audio2_token2wav.py:enable_device_spk_embedding",
+    "vllm_omni/model_executor/models/cosyvoice3/speaker_embedding_trt.py"
+  ],
+  "preconditions": [
+    "Measure CPU-vs-device latency on identical fbank inputs before served attribution.",
+    "Keep CUDA default behavior unchanged; require explicit token2wav_device_spk=true.",
+    "Confirm the device backend uses the same campplus.onnx weights and retain numerical/quality deltas."
+  ],
+  "numerical_gate": {
+    "normalized_embedding_cosine_min": 0.99999,
+    "normalized_embedding_abs_error_max": 0.001,
+    "inputs": "Fixed tuning reference fbank features; include short and normalized six-second shapes."
+  },
+  "service_gate": "Existing frozen search-plan quality and repeated served C16/C32 gates apply; isolated speaker microbench cannot establish a service gain."
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/speaker-microbatch-control.json b/evidence/minicpmo45-l20x-20261021/plan/speaker-microbatch-control.json
new file mode 100644
index 000000000..c22f4a52a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/speaker-microbatch-control.json
@@ -0,0 +1,19 @@
+{
+  "plane": "model",
+  "hypothesis": "After moving serialized CPU speaker work to CUDA, a larger CFM microbatch may become useful. Compare against speaker-only before selecting.",
+  "changed_setting": {
+    "micro_batch_size": [
+      4,
+      8
+    ]
+  },
+  "fixed_setting": {
+    "token2wav_device_spk": true
+  },
+  "dataset": "same disjoint tuning 64",
+  "concurrency": [
+    16,
+    32
+  ],
+  "gate": "Must improve both high-concurrency throughput cells; generated speech quality remains separately required; no frozen gates changed."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/speaker-mrv2-control.json b/evidence/minicpmo45-l20x-20261021/plan/speaker-mrv2-control.json
new file mode 100644
index 000000000..7b97cf428
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/speaker-mrv2-control.json
@@ -0,0 +1,18 @@
+{
+  "plane": "model",
+  "hypothesis": "MRv2 host scheduling may improve throughput after removing CPU speaker extraction, despite no gain in the unmodified-main control.",
+  "control": "existing main MRv2 profile",
+  "changed_setting": {
+    "token2wav_device_spk": true
+  },
+  "dataset": "same disjoint tuning64",
+  "concurrency": [
+    1,
+    2,
+    4,
+    8,
+    16,
+    32
+  ],
+  "gate": "Same frozen performance and quality gates; compare with speaker V1 before selection."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/vllm-main-resolved-config.json b/evidence/minicpmo45-l20x-20261021/plan/vllm-main-resolved-config.json
new file mode 100644
index 000000000..668423107
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/vllm-main-resolved-config.json
@@ -0,0 +1,179 @@
+{
+  "pipeline": "minicpmo_4_5",
+  "async_chunk": true,
+  "session_mode": "turn",
+  "duplex_session": {
+    "max_sessions": 16
+  },
+  "trust_remote_code": true,
+  "enable_prefix_caching": false,
+  "connectors": {
+    "connector_of_shared_memory": {
+      "name": "SharedMemoryConnector",
+      "extra": {
+        "connector_get_sleep_s": 0.01,
+        "connector_get_max_wait_first_chunk": 3000,
+        "connector_get_max_wait": 300,
+        "codec_chunk_frames": 25,
+        "codec_left_context_frames": 3,
+        "enable_hift_graph": true,
+        "hift_graph_continuation_frames": [
+          4,
+          28
+        ],
+        "hift_graph_exact_batch_sizes": [
+          1
+        ],
+        "enable_cfm_graph": true,
+        "cfm_fused_body": true,
+        "enable_code2wav_encoder_graph": true,
+        "code2wav_encoder_graph_rows": 4,
+        "code2wav_encoder_max_graphs": 12,
+        "code2wav_encoder_capture_after": 8,
+        "max_graph_batch": 32,
+        "micro_batch_size": 4,
+        "cfm_precapture_empty_cache": true,
+        "cfm_max_graphs": 32
+      }
+    }
+  },
+  "stages": [
+    {
+      "stage_id": 0,
+      "max_num_seqs": 16,
+      "gpu_memory_utilization": 0.55,
+      "enforce_eager": false,
+      "tensor_parallel_size": 1,
+      "max_num_batched_tokens": 16384,
+      "devices": "0",
+      "interleave_mm_strings": true,
+      "media_io_kwargs": {
+        "video": {
+          "fps": 1,
+          "num_frames": 128
+        }
+      },
+      "limit_mm_per_prompt": {
+        "image": 64,
+        "audio": 64,
+        "video": 1
+      },
+      "default_sampling_params": {
+        "temperature": 0.0,
+        "top_p": 1.0,
+        "top_k": -1,
+        "max_tokens": 2048,
+        "seed": 42,
+        "detokenize": true,
+        "repetition_penalty": 1.0
+      }
+    },
+    {
+      "stage_id": 1,
+      "max_num_seqs": 16,
+      "gpu_memory_utilization": 0.15,
+      "enforce_eager": false,
+      "max_num_batched_tokens": 8192,
+      "max_model_len": 4096,
+      "devices": "0",
+      "output_connectors": {
+        "to_stage_2": "connector_of_shared_memory"
+      },
+      "default_sampling_params": {
+        "temperature": 0.8,
+        "top_p": 0.85,
+        "top_k": 25,
+        "repetition_penalty": 1.05,
+        "min_tokens": 50,
+        "max_tokens": 4096,
+        "seed": 42,
+        "detokenize": false
+      }
+    },
+    {
+      "stage_id": 2,
+      "max_num_seqs": 16,
+      "gpu_memory_utilization": 0.18,
+      "enforce_eager": true,
+      "enable_chunked_prefill": false,
+      "max_num_batched_tokens": 65536,
+      "max_model_len": 65536,
+      "devices": "0",
+      "input_connectors": {
+        "from_stage_1": "connector_of_shared_memory"
+      },
+      "default_sampling_params": {
+        "temperature": 0.0,
+        "top_p": 1.0,
+        "top_k": -1,
+        "max_tokens": 65536,
+        "detokenize": true
+      }
+    }
+  ],
+  "platforms": {
+    "npu": {
+      "stages": [
+        {
+          "stage_id": 0,
+          "max_num_seqs": 8,
+          "gpu_memory_utilization": 0.55,
+          "additional_config": {
+            "encoder_enable_npu_graph": true,
+            "encoder_max_npu_graphs": 4
+          },
+          "max_num_batched_tokens": 8192,
+          "enable_prefix_caching": false,
+          "compilation_config": {
+            "cudagraph_mode": "PIECEWISE"
+          }
+        },
+        {
+          "stage_id": 1,
+          "max_num_seqs": 8,
+          "kv_cache_memory_bytes": 4294967296,
+          "gpu_memory_utilization": 0.1,
+          "max_num_batched_tokens": 8192,
+          "speculative_config": {
+            "method": "ngram",
+            "num_speculative_tokens": 7,
+            "prompt_lookup_min": 1,
+            "prompt_lookup_max": 1
+          },
+          "async_scheduling": false,
+          "default_sampling_params": {
+            "stop_token_ids": [
+              1
+            ]
+          },
+          "compilation_config": {
+            "cudagraph_mode": "FULL_DECODE_ONLY"
+          }
+        },
+        {
+          "stage_id": 2,
+          "max_num_seqs": 8,
+          "gpu_memory_utilization": 0.22,
+          "additional_config": {
+            "code2wav_enable_npu_graph": true,
+            "cfm_graph_batch_buckets": [
+              1,
+              2,
+              4,
+              8
+            ],
+            "code2wav_max_npu_graphs": 32
+          }
+        }
+      ]
+    },
+    "cuda": {
+      "stages": [
+        {
+          "stage_id": 1,
+          "kv_cache_memory_bytes": 4294967296
+        }
+      ]
+    }
+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/plan/vllm-packages.json b/evidence/minicpmo45-l20x-20261021/plan/vllm-packages.json
new file mode 100644
index 000000000..b9febd019
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/vllm-packages.json
@@ -0,0 +1,524 @@
+{
+  "CairoSVG": "2.9.0",
+  "Farama-Notifications": "0.0.6",
+  "FlagEmbedding": "1.4.0",
+  "GitPython": "3.1.50",
+  "HyperPyYAML": "1.2.3",
+  "ImageIO": "2.37.4",
+  "Jinja2": "3.1.6",
+  "Markdown": "3.10.2",
+  "MarkupSafe": "3.0.3",
+  "OpenCC": "1.4.1",
+  "PyJWT": "2.12.1",
+  "PyYAML": "6.0.3",
+  "Pygments": "2.21.0",
+  "RapidFuzz": "3.14.5",
+  "Werkzeug": "3.1.8",
+  "absl-py": "2.4.0",
+  "accelerate": "1.12.0",
+  "addict": "2.4.0",
+  "aenum": "3.1.16",
+  "aiohappyeyeballs": "2.6.1",
+  "aiohttp": "3.14.5",
+  "aiohttp-cors": "0.8.1",
+  "aiosignal": "1.4.0",
+  "airportsdata": "20260315",
+  "aliyun-python-sdk-core": "2.16.0",
+  "aliyun-python-sdk-kms": "2.16.5",
+  "annotated-doc": "0.0.5",
+  "annotated-types": "0.7.0",
+  "anthropic": "0.101.0",
+  "antlr4-python3-runtime": "4.9.3",
+  "anyascii": "0.3.3",
+  "anyio": "4.15.1",
+  "apache-tvm-ffi": "0.1.11",
+  "argbind": "0.3.9",
+  "astor": "0.8.1",
+  "asttokens": "3.0.1",
+  "attrs": "26.1.0",
+  "audioread": "3.1.0",
+  "av": "18.0.0",
+  "babel": "2.18.0",
+  "backrefs": "7.0",
+  "beautifulsoup4": "4.15.0",
+  "better-profanity": "0.7.0",
+  "blake3": "1.0.8",
+  "blobfile": "3.0.0",
+  "bracex": "2.6",
+  "brotli": "1.2.0",
+  "build": "1.5.0",
+  "cache_dit": "1.5.0",
+  "cachetools": "7.1.1",
+  "cairocffi": "1.7.1",
+  "cbor": "1.0.0",
+  "cbor2": "6.0.1",
+  "certifi": "2026.10.19",
+  "cffi": "2.0.0",
+  "cfgv": "3.5.0",
+  "charset-normalizer": "3.4.7",
+  "click": "8.5.0",
+  "cloudpickle": "3.1.2",
+  "colorama": "0.4.6",
+  "coloredlogs": "15.0.1",
+  "colorful": "0.5.8",
+  "compressed-tensors": "0.17.0",
+  "contourpy": "1.3.3",
+  "contractions": "0.1.73",
+  "cosmos-guardrail": "0.3.1",
+  "coverage": "7.14.0",
+  "crcmod": "1.7",
+  "cryptography": "48.0.0",
+  "csscompressor": "0.9.5",
+  "cssselect2": "0.9.0",
+  "cuda-bindings": "13.0.3",
+  "cuda-core": "1.0.1",
+  "cuda-pathfinder": "1.6.0",
+  "cuda-python": "13.0.3",
+  "cuda-tile": "1.5.0",
+  "cuda-toolkit": "13.0.3.0",
+  "cycler": "0.12.1",
+  "datasets": "3.6.0",
+  "decorator": "5.2.1",
+  "decord": "0.6.0",
+  "decord2": "3.4.0",
+  "defusedxml": "0.7.1",
+  "depyf": "0.20.0",
+  "descript-audio-codec": "1.0.0",
+  "descript-audiotools": "0.7.2",
+  "diffusers": "0.40.0",
+  "dill": "0.3.8",
+  "diskcache": "5.6.3",
+  "distlib": "0.4.0",
+  "distro": "1.9.0",
+  "dm-tree": "0.1.10",
+  "dnspython": "2.8.0",
+  "docopt": "0.6.2",
+  "docstring_parser": "0.18.0",
+  "edge-tts": "7.2.8",
+  "editdistance": "0.8.1",
+  "einops": "0.8.2",
+  "einx": "0.4.3",
+  "email-validator": "2.3.0",
+  "et_xmlfile": "2.0.0",
+  "execnet": "2.1.2",
+  "executing": "2.2.1",
+  "fa3_fwd": "0.0.3",
+  "fastapi": "0.136.1",
+  "fastapi-cli": "0.0.24",
+  "fastapi-cloud-cli": "0.17.1",
+  "fastar": "0.11.0",
+  "fastsafetensors": "0.3.3",
+  "ffmpy": "1.0.0",
+  "filelock": "4.2.4",
+  "fire": "0.7.1",
+  "flashinfer-cubin": "0.6.13",
+  "flashinfer-jit-cache": "0.7.0.post1+cu130",
+  "flashinfer-jit-cache-sm100a": "0.7.0.post1+cu130",
+  "flashinfer-jit-cache-sm103a": "0.7.0.post1+cu130",
+  "flashinfer-jit-cache-sm120f": "0.7.0.post1+cu130",
+  "flashinfer-jit-cache-sm80": "0.7.0.post1+cu130",
+  "flashinfer-jit-cache-sm89": "0.7.0.post1+cu130",
+  "flashinfer-jit-cache-sm90a": "0.7.0.post1+cu130",
+  "flashinfer-python": "0.7.0.post1",
+  "flatbuffers": "25.12.19",
+  "flatten-dict": "0.5.0",
+  "fonttools": "4.62.1",
+  "frozendict": "2.4.7",
+  "frozenlist": "1.8.0",
+  "fsspec": "2026.9.0",
+  "funasr": "1.3.29",
+  "gguf": "0.19.0",
+  "ghp-import": "2.1.0",
+  "gitdb": "4.0.12",
+  "google-api-core": "2.30.3",
+  "google-auth": "2.53.0",
+  "googleapis-common-protos": "1.75.0",
+  "gradio": "6.14.0",
+  "gradio_client": "2.5.0",
+  "griffelib": "2.0.2",
+  "groovy": "0.1.2",
+  "grpcio": "1.75.1",
+  "grpcio-health-checking": "1.75.1",
+  "grpcio-reflection": "1.75.1",
+  "grpcio-tools": "1.75.1",
+  "gymnasium": "1.3.0",
+  "h11": "0.16.0",
+  "hf-gradio": "0.4.1",
+  "hf-xet": "1.7.0",
+  "hf_transfer": "0.1.9",
+  "htmlmin2": "0.1.13",
+  "httpcore": "1.0.9",
+  "httpcore2": "2.13.1",
+  "httptools": "0.7.1",
+  "httpx": "0.28.1",
+  "httpx-sse": "0.4.3",
+  "httpx2": "2.13.1",
+  "huggingface_hub": "1.33.0",
+  "humanfriendly": "10.0",
+  "humming-kernels": "0.1.17",
+  "hydra-core": "1.3.2",
+  "id": "1.6.1",
+  "identify": "2.6.19",
+  "idna": "3.20",
+  "ijson": "3.5.0",
+  "imageio-ffmpeg": "0.6.0",
+  "importlib_metadata": "8.7.1",
+  "importlib_resources": "7.1.0",
+  "inflect": "7.5.0",
+  "iniconfig": "2.3.0",
+  "inscriptis": "2.7.1",
+  "instanttensor": "0.2.2",
+  "interegular": "0.3.3",
+  "ipython": "9.14.0",
+  "ipython_pygments_lexers": "1.1.1",
+  "ir_datasets": "0.5.11",
+  "jaconv": "0.5.0",
+  "jamo": "0.4.1",
+  "janus": "2.0.0",
+  "jedi": "0.20.0",
+  "jieba": "0.42.1",
+  "jiter": "0.16.0",
+  "jiwer": "4.0.0",
+  "jmespath": "0.10.0",
+  "joblib": "1.5.3",
+  "jsmin": "3.0.1",
+  "jsonschema": "4.26.0",
+  "jsonschema-specifications": "2025.9.1",
+  "julius": "0.2.7",
+  "kaldifst": "1.8.0",
+  "kaldiio": "2.18.1",
+  "kernels": "0.16.1",
+  "kernels-data": "0.15.2",
+  "kiwisolver": "1.5.0",
+  "lark": "1.2.2",
+  "lazy-loader": "0.5",
+  "librosa": "0.11.0",
+  "lightning-utilities": "0.15.3",
+  "llguidance": "1.7.5",
+  "llvmlite": "0.47.0",
+  "lm-format-enforcer": "0.11.3",
+  "logger": "1.4",
+  "loguru": "0.7.3",
+  "lpips": "0.1.4",
+  "lxml": "6.0.4",
+  "lz4": "4.4.5",
+  "markdown-it-py": "4.2.0",
+  "markdown2": "2.5.5",
+  "matplotlib": "3.10.9",
+  "matplotlib-inline": "0.2.2",
+  "mcp": "2.2.0",
+  "mcp-types": "2.2.0",
+  "mdurl": "0.1.2",
+  "mediapy": "1.2.6",
+  "mergedeep": "1.3.4",
+  "miniaudio": "1.71",
+  "minicpmo-utils": "1.0.6",
+  "mistral_common": "1.11.6",
+  "mistune": "3.3.4",
+  "mkdocs": "1.6.1",
+  "mkdocs-api-autonav": "0.4.0",
+  "mkdocs-autorefs": "1.4.4",
+  "mkdocs-awesome-nav": "3.3.0",
+  "mkdocs-gen-files": "0.6.1",
+  "mkdocs-get-deps": "0.2.2",
+  "mkdocs-git-revision-date-localized-plugin": "1.5.3",
+  "mkdocs-glightbox": "0.5.2",
+  "mkdocs-material": "9.7.6",
+  "mkdocs-material-extensions": "1.3.1",
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diff --git a/evidence/minicpmo45-l20x-20261021/results/baseline-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/baseline-quality.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/baseline-table.json b/evidence/minicpmo45-l20x-20261021/results/baseline-table.json
new file mode 100644
index 000000000..533f7cf6a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/baseline-table.json
@@ -0,0 +1,210 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "scope": "Completed steady-state baseline measurements; no optimization verdict",
+  "rows": [
+    {
+      "engine": "vllm",
+      "concurrency": 1,
+      "requests_per_repeat": 320,
+      "repeats": 3,
+      "n_failed": 0,
+      "throughput_frames_s_mean": 192.6309728972112,
+      "throughput_frames_s_runs": [
+        191.46859704374864,
+        194.38639468569238,
+        192.03792696219256
+      ],
+      "ttfa_p50_ms_pooled": 307.4587588198483,
+      "ttfa_p95_ms_pooled": 343.0558750871569,
+      "rtf_mean": 0.13163823357797064,
+      "mean_audio_seconds": 4.403375
+    },
+    {
+      "engine": "vllm",
+      "concurrency": 2,
+      "requests_per_repeat": 320,
+      "repeats": 3,
+      "n_failed": 0,
+      "throughput_frames_s_mean": 295.48597389019307,
+      "throughput_frames_s_runs": [
+        295.3212311165908,
+        293.17643702367513,
+        297.9602535303133
+      ],
+      "ttfa_p50_ms_pooled": 410.91528814285994,
+      "ttfa_p95_ms_pooled": 534.6035631839186,
+      "rtf_mean": 0.1720971816832971,
+      "mean_audio_seconds": 4.401875
+    },
+    {
+      "engine": "vllm",
+      "concurrency": 4,
+      "requests_per_repeat": 320,
+      "repeats": 3,
+      "n_failed": 0,
+      "throughput_frames_s_mean": 394.0476581440165,
+      "throughput_frames_s_runs": [
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+      "ttfa_p50_ms_pooled": 881.6496999934316,
+      "ttfa_p95_ms_pooled": 1000.247368076816,
+      "rtf_mean": 0.2666428173622068,
+      "mean_audio_seconds": 4.421
+    },
+    {
+      "engine": "vllm",
+      "concurrency": 8,
+      "requests_per_repeat": 320,
+      "repeats": 3,
+      "n_failed": 0,
+      "throughput_frames_s_mean": 488.4001363373871,
+      "throughput_frames_s_runs": [
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+      "ttfa_p50_ms_pooled": 1375.2594594843686,
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+      "rtf_mean": 0.42630675701070436,
+      "mean_audio_seconds": 4.416125
+    },
+    {
+      "engine": "vllm",
+      "concurrency": 16,
+      "requests_per_repeat": 320,
+      "repeats": 3,
+      "n_failed": 0,
+      "throughput_frames_s_mean": 513.2861988294537,
+      "throughput_frames_s_runs": [
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+        519.9674080424297
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+      "ttfa_p50_ms_pooled": 1702.651811297983,
+      "ttfa_p95_ms_pooled": 2727.534947451204,
+      "rtf_mean": 0.7967777842709449,
+      "mean_audio_seconds": 4.425833333333333
+    },
+    {
+      "engine": "vllm",
+      "concurrency": 32,
+      "requests_per_repeat": 320,
+      "repeats": 3,
+      "n_failed": 0,
+      "throughput_frames_s_mean": 540.2205300552778,
+      "throughput_frames_s_runs": [
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+      "throughput_frames_s_mean": 291.33565256989596,
+      "throughput_frames_s_runs": [
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+        294.1806012591891,
+        293.13115243655807
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+      "ttfa_p50_ms_pooled": 371.0423116572201,
+      "ttfa_p95_ms_pooled": 461.8933257646858,
+      "rtf_mean": 0.0888416606367711,
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+    },
+    {
+      "engine": "sglang",
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+      "throughput_frames_s_mean": 476.64068307533654,
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+      "throughput_frames_s_mean": 713.7879426625113,
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+      "ttfa_p50_ms_pooled": 835.1065027527511,
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+      "rtf_mean": 0.1980206295767324,
+      "mean_audio_seconds": 4.344666666666667
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+    {
+      "engine": "sglang",
+      "concurrency": 16,
+      "requests_per_repeat": 320,
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+      "ttfa_p50_ms_pooled": 1111.986730247736,
+      "ttfa_p95_ms_pooled": 1411.4549641031772,
+      "rtf_mean": 0.2638718498759094,
+      "mean_audio_seconds": 4.3460833333333335
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+    {
+      "engine": "sglang",
+      "concurrency": 32,
+      "requests_per_repeat": 320,
+      "repeats": 3,
+      "n_failed": 0,
+      "throughput_frames_s_mean": 1918.4671911997168,
+      "throughput_frames_s_runs": [
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+      "ttfa_p50_ms_pooled": 1763.5161047801375,
+      "ttfa_p95_ms_pooled": 2479.3635668233037,
+      "rtf_mean": 0.4245844838355303,
+      "mean_audio_seconds": 4.335666666666667
+    }
+  ]
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/environment-attempts.json b/evidence/minicpmo45-l20x-20261021/results/environment-attempts.json
new file mode 100644
index 000000000..ffd9c2e04
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/environment-attempts.json
@@ -0,0 +1,35 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "attempts": [
+    {
+      "framework": "vllm_omni",
+      "status": "cancelled",
+      "reason": "Original editable finder could import missing modules from another checkout; replaced with an isolated entry environment."
+    },
+    {
+      "framework": "vllm_omni",
+      "status": "failed",
+      "reason": "Transformers 5.16.1 required tokenizers>=0.23.1; dependency installation completed before retry."
+    },
+    {
+      "framework": "sglang_omni",
+      "status": "failed",
+      "reason": "Dependency resolution required prerelease support for pinned cuda-tile; resolution succeeded with prerelease=allow."
+    },
+    {
+      "framework": "sglang_omni",
+      "status": "failed",
+      "reason": "Default shared IPC directory was not writable; retry uses a task-owned IPC directory."
+    },
+    {
+      "framework": "sglang_omni",
+      "status": "failed",
+      "reason": "Thinker and Talker initialization conflicted on default distributed TCP port 29500; retry explicitly configures distinct loopback rendezvous ports."
+    },
+    {
+      "framework": "quality_harness",
+      "status": "failed_then_corrected",
+      "reason": "The reference save_run writes summary before WAV files. The asynchronous scoring watcher observed the summary too early and failed opening one WAV. Wait for the next run summary, which implies the previous save_run completed, before scoring run1. No service failure or changed output was inferred."
+    }
+  ]
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/excluded-local-checkpoint-scan.json b/evidence/minicpmo45-l20x-20261021/results/excluded-local-checkpoint-scan.json
new file mode 100644
index 000000000..1befeffbf
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/excluded-local-checkpoint-scan.json
@@ -0,0 +1,43 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "excluded_from_baseline": true,
+  "reason": "Model config and two model Python files did not match pinned official revision. Weights matched; official metadata replacement required a new cohort.",
+  "measurements": [
+    {
+      "concurrency": 1,
+      "n_requests": 64,
+      "n_failed": 0,
+      "throughput_frames_s": 192.99414181262983,
+      "ttfa_p50_s": 0.3030988499522209,
+      "ttfa_p95_s": 0.3350931538734585,
+      "rtf_mean": 0.13142912169653032
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+    {
+      "concurrency": 2,
+      "n_requests": 64,
+      "n_failed": 0,
+      "throughput_frames_s": 306.1663253559082,
+      "ttfa_p50_s": 0.3919649701565504,
+      "ttfa_p95_s": 0.5106137109454721,
+      "rtf_mean": 0.1656832240376756
+    },
+    {
+      "concurrency": 4,
+      "n_requests": 64,
+      "n_failed": 0,
+      "throughput_frames_s": 390.4676265367766,
+      "ttfa_p50_s": 0.8487142664380372,
+      "ttfa_p95_s": 0.9391858957242221,
+      "rtf_mean": 0.2690079858724289
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+    {
+      "concurrency": 8,
+      "n_requests": 64,
+      "n_failed": 0,
+      "throughput_frames_s": 473.62191003975323,
+      "ttfa_p50_s": 1.2351192804053426,
+      "ttfa_p95_s": 1.5106232981197536,
+      "rtf_mean": 0.4311442916392455
+    }
+  ]
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/mrv2-host-profile.json b/evidence/minicpmo45-l20x-20261021/results/mrv2-host-profile.json
new file mode 100644
index 000000000..41b58b833
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/mrv2-host-profile.json
@@ -0,0 +1,13 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "samples": 1535,
+  "inclusive_stack_samples": {
+    "_decode_cfm": 12,
+    "setup_batch": 86,
+    "decode_batch": 1198,
+    "prepare_prompt": 1109,
+    "_encode_chunk": 131,
+    "_forward_spk_embedding": 886
+  },
+  "limitation": "py-spy fell behind its 100 Hz target by up to 46 seconds and severely perturbed service. These are qualitative stacks, not time attribution; profiled requests excluded from performance results."
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/resource-snapshot.json b/evidence/minicpmo45-l20x-20261021/results/resource-snapshot.json
new file mode 100644
index 000000000..647a46e4c
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/resource-snapshot.json
@@ -0,0 +1,33 @@
+{
+  "qualification": "Single snapshot, not peak VRAM; startup and shared-host workload may overlap.",
+  "roles": [
+    {
+      "role": "quality_asr",
+      "gpu": "NVIDIA L20X",
+      "used_memory_mib": 52377,
+      "total_memory_mib": 143771,
+      "utilization_percent": 0
+    },
+    {
+      "role": "speaker_microbatch_candidate",
+      "gpu": "NVIDIA L20X",
+      "used_memory_mib": 71229,
+      "total_memory_mib": 143771,
+      "utilization_percent": 0
+    },
+    {
+      "role": "speaker_candidate",
+      "gpu": "NVIDIA L20X",
+      "used_memory_mib": 99906,
+      "total_memory_mib": 143771,
+      "utilization_percent": 67
+    },
+    {
+      "role": "speaker_mrv2_candidate",
+      "gpu": "NVIDIA L20X",
+      "used_memory_mib": 65587,
+      "total_memory_mib": 143771,
+      "utilization_percent": 0
+    }
+  ]
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/sglang-exploratory.json.gz b/evidence/minicpmo45-l20x-20261021/results/sglang-exploratory.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/sglang-main-repeated.json.gz b/evidence/minicpmo45-l20x-20261021/results/sglang-main-repeated.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-candidate-micro.json b/evidence/minicpmo45-l20x-20261021/results/speaker-candidate-micro.json
new file mode 100644
index 000000000..6b4f2c410
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-candidate-micro.json
@@ -0,0 +1,327 @@
+{
+  "verdict": "PASS",
+  "scope": "isolated speaker embedding only",
+  "backend": "trt",
+  "cpu_reference": true,
+  "asset_sha256": "a6ac6a63997761ae2997373e2ee1c47040854b4b759ea41ec48e4e42df0f4d73",
+  "quality": [
+    {
+      "id": "common_voice_en_19254683-common_voice_en_19254687",
+      "frames": 598,
+      "input_sha256": "66d28e062a17fa3a052b0e100f0a01d22f1a76897e6cb17ff7ed1ea904a11ee5",
+      "cosine": 1.0,
+      "max_normalized_abs_error": 8.530914783477783e-07
+    },
+    {
+      "id": "common_voice_en_19967495-common_voice_en_19967497",
+      "frames": 598,
+      "input_sha256": "75e01d5f80f4b341ee5fb8f91dcfd9e6415637d923789356219d4b1f688183d2",
+      "cosine": 1.0,
+      "max_normalized_abs_error": 3.5762786865234375e-07
+    },
+    {
+      "id": "common_voice_en_21555942-common_voice_en_21555950",
+      "frames": 598,
+      "input_sha256": "ff3cf3d8dbbb0f35fcdbee7c88c3d3e7370af0fea3a9d4075f006ff81cb85726",
+      "cosine": 1.0,
+      "max_normalized_abs_error": 3.501772880554199e-07
+    },
+    {
+      "id": "common_voice_en_125386-common_voice_en_125388",
+      "frames": 598,
+      "input_sha256": "5c274a334bdc38dee252ee12cbf8521863a1c4c04c2e1101f9d2976a776ed762",
+      "cosine": 1.0,
+      "max_normalized_abs_error": 4.470348358154297e-07
+    },
+    {
+      "id": "common_voice_en_20236234-common_voice_en_20236233",
+      "frames": 598,
+      "input_sha256": "81b509425418da0bcbbededcbb6793b75b94ec0e9bb5942d25025672c778754e",
+      "cosine": 1.0,
+      "max_normalized_abs_error": 3.129243850708008e-07
+    },
+    {
+      "id": "common_voice_en_32144882-common_voice_en_32144886",
+      "frames": 598,
+      "input_sha256": "448b86c2f9fb16ec950c5975e253652c04a1c9d28691680090df548e554a41fc",
+      "cosine": 1.0000001192092896,
+      "max_normalized_abs_error": 4.842877388000488e-07
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+    {
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+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-torch-ieee-micro.json b/evidence/minicpmo45-l20x-20261021/results/speaker-torch-ieee-micro.json
new file mode 100644
index 000000000..bf416c730
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-torch-ieee-micro.json
@@ -0,0 +1,326 @@
+{
+  "verdict": "FAIL",
+  "scope": "isolated speaker embedding only",
+  "backend": "torch",
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+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-torch-micro.json b/evidence/minicpmo45-l20x-20261021/results/speaker-torch-micro.json
new file mode 100644
index 000000000..5e0d6c8d7
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-torch-micro.json
@@ -0,0 +1,326 @@
+{
+  "verdict": "FAIL",
+  "scope": "isolated speaker embedding only",
+  "backend": "torch",
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+    "torch": "2.13.0+cu130",
+    "cuda": "13.0",
+    "cudnn_allow_tf32": true,
+    "matmul_allow_tf32": false
+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-trt-ieee-micro.json b/evidence/minicpmo45-l20x-20261021/results/speaker-trt-ieee-micro.json
new file mode 100644
index 000000000..9fb20292d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-trt-ieee-micro.json
@@ -0,0 +1,326 @@
+{
+  "verdict": "FAIL",
+  "scope": "isolated speaker embedding only",
+  "backend": "trt",
+  "asset_sha256": "a6ac6a63997761ae2997373e2ee1c47040854b4b759ea41ec48e4e42df0f4d73",
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+    {
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+      "id": "common_voice_en_20236234-common_voice_en_20236233",
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+    {
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+  "settings": {
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+    "cuda": "13.0",
+    "cudnn_allow_tf32": false,
+    "matmul_allow_tf32": false
+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-trt-micro.json b/evidence/minicpmo45-l20x-20261021/results/speaker-trt-micro.json
new file mode 100644
index 000000000..4f5c4b94f
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-trt-micro.json
@@ -0,0 +1,326 @@
+{
+  "verdict": "FAIL",
+  "scope": "isolated speaker embedding only",
+  "backend": "trt",
+  "asset_sha256": "a6ac6a63997761ae2997373e2ee1c47040854b4b759ea41ec48e4e42df0f4d73",
+  "quality": [
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+    {
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+    {
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+    {
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+    {
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+    {
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+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-trt-ort-compatible-micro.json b/evidence/minicpmo45-l20x-20261021/results/speaker-trt-ort-compatible-micro.json
new file mode 100644
index 000000000..049d5b35e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-trt-ort-compatible-micro.json
@@ -0,0 +1,326 @@
+{
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+  "settings": {
+    "torch": "2.13.0+cu130",
+    "cuda": "13.0",
+    "cudnn_allow_tf32": true,
+    "matmul_allow_tf32": false
+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/stage-attribution.json b/evidence/minicpmo45-l20x-20261021/results/stage-attribution.json
new file mode 100644
index 000000000..a248dd125
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/stage-attribution.json
@@ -0,0 +1,49 @@
+{
+  "status": "INCONCLUSIVE",
+  "kind": "request stage timings, not isolated GPU compute",
+  "measurements": {
+    "c1-stages": {
+      "requests": 32,
+      "mean": {
+        "thinker_ttft_ms": 24.557024240493774,
+        "thinker_gen_ms": 87.18335628509521,
+        "thinker_tpot_ms": 4.97801710313736,
+        "talker_first_output_ms": 137.7464383840561,
+        "talker_gen_ms": 446.16246223449707,
+        "code2wav_first_output_ms": 302.55284617024085,
+        "code2wav_gen_ms": 572.2757847078385,
+        "audio_s": 4.516129032258064,
+        "client_ttfa_s": 0.30634270794689655
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+    },
+    "c16-stages": {
+      "requests": 64,
+      "mean": {
+        "thinker_ttft_ms": 54.34560030698776,
+        "thinker_gen_ms": 178.88439819216728,
+        "thinker_tpot_ms": 10.912456663326425,
+        "talker_first_output_ms": 362.1317632496357,
+        "talker_gen_ms": 892.5475589931011,
+        "code2wav_first_output_ms": 1787.1193774044514,
+        "code2wav_gen_ms": 3271.9841934740543,
+        "audio_s": 4.3862499999999995,
+        "client_ttfa_s": 1.8096598004049156
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+    },
+    "c32-stages": {
+      "requests": 128,
+      "mean": {
+        "thinker_ttft_ms": 80.07399551570415,
+        "thinker_gen_ms": 222.38353826105595,
+        "thinker_tpot_ms": 12.61050885427539,
+        "talker_first_output_ms": 559.0925421565771,
+        "talker_gen_ms": 1080.1075510680676,
+        "code2wav_first_output_ms": 3129.139143973589,
+        "code2wav_gen_ms": 6300.101432949305,
+        "audio_s": 4.38125,
+        "client_ttfa_s": 3.156374828031403
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+    }
+  },
+  "interpretation": "C16 Code2Wav first output is much later than Talker first output; test whether MPS overlap reduces stage interference. Setup/encoder attribution requires kernel-level evidence."
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/status.json b/evidence/minicpmo45-l20x-20261021/results/status.json
new file mode 100644
index 000000000..546be683d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/status.json
@@ -0,0 +1,20 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "baseline": "Completed two engines at six concurrency levels, three measured 320-request repeats each; zero failed measured requests.",
+  "candidate_revision": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
+  "candidate_microbench": "PASS within frozen embedding gate; CPU-compatible FP32 TensorRT",
+  "candidate_unit_tests": {
+    "passed": 60,
+    "warnings": 16
+  },
+  "optimization_submitted": false,
+  "pending": [
+    "candidate repeated benchmark",
+    "candidate speech quality",
+    "fresh-start high-concurrency confirmation",
+    "combined-control selection"
+  ],
+  "candidate_pull_request": "https://github.com/vllm-project/vllm-omni/pull/9188",
+  "candidate_cpu_tests_passed": 67,
+  "candidate_tuning": "C16/C32 gains observed; held-out repeated service and generated speech quality pending"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/tuning-table.json b/evidence/minicpmo45-l20x-20261021/results/tuning-table.json
new file mode 100644
index 000000000..313e7b6fe
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/tuning-table.json
@@ -0,0 +1,1422 @@
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-encoder-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-encoder-tuning.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-main-repeated.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-main-repeated.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-main-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-main-tuning.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-microbatch-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-microbatch-tuning.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-mps-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-mps-tuning.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-mrv2-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-mrv2-tuning.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-tuning.json.gz
new file mode 100644
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literal 0
HcmV?d00001

diff --git a/evidence/minicpmo45-l20x-20261021/validator/.gitkeep b/evidence/minicpmo45-l20x-20261021/validator/.gitkeep
new file mode 100644
index 000000000..e69de29bb
diff --git a/evidence/minicpmo45-l20x-20261021/validator/bench_speaker.py b/evidence/minicpmo45-l20x-20261021/validator/bench_speaker.py
new file mode 100644
index 000000000..8d81879b6
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/bench_speaker.py
@@ -0,0 +1,52 @@
+"""Isolated CAM++ parity and synchronized latency; not a service benchmark."""
+import argparse,hashlib,json,time,statistics
+from pathlib import Path
+import numpy as np
+import soundfile as sf
+import torch
+import torch.nn.functional as F
+import onnxruntime as ort
+from bench.workload import load_seed_tts_rows,make_id_sets
+from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_code2wav import _normalize_reference
+from vllm_omni.model_executor.models.step_audio2.step_audio2_token2wav import AudioResampler,kaldi
+p=argparse.ArgumentParser();p.add_argument('--model',required=True);p.add_argument('--out',required=True);p.add_argument('--backend',choices=['torch','trt'],required=True);p.add_argument('--ieee',action='store_true');p.add_argument('--gpu-onnx');p.add_argument('--cpu-reference',action='store_true');a=p.parse_args()
+if a.ieee:
+ torch.backends.cuda.matmul.allow_tf32=False
+ torch.backends.cudnn.allow_tf32=False
+asset=Path(a.model)/'assets/token2wav/campplus.onnx'
+options=ort.SessionOptions();options.intra_op_num_threads=1;options.graph_optimization_level=ort.GraphOptimizationLevel.ORT_ENABLE_ALL
+cpu=ort.InferenceSession(str(asset),sess_options=options,providers=['CPUExecutionProvider'])
+if a.backend=='trt':
+ if a.ieee:
+  from speaker_trt_ieee import get_campplus_trt
+ else:
+  from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_trt import get_campplus_trt
+ gpu=get_campplus_trt(a.gpu_onnx or str(asset),device='cuda:0',**({'cpu_reference':True} if a.cpu_reference else {}))
+else:
+ from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import get_campplus_torch
+ gpu=get_campplus_torch(str(asset),device='cuda:0')
+rows=load_seed_tts_rows();ids=make_id_sets(rows).tuning_pool[:32];byid={r.row_id:r for r in rows};feats=[]
+for i in ids:
+ audio,sr=sf.read(byid[i].ref_wav_path,dtype='float32',always_2d=True)
+ norm,sr=_normalize_reference(audio.T,sr)
+ audio16=AudioResampler(target_sr=16000).resample(norm.numpy(),orig_sr=sr)
+ feat=kaldi.fbank(torch.from_numpy(audio16).unsqueeze(0),num_mel_bins=80,dither=0,sample_frequency=16000)
+ feat-=feat.mean(0,keepdim=True);feats.append((i,feat))
+feats.extend([(ids[0]+'-short97',feats[0][1][:97]),(ids[0]+'-short200',feats[0][1][:200])])
+def run_cpu(feat):return torch.from_numpy(cpu.run(None,{cpu.get_inputs()[0].name:feat.unsqueeze(0).numpy()})[0])
+quality=[]
+with torch.inference_mode():
+ for i,f in feats:
+  ref=F.normalize(run_cpu(f),dim=-1);out=F.normalize(gpu(f).float().cpu(),dim=-1)
+  quality.append({'id':i,'frames':len(f),'input_sha256':hashlib.sha256(f.numpy().tobytes()).hexdigest(),'cosine':float(F.cosine_similarity(ref,out).item()),'max_normalized_abs_error':float((ref-out).abs().max())})
+ timings={}
+ for label,fn in [('cpu_onnx',run_cpu),(a.backend,gpu)]:
+  f=feats[0][1]
+  for _ in range(10):fn(f)
+  torch.cuda.synchronize();samples=[]
+  for _ in range(30):
+   torch.cuda.synchronize();t=time.perf_counter();fn(f);torch.cuda.synchronize();samples.append((time.perf_counter()-t)*1000)
+  timings[label]={'mean_ms':statistics.mean(samples),'median_ms':statistics.median(samples),'samples_ms':samples}
+passed=all(q['cosine']>=0.99999 and q['max_normalized_abs_error']<=0.001 for q in quality)
+doc={'verdict':'PASS' if passed else 'FAIL','scope':'isolated speaker embedding only','backend':a.backend,'cpu_reference':a.cpu_reference,'asset_sha256':hashlib.sha256(asset.read_bytes()).hexdigest(),'quality':quality,'latency':timings,'settings':{'torch':torch.__version__,'cuda':torch.version.cuda,'cudnn_allow_tf32':torch.backends.cudnn.allow_tf32,'matmul_allow_tf32':torch.backends.cuda.matmul.allow_tf32}}
+Path(a.out).write_text(json.dumps(doc,indent=2));print(json.dumps({'verdict':doc['verdict'],'latency':{k:v['median_ms'] for k,v in timings.items()},'min_cosine':min(x['cosine'] for x in quality),'max_error':max(x['max_normalized_abs_error'] for x in quality)}),flush=True)
diff --git a/evidence/minicpmo45-l20x-20261021/validator/benchmark-sources.json b/evidence/minicpmo45-l20x-20261021/validator/benchmark-sources.json
new file mode 100644
index 000000000..aa5101dce
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/benchmark-sources.json
@@ -0,0 +1,20 @@
+{
+  "repository": "https://github.com/InferMatrixLab/minicpm-o-4.5-single-gpu-engine",
+  "revision": "a4f4778f312791c2d190b48e521141887ed160c8",
+  "hashes": {
+    "bench/metrics.py": "ef40121126464c9b120bd37710b145895a0a784a4caab5319d3f535b64ab35a0",
+    "bench/protocol.py": "c739883456a14c0717121af1c1d7e6fd0ec6601f9a657c1d0d577a27f23dab74",
+    "bench/workload.py": "d3be4052477311dec3165c7a9db3d5f7cb93396768d8864d65646610a40283c7",
+    "bench/adapters/vllm_omni.py": "c9c13147e482e984fb2757f0c5a572c60ec17d383f4ee710cb9865414b642d12",
+    "bench/adapters/sglang_omni.py": "dcda6bf0b67c75d68daeae275fd4ce55b8a594136afb2f176b93ce6dec809305",
+    "exploratory_driver_sha256": "457be625304659741dcb9a6b19ee0d02f674ac36ac2e51c0c7aad9b36ad96d73"
+  },
+  "unit_tests": {
+    "passed": 30,
+    "skipped": 1,
+    "paths": [
+      "tests/bench/test_metrics.py",
+      "tests/bench/test_protocol_manifest.py"
+    ]
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/driver-revisions.json b/evidence/minicpmo45-l20x-20261021/validator/driver-revisions.json
new file mode 100644
index 000000000..3d17a2631
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/driver-revisions.json
@@ -0,0 +1,28 @@
+{
+  "v1": {
+    "file": "run_baseline_v1.py",
+    "sha256": "457be625304659741dcb9a6b19ee0d02f674ac36ac2e51c0c7aad9b36ad96d73",
+    "used_for": [
+      "vllm-official-exploratory",
+      "sglang-official-exploratory",
+      "vllm-official-repeated",
+      "sglang-official-repeated"
+    ]
+  },
+  "v2": {
+    "file": "run_baseline.py",
+    "sha256": "0c66908c5959e3b91e5a091af5cf2a6382443c3ba0c416d6917e7af3aef3222b",
+    "change": "Add explicit disjoint tuning-pool selection; evaluation behavior unchanged. Candidate screening uses tuning rows before held-out evaluation.",
+    "used_for": [
+      "vllm-main-tuning",
+      "vllm-mps-tuning",
+      "vllm-mrv2-tuning",
+      "vllm-encoder-tuning",
+      "vllm-microbatch-tuning",
+      "vllm-speaker-tuning",
+      "vllm-speaker-repeated",
+      "vllm-speaker-microbatch-tuning",
+      "vllm-speaker-mrv2-tuning"
+    ]
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/export_metrics.py b/evidence/minicpmo45-l20x-20261021/validator/export_metrics.py
new file mode 100644
index 000000000..2f9caf5a6
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/export_metrics.py
@@ -0,0 +1,29 @@
+"""Export finite metrics and artifact hashes without local paths or raw audio."""
+import argparse,gzip,hashlib,json,math
+from pathlib import Path
+p=argparse.ArgumentParser();p.add_argument('input',type=Path);p.add_argument('output',type=Path);a=p.parse_args()
+def clean(x):
+ if isinstance(x,float) and not math.isfinite(x):return None
+ if isinstance(x,dict):return {k:clean(v) for k,v in x.items()}
+ if isinstance(x,list):return [clean(v) for v in x]
+ return x
+cells=[]
+for d in sorted(a.input.glob('c*/run*')):
+ if not (d/'summary.json').exists():continue
+ summary=json.loads((d/'summary.json').read_text())
+ records=[json.loads(x) for x in (d/'requests.jsonl').read_text().splitlines()]
+ # Monotonic absolute clock values have no cross-host meaning.
+ for r in records:
+  for k in ('t_dispatch','t_complete'):r.pop(k,None)
+ files={p.name:hashlib.sha256(p.read_bytes()).hexdigest() for p in d.glob('*') if p.is_file()}
+ wavs={p.name:hashlib.sha256(p.read_bytes()).hexdigest() for p in (d/'wav').glob('*.wav')}
+ cells.append({'cell':str(d.relative_to(a.input)),'summary':summary,'requests':records,'artifact_hashes':files,'wav_hashes':wavs})
+a.output.parent.mkdir(parents=True,exist_ok=True)
+plan=json.loads((a.input/'plan.json').read_text())
+source_plan={k:plan[k] for k in ('adapter','concurrency','requests','repeats','id_set','cache_policy','qualification','ids') if k in plan}
+source_plan.setdefault('id_set','eval')
+payload=json.dumps(clean({'qualification':'exploratory repeated steady state; no restart between cells','source_plan':source_plan,'metadata_notes':'Summary fields such as id_set, revision and GPU retain reference-helper defaults. The source_plan and campaign manifests are authoritative; tuning selection is not inferred from summary.id_set.','cells':cells}),indent=2,allow_nan=False)+'\n'
+if a.output.suffix == '.gz':
+ a.output.write_bytes(gzip.compress(payload.encode(),mtime=0))
+else:
+ a.output.write_text(payload)
diff --git a/evidence/minicpmo45-l20x-20261021/validator/graph-tests.json b/evidence/minicpmo45-l20x-20261021/validator/graph-tests.json
new file mode 100644
index 000000000..17c51b973
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/graph-tests.json
@@ -0,0 +1,14 @@
+{
+  "source": "vllm-omni baseline main pinned in plan/baseline-plan.json",
+  "tests": [
+    "tests/model_executor/models/minicpmo_4_5/test_flow_encoder_graph.py",
+    "tests/model_executor/models/minicpmo_4_5/test_code2wav_batching.py"
+  ],
+  "device": "NVIDIA L20X",
+  "passed": 170,
+  "skipped": 1,
+  "warnings": 16,
+  "elapsed_seconds": 39.62,
+  "scope": "Existing CPU and GPU exact-shape graph replay, state ownership and Code2Wav batching. Not a service quality verdict.",
+  "log_sha256": "0d9932308d994475c4f1f0e1419fb07232108c15cc45ae3479402da6e8caaf4a"
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json b/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
new file mode 100644
index 000000000..c4327c86a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
@@ -0,0 +1,14 @@
+{
+  "full_pytest": {
+    "exit_code": 0,
+    "collected": 266
+  },
+  "ruff_src_tests": "PASS",
+  "generated_catalog_check": "PASS",
+  "scope": "scaffold and knowledge delivery only; does not establish campaign performance",
+  "installed_wheel": {
+    "peer_cuda_search": "PASS",
+    "owner_local_case_resource": "PASS",
+    "note": "CLI resource returns a path; resolved content was read and checked from the installed wheel."
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/run_baseline.py b/evidence/minicpmo45-l20x-20261021/validator/run_baseline.py
new file mode 100644
index 000000000..982f1cba3
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/run_baseline.py
@@ -0,0 +1,49 @@
+import argparse
+import asyncio
+import json
+from pathlib import Path
+from bench.adapters import get_adapter
+from bench.client import make_session
+from bench.protocol import closed_loop, evaluate_run, save_run
+from bench.workload import load_seed_tts_rows, make_id_sets, canonical_requests
+
+async def main():
+    p = argparse.ArgumentParser()
+    p.add_argument('--adapter', required=True)
+    p.add_argument('--url', required=True)
+    p.add_argument('--out', required=True)
+    p.add_argument('--concurrency', type=int, nargs='+', default=[1,2,4,8,16,32])
+    p.add_argument('--requests', type=int, default=320)
+    p.add_argument('--repeats', type=int, default=3)
+    p.add_argument('--id-set', choices=['eval', 'tuning'], default='eval')
+    a = p.parse_args()
+    out = Path(a.out)
+    out.mkdir(parents=True, exist_ok=True)
+    rows = load_seed_tts_rows()
+    sets = make_id_sets(rows)
+    adapter = get_adapter(a.adapter)
+    # Exploratory steady-state baseline. No restart between cells; explicitly
+    # distinct from the reference campaign's fresh-server certification.
+    plan = vars(a) | {'cache_policy':'none', 'qualification':'exploratory', 'ids':sets.to_json()}
+    (out/'plan.json').write_text(json.dumps(plan, indent=2))
+    async with make_session() as session:
+        for c in a.concurrency:
+            warm = canonical_requests(rows, sets.warmup(c))
+            traces = await closed_loop(session,a.url,adapter,warm,c,timeout_s=180)
+            result = evaluate_run('warmup',c,traces,measured=False)
+            save_run(result,out/f'c{c}'/'warmup')
+            if any(not r.ok for r in result.per_request):
+                raise RuntimeError(f'C{c} warmup failed; inspect saved traces')
+            pool = sets.eval_pool if a.id_set == 'eval' else sets.tuning_pool
+            if a.requests > len(pool):
+                raise ValueError('Requested count exceeds the selected disjoint pool')
+            reqs=canonical_requests(rows, list(pool[:a.requests]))
+            for k in range(a.repeats+1):
+                traces=await closed_loop(session,a.url,adapter,reqs,c,timeout_s=180,record_raw=True)
+                result=evaluate_run(f'run{k}',c,traces,measured=k>0)
+                save_run(result,out/f'c{c}'/f'run{k}')
+                print(json.dumps(result.summary()),flush=True)
+                if any(not r.ok for r in result.per_request):
+                    raise RuntimeError(f'C{c} run{k} failed; inspect saved traces')
+
+asyncio.run(main())
diff --git a/evidence/minicpmo45-l20x-20261021/validator/run_baseline_v1.py b/evidence/minicpmo45-l20x-20261021/validator/run_baseline_v1.py
new file mode 100644
index 000000000..4910f0979
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/run_baseline_v1.py
@@ -0,0 +1,45 @@
+import argparse
+import asyncio
+import json
+from pathlib import Path
+from bench.adapters import get_adapter
+from bench.client import make_session
+from bench.protocol import closed_loop, evaluate_run, save_run
+from bench.workload import load_seed_tts_rows, make_id_sets, canonical_requests
+
+async def main():
+    p = argparse.ArgumentParser()
+    p.add_argument('--adapter', required=True)
+    p.add_argument('--url', required=True)
+    p.add_argument('--out', required=True)
+    p.add_argument('--concurrency', type=int, nargs='+', default=[1,2,4,8,16,32])
+    p.add_argument('--requests', type=int, default=320)
+    p.add_argument('--repeats', type=int, default=3)
+    a = p.parse_args()
+    out = Path(a.out)
+    out.mkdir(parents=True, exist_ok=True)
+    rows = load_seed_tts_rows()
+    sets = make_id_sets(rows)
+    adapter = get_adapter(a.adapter)
+    # Exploratory steady-state baseline. No restart between cells; explicitly
+    # distinct from the reference campaign's fresh-server certification.
+    plan = vars(a) | {'cache_policy':'none', 'qualification':'exploratory', 'ids':sets.to_json()}
+    (out/'plan.json').write_text(json.dumps(plan, indent=2))
+    async with make_session() as session:
+        for c in a.concurrency:
+            warm = canonical_requests(rows, sets.warmup(c))
+            traces = await closed_loop(session,a.url,adapter,warm,c,timeout_s=180)
+            result = evaluate_run('warmup',c,traces,measured=False)
+            save_run(result,out/f'c{c}'/'warmup')
+            if any(not r.ok for r in result.per_request):
+                raise RuntimeError(f'C{c} warmup failed; inspect saved traces')
+            reqs=canonical_requests(rows, list(sets.eval_pool[:a.requests]))
+            for k in range(a.repeats+1):
+                traces=await closed_loop(session,a.url,adapter,reqs,c,timeout_s=180,record_raw=True)
+                result=evaluate_run(f'run{k}',c,traces,measured=k>0)
+                save_run(result,out/f'c{c}'/f'run{k}')
+                print(json.dumps(result.summary()),flush=True)
+                if any(not r.ok for r in result.per_request):
+                    raise RuntimeError(f'C{c} run{k} failed; inspect saved traces')
+
+asyncio.run(main())
diff --git a/evidence/minicpmo45-l20x-20261021/validator/score_outputs.py b/evidence/minicpmo45-l20x-20261021/validator/score_outputs.py
new file mode 100644
index 000000000..e55d09992
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/score_outputs.py
@@ -0,0 +1,71 @@
+"""Score saved benchmark WAVs with the pinned SGLang-Omni native scorers."""
+import argparse
+import concurrent.futures
+import hashlib
+import json
+from pathlib import Path
+import numpy as np
+import soundfile as sf
+from bench.workload import load_seed_tts_rows
+from benchmarks.tasks.asr import load_qwen3_asr, transcribe, apply_wer
+from benchmarks.metrics.wer import SampleOutput
+
+p=argparse.ArgumentParser()
+p.add_argument('--run', required=True)
+p.add_argument('--out', required=True)
+p.add_argument('--scorers', required=True)
+p.add_argument('--asr-port',type=int,default=29181)
+p.add_argument('--device',default='cuda:0')
+p.add_argument('--tasks',nargs='+',default=['wer','sim','utmos'])
+a=p.parse_args()
+rows={r.row_id:r for r in load_seed_tts_rows()}
+metrics=[json.loads(x) for x in (Path(a.run)/'requests.jsonl').read_text().splitlines()]
+assert metrics and all(x['ok'] for x in metrics)
+ids=sorted(x['request_id'] for x in metrics)
+assert len(ids)==len(set(ids))
+wavs=[str(Path(a.run)/'wav'/f'{i}.wav') for i in ids]
+out=Path(a.out);out.parent.mkdir(parents=True,exist_ok=True)
+doc=json.loads(out.read_text()) if out.exists() else {'rows':{},'tasks':[]}
+for i,w in zip(ids,wavs):
+ audio,sr=sf.read(w)
+ assert len(audio)>0 and np.isfinite(audio).all()
+ doc['rows'].setdefault(i,{}).update({'wav_sha256':hashlib.sha256(Path(w).read_bytes()).hexdigest(),'duration_s':len(audio)/sr})
+def save():
+ out.write_text(json.dumps(doc,indent=2,allow_nan=False))
+save()
+if 'wer' in a.tasks and 'wer' not in doc['tasks']:
+ asr=load_qwen3_asr(a.asr_port)
+ def score(pair):
+  i,w=pair
+  hyp=transcribe(asr,w,'en',a.device)
+  r=apply_wer(SampleOutput(sample_id=i,target_text=rows[i].target_text),hyp,'en')
+  assert r.is_success, r.error
+  return i,{k:getattr(r,k) for k in ('wer','substitutions','deletions','insertions','hits')}|{'hyp_text':hyp}
+ with concurrent.futures.ThreadPoolExecutor(max_workers=4) as pool:
+  for i,result in pool.map(score,zip(ids,wavs)):
+   doc['rows'][i]['wer']=result
+ doc['tasks'].append('wer');save()
+if 'sim' in a.tasks and 'sim' not in doc['tasks']:
+ from benchmarks.metrics.speaker_similarity import WavLMSpeakerSimilarity
+ s=Path(a.scorers)/'sim'
+ scorer=WavLMSpeakerSimilarity(finetune_checkpoint=s/'wavlm_large_finetune.pth',wavlm_base=s/'wavlm_large.pt',device=a.device)
+ for j in range(0,len(ids),4):
+  scores=scorer.score_batch([rows[i].ref_wav_path for i in ids[j:j+4]],wavs[j:j+4])
+  for i,v in zip(ids[j:j+4],scores):doc['rows'][i]['sim']=float(v)
+ doc['tasks'].append('sim');save();del scorer
+if 'utmos' in a.tasks and 'utmos' not in doc['tasks']:
+ from benchmarks.metrics.utmos import UTMOSScorer
+ scorer=UTMOSScorer(device=a.device,cache_dir=Path(a.scorers)/'utmos')
+ for j in range(0,len(ids),8):
+  scores=scorer.score_batch(wavs[j:j+8])
+  for i,v in zip(ids[j:j+8],scores):doc['rows'][i]['utmos']=float(v)
+ doc['tasks'].append('utmos');save()
+summary={'n':len(ids)}
+for k in ('sim','utmos'):
+ if k in doc['tasks']:summary[k]=float(np.mean([v[k] for v in doc['rows'].values()]))
+if 'wer' in doc['tasks']:
+ counts={k:sum(v['wer'][k] for v in doc['rows'].values()) for k in ('substitutions','deletions','insertions','hits')}
+ summary['wer']=sum(counts[k] for k in ('substitutions','deletions','insertions'))/sum(counts[k] for k in ('substitutions','deletions','hits'))
+ summary['wer_counts']=counts
+ summary['wer_mean']=float(np.mean([v['wer']['wer'] for v in doc['rows'].values()]))
+doc['summary']=summary;save();print(json.dumps(summary),flush=True)
diff --git a/evidence/minicpmo45-l20x-20261021/validator/scorer-model-hashes.json b/evidence/minicpmo45-l20x-20261021/validator/scorer-model-hashes.json
new file mode 100644
index 000000000..4914073ca
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/scorer-model-hashes.json
@@ -0,0 +1,62 @@
+[
+  {
+    "file": "wavlm_large_finetune.pth",
+    "bytes": 1301926579,
+    "sha256": "51f07e3b94d9e0262a6a675ef5a087be3dd09e8c62e9d886827f44f82fe7f94b"
+  },
+  {
+    "file": "wavlm_large.pt",
+    "bytes": 1261965425,
+    "sha256": "6fb4b3c3e6aa567f0a997b30855859cb81528ee8078802af439f7b2da0bf100f"
+  },
+  {
+    "file": "utmos.jit",
+    "bytes": 413019495,
+    "sha256": "3080923f49ee69eb81ad875491eef94e533bf329d70e0cc37fa23745c464669d"
+  },
+  {
+    "file": "config.json",
+    "bytes": 6194,
+    "sha256": "2e74a751548b8ad7d7526d29365ad8144c345d8b412b1152d25dc6698452712f"
+  },
+  {
+    "file": "vocab.json",
+    "bytes": 2776833,
+    "sha256": "ca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910"
+  },
+  {
+    "file": "tokenizer_config.json",
+    "bytes": 12487,
+    "sha256": "4942d005604266809309cabc9f4e9cb89ce855d59b14681fdc0e1cc62ea26c4c"
+  },
+  {
+    "file": "model.safetensors.index.json",
+    "bytes": 64821,
+    "sha256": "f994739fe38e5210b9e3e8ce6c6307315e2ceac3cb630e7b7414d69dce520f60"
+  },
+  {
+    "file": "chat_template.json",
+    "bytes": 1161,
+    "sha256": "75a8cfca24f00de72d796fbfed6858fc9614ef3dabd8696684cc3bc03a9c58ff"
+  },
+  {
+    "file": "generation_config.json",
+    "bytes": 142,
+    "sha256": "1da527824d81e07118facff437e03f2e24a23311e3bdeb2368973fe77e5f275c"
+  },
+  {
+    "file": "preprocessor_config.json",
+    "bytes": 330,
+    "sha256": "45e120a4eda2c20c5d7f2ea9354e63536bf35e27aa573fb7cdf78017b378770d"
+  },
+  {
+    "file": "model-00002-of-00002.safetensors",
+    "bytes": 478200688,
+    "sha256": "6e0b9d9e09e2e0238e7ef3cc8a484ab387e91b90f1900bedf88bc92d7929ccfc"
+  },
+  {
+    "file": "model-00001-of-00002.safetensors",
+    "bytes": 4220320824,
+    "sha256": "a4cd1f1a04d90b757dc7f7dd26254e69a013b19e80efe590a83c6a3bde8608d6"
+  }
+]
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/validator/speaker-tests.json b/evidence/minicpmo45-l20x-20261021/validator/speaker-tests.json
new file mode 100644
index 000000000..777322a20
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/speaker-tests.json
@@ -0,0 +1,8 @@
+{
+  "passed": 67,
+  "warnings": 16,
+  "scope": "CPU regression; CUDA/real model numerical validation separately recorded",
+  "command": "pytest -q tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py tests/model_executor/models/cosyvoice3/test_speaker_embedding_cpu_reference.py tests/model_executor/models/step_audio2/test_step_audio2_token2wav_async_chunk.py -m 'core_model and cpu' --run-level core_model",
+  "ci_routing": ".buildkite/cuda/test-ready.yml existing tests/model_executor core_model and cpu step",
+  "precommit": "passed"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/speaker_trt_ieee.py b/evidence/minicpmo45-l20x-20261021/validator/speaker_trt_ieee.py
new file mode 100644
index 000000000..0e59a373d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/speaker_trt_ieee.py
@@ -0,0 +1,158 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""TensorRT speaker-embedding (campplus) extractor for CosyVoice3.
+
+Drop-in accelerator for the ONNX-Runtime campplus session used in the
+multimodal processor. ``campplus.onnx`` maps an fbank feature
+``[B, T, 80]`` to a 192-d speaker embedding ``[B, 192]``; on this stack the
+ONNX path only has a CPU execution provider, so it dominates per-request
+prompt-processing latency. Building a TensorRT engine once and running it on
+GPU removes that bottleneck.
+
+The engine is built lazily from ``campplus.onnx`` on first use and cached as
+a ``.plan`` file (engines are device/TRT-version specific, so the cache key
+includes both). Set ``COSYVOICE3_TRT_CACHE`` to override the cache dir.
+
+Written against TensorRT >= 10/11: ``EXPLICIT_BATCH`` is the implicit default
+(create the network with no flags) and ``ITensor.dtype`` is read-only (I/O
+dtypes come from the ONNX graph), so neither is set here.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import os
+import threading
+
+import torch
+from vllm.logger import init_logger
+
+logger = init_logger(__name__)
+
+# campplus fbank sequence length bounds for the optimization profile.
+_MIN_T = 4
+_OPT_T = 500
+_MAX_T = 3000
+_EMBED_DIM = 192
+
+
+def _trt_logger():
+    import tensorrt as trt
+
+    return trt.Logger(trt.Logger.WARNING)
+
+
+def _convert_onnx_to_trt(onnx_path: str, plan_path: str) -> None:
+    import tensorrt as trt
+
+    logger.info("Building campplus TensorRT engine from %s ...", onnx_path)
+    trt_logger = _trt_logger()
+    builder = trt.Builder(trt_logger)
+    # EXPLICIT_BATCH is implicit in TRT>=10; create the network with no flags.
+    network = builder.create_network(0)
+    parser = trt.OnnxParser(network, trt_logger)
+    with open(onnx_path, "rb") as f:
+        if not parser.parse(f.read()):
+            errs = "; ".join(str(parser.get_error(i)) for i in range(parser.num_errors))
+            raise ValueError(f"Failed to parse {onnx_path}: {errs}")
+
+    config = builder.create_builder_config()
+    config.clear_flag(trt.BuilderFlag.TF32)
+    config.set_memory_pool_limit(trt.MemoryPoolType.WORKSPACE, 1 << 31)  # 2 GiB
+
+    input_name = network.get_input(0).name
+    profile = builder.create_optimization_profile()
+    profile.set_shape(
+        input_name,
+        (1, _MIN_T, 80),
+        (1, _OPT_T, 80),
+        (1, _MAX_T, 80),
+    )
+    config.add_optimization_profile(profile)
+
+    engine_bytes = builder.build_serialized_network(network, config)
+    if engine_bytes is None:
+        raise RuntimeError(f"TensorRT failed to build campplus engine from {onnx_path}")
+    tmp = plan_path + ".tmp"
+    with open(tmp, "wb") as f:
+        f.write(engine_bytes)
+    os.replace(tmp, plan_path)
+    logger.info("Wrote campplus TensorRT engine to %s", plan_path)
+
+
+def _resolve_plan_path(onnx_path: str, prefix: str = "campplus") -> str:
+    cache_dir = os.environ.get("COSYVOICE3_TRT_CACHE") or os.path.join(
+        os.path.expanduser("~"), ".cache", "vllm_omni", "cosyvoice3_trt"
+    )
+    os.makedirs(cache_dir, exist_ok=True)
+    try:
+        # No-arg form targets the current device (avoids the banned
+        # torch.cuda.current_device per ruff TID251).
+        dev_name = torch.cuda.get_device_name()
+    except Exception:
+        dev_name = "unknown"
+    import tensorrt as trt
+
+    st = os.stat(onnx_path)
+    key = f"{os.path.abspath(onnx_path)}|{st.st_size}|{int(st.st_mtime)}|{dev_name}|trt{trt.__version__}"
+    digest = hashlib.sha1(key.encode()).hexdigest()[:16]
+    return os.path.join(cache_dir, f"{prefix}_{digest}.plan")
+
+
+class CampplusTRT:
+    """Lazily-built TensorRT campplus speaker-embedding extractor."""
+
+    def __init__(self, onnx_path: str, device: str | torch.device):
+        import tensorrt as trt
+
+        self.device = torch.device(device)
+        plan_path = _resolve_plan_path(onnx_path)
+        if not os.path.exists(plan_path) or os.path.getsize(plan_path) == 0:
+            _convert_onnx_to_trt(onnx_path, plan_path)
+
+        runtime = trt.Runtime(_trt_logger())
+        with open(plan_path, "rb") as f:
+            self.engine = runtime.deserialize_cuda_engine(f.read())
+        if self.engine is None:
+            raise RuntimeError(f"Failed to deserialize campplus TensorRT engine {plan_path}")
+        self.context = self.engine.create_execution_context()
+        self.input_name = self.engine.get_tensor_name(0)
+        self.output_name = self.engine.get_tensor_name(1)
+        # TRT execution contexts are not safe for concurrent enqueue; serialize.
+        self._lock = threading.Lock()
+        logger.info("Loaded campplus TensorRT engine (%s)", plan_path)
+
+    @torch.inference_mode()
+    def __call__(self, feat: torch.Tensor) -> torch.Tensor:
+        """feat: ``[T, 80]`` fbank features. Returns ``[1, 192]`` embedding."""
+        x = feat.unsqueeze(0).to(self.device, dtype=torch.float32).contiguous()
+        out = torch.empty((x.shape[0], _EMBED_DIM), device=self.device, dtype=torch.float32)
+        stream = torch.cuda.current_stream(self.device)
+        with self._lock:
+            self.context.set_input_shape(self.input_name, tuple(x.shape))
+            self.context.set_tensor_address(self.input_name, x.data_ptr())
+            self.context.set_tensor_address(self.output_name, out.data_ptr())
+            ok = self.context.execute_async_v3(stream.cuda_stream)
+            if not ok:
+                raise RuntimeError("campplus TensorRT execute_async_v3 failed")
+            stream.synchronize()
+        return out
+
+
+# Process-wide cache: the mm processor is re-created per request (the deploy
+# config disables the mm-processor object cache), so building a fresh
+# CampplusTRT each time would re-deserialize the ~33 MB engine and allocate a
+# new execution context on every request — inflating TTFP. Cache by
+# (engine path, device) and reuse; the context serializes concurrent enqueues
+# via its own lock, so a single shared instance is safe across requests.
+_CAMPPLUS_CACHE: dict[tuple[str, str], CampplusTRT] = {}
+
+
+def get_campplus_trt(onnx_path: str, device: str | torch.device) -> CampplusTRT:
+    """Return a process-wide cached :class:`CampplusTRT` (engine + context)."""
+    key = (os.path.abspath(onnx_path), str(device))
+    inst = _CAMPPLUS_CACHE.get(key)
+    if inst is None:
+        inst = CampplusTRT(onnx_path, device)
+        _CAMPPLUS_CACHE[key] = inst
+    return inst
diff --git a/evidence/minicpmo45-l20x-20261021/validator/summarize_results.py b/evidence/minicpmo45-l20x-20261021/validator/summarize_results.py
new file mode 100644
index 000000000..b541bf426
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/summarize_results.py
@@ -0,0 +1,77 @@
+"""Aggregate saved runs and apply the campaign's frozen directional gates."""
+import argparse
+import json
+import statistics
+from pathlib import Path
+
+import numpy as np
+
+
+def aggregate(root):
+    rows = []
+    for concurrency in (1, 2, 4, 8, 16, 32):
+        summaries, requests = [], []
+        for repeat in (1, 2, 3):
+            folder = root / f"c{concurrency}/run{repeat}"
+            if not (folder / "summary.json").exists():
+                continue
+            summaries.append(json.loads((folder / "summary.json").read_text()))
+            requests.extend(json.loads(line) for line in (folder / "requests.jsonl").read_text().splitlines())
+        if not summaries:
+            continue
+        rates = [row["throughput_frames_s"] for row in summaries]
+        rows.append({
+            "concurrency": concurrency,
+            "requests_per_repeat": [row["n_requests"] for row in summaries],
+            "repeats": len(summaries),
+            "n_failed": sum(row["n_failed"] for row in summaries),
+            "throughput_frames_s_mean": statistics.mean(rates),
+            "throughput_frames_s_runs": rates,
+            "ttfa_p50_ms_pooled": float(np.percentile([row["ttfa_s"] for row in requests], 50) * 1000),
+            "ttfa_p95_ms_pooled": float(np.percentile([row["ttfa_s"] for row in requests], 95) * 1000),
+            "rtf_mean": statistics.mean(row["rtf"] for row in requests),
+            "mean_audio_seconds": statistics.mean(row["duration_s"] for row in requests),
+        })
+    return rows
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--baseline", type=Path, required=True)
+    parser.add_argument("--candidate", type=Path, required=True)
+    parser.add_argument("--quality-dir", type=Path, required=True)
+    parser.add_argument("--baseline-quality-prefix", default="vllm-repeated")
+    parser.add_argument("--candidate-quality-prefix", default="vllm-speaker-repeated")
+    parser.add_argument("--out", type=Path, required=True)
+    args = parser.parse_args()
+    baseline, candidate = aggregate(args.baseline), aggregate(args.candidate)
+    complete = all(len(rows) == 6 and all(row["repeats"] == 3 and row["requests_per_repeat"] == [320] * 3 for row in rows) for rows in (baseline, candidate))
+    performance = []
+    for concurrency in (16, 32):
+        b = next((row for row in baseline if row["concurrency"] == concurrency), None)
+        c = next((row for row in candidate if row["concurrency"] == concurrency), None)
+        if b and c:
+            performance.append({"concurrency": concurrency, "gain_ratio": c["throughput_frames_s_mean"] / b["throughput_frames_s_mean"], "all_candidate_runs_exceed_all_baseline_runs": min(c["throughput_frames_s_runs"]) > max(b["throughput_frames_s_runs"])})
+    quality = []
+    for concurrency in (1, 16, 32):
+        paths = [args.quality_dir / f"{prefix}-c{concurrency}.json" for prefix in (args.baseline_quality_prefix, args.candidate_quality_prefix)]
+        if not all(path.exists() for path in paths):
+            continue
+        b, c = [json.loads(path.read_text()) for path in paths]
+        if not all(set(doc["tasks"]) == {"wer", "sim", "utmos"} for doc in (b, c)):
+            continue
+        b, c = b["summary"], c["summary"]
+        quality.append({"concurrency": concurrency, "baseline": b, "candidate": c, "gates": {"wer_nonincrease": c["wer"] <= b["wer"], "sim_nondecrease": c["sim"] >= b["sim"], "utmos_nondecrease": c["utmos"] >= b["utmos"]}})
+    if not complete or len(quality) != 3:
+        verdict = "INCONCLUSIVE"
+    elif any(row["n_failed"] for row in baseline + candidate) or not all(all(row["gates"].values()) for row in quality):
+        verdict = "FAIL"
+    elif len(performance) != 2 or not all(row["all_candidate_runs_exceed_all_baseline_runs"] for row in performance):
+        verdict = "FAIL"
+    else:
+        verdict = "PASS"
+    args.out.write_text(json.dumps({"verdict": verdict, "scope": "Frozen steady-state throughput and point-estimate speech gates; no global optimum or cold-cache certification", "baseline": baseline, "candidate": candidate, "performance": performance, "quality": quality}, indent=2) + "\n")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
index 18a832c8d..625e7bfe1 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
@@ -15,7 +15,7 @@ These are knowledge abstracts (`--kind knowledge`), with namespaced package
 IDs distinct from explicitly selected `checkout_ref` skills. Ascend/CUDA
 procedures use their corresponding backend; shared methods use `common`.
 
-Source snapshot: [ba5290acecb9688dfdc6225dba83d8a6a23dee22](https://github.com/InferMatrixLab/InferRSI/tree/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library).
+Source snapshot: [9e22223040c7dc1bffe0b04de13a411ddd06646e](https://github.com/InferMatrixLab/InferRSI/tree/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library).
 
 ```bash
 inferrsi knowledge search 'profiling' --repo-type inferrsi --limit 50
@@ -29,7 +29,7 @@ contain the current input paths and bytes (Git checkout filters are respected).
 
 ```bash
 python tools/build_skill_index.py --source-revision <committed-source-revision>
-python tools/build_skill_index.py --source-revision ba5290acecb9688dfdc6225dba83d8a6a23dee22 --check
+python tools/build_skill_index.py --source-revision 9e22223040c7dc1bffe0b04de13a411ddd06646e --check
 ```
 
 `--check` detects missing, stale and unexpected generated records without writing.
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
index 5c7ef132e..b8f4d0ed7 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
index 83a95b1dc..1e66c1421 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
index adeb97ed6..541b9ec89 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
index 9df3e3177..74a05ffda 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
index 38335c43a..785e4dde8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
index 3723c7833..e1254de94 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
index 9a8658b5e..e14f3332a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
index 095da8cf3..d9b542932 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
index 5fa671b8f..9246ac746 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
index d783badcd..4f1bf4c6d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
index 6e13b8bef..e75ca7a71 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
index 58f56749f..adf7bb57a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
index 0b1ad3608..d0dfdded1 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
index c21feaed5..fbfb8a8a5 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/methods/assess-serving-preemption/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/assess-serving-preemption/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/methods/assess-serving-preemption/SKILL.md",
         "src/inferrsi/data/skill_library/methods/assess-serving-preemption/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
index 73d78243c..42d3d72c0 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/methods/assess-split-backward-schedule/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/assess-split-backward-schedule/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/methods/assess-split-backward-schedule/SKILL.md",
         "src/inferrsi/data/skill_library/methods/assess-split-backward-schedule/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
index 02d58b721..5be576ef8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
@@ -21,8 +21,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json
index 225a26d08..74656b7ce 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json
@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
index 423bad354..09ed2ec5c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
@@ -25,8 +25,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
index bdab5b08d..9f439e23c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
@@ -22,8 +22,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
index 8e700bac0..6b427eb59 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json
index f08c3c7bd..be329b512 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json
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index 8ee2867fa..1c1d5a29e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/claim-contract.json
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index fdb9dd873..39e5a0176 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
index f3304eec3..8da19d5e7 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
index 95d09aba9..222ae1324 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
index 510043dcf..8a73b81d4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
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index 3e7aaa138..080ba0a9a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
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index 14d4375cb..e5297d42b 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
index c50b4bfd0..2ee351d31 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json
index 91865ca79..6f78ce7f3 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json
index bd63d273c..5b149c594 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json
index 011f61491..cafb16f81 100644
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         "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/drama3-rejected-directions.md",
+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json",
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@@ -36,7 +38,7 @@
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@@ -45,11 +47,13 @@
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index c17b18b30..fa2c0f533 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
@@ -24,8 +24,8 @@
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index 1d87a0cda..800901aaf 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
index e0f8053e8..7b0fcb765 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
@@ -22,8 +22,8 @@
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index 67a9e508e..6acdcb066 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
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index b25996fad..e3c2a1a44 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
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index 36f9e8de4..8f865a100 100644
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index 4a736e9e4..da2bc93a8 100644
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index 742ab5db4..64f232002 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
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@@ -21,8 +21,8 @@
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index fc53679f9..16c561851 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
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index f33b62d14..77420301e 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
index e0b2e1567..39333ba22 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
index 9454955a4..0ede14999 100644
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index 53291c0f1..b331e438a 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
index 2fbbd7855..708c33bb7 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
index a31c6b3f3..73dbbab7c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
index 8755f9244..e2d037bc8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ba5290acecb9688dfdc6225dba83d8a6a23dee22/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
-      "commit": "ba5290acecb9688dfdc6225dba83d8a6a23dee22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
+      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json",

From 5f0b0a5d37e76472a45a4d745f2d0463232922fa Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 11:27:01 +0800
Subject: [PATCH 03/40] Freeze separately authorized MiniCPM speech
 noninferiority holdout

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/noninferiority-holdout.json          | 366 ++++++++++++++++++
 .../validator/noninferiority.py               |  95 +++++
 .../validator/run_holdout.py                  |  51 +++
 3 files changed, 512 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/noninferiority-holdout.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/noninferiority.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/run_holdout.py

diff --git a/evidence/minicpmo45-l20x-20261021/plan/noninferiority-holdout.json b/evidence/minicpmo45-l20x-20261021/plan/noninferiority-holdout.json
new file mode 100644
index 000000000..ca97e7dd8
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/noninferiority-holdout.json
@@ -0,0 +1,366 @@
+{
+  "state": "frozen_before_unused_holdout_generation",
+  "frozen_at_utc": "2026-10-21T03:24:13.174331+00:00",
+  "acceptance_issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+  "authority": "User delegated choice of reasonable margins; old strict zero-regression verdict remains unchanged.",
+  "scope": "New noninferiority validation only; margins chosen after exploratory first-cohort results, before any second-cohort generation. Not universal perceptual thresholds.",
+  "margins": {
+    "wer_percentage_points": 0.2,
+    "sim_x100_drop": 0.5,
+    "utmos_drop": 0.05
+  },
+  "candidate_selection": "Among already frozen speaker-only and speaker+MPS profiles, choose highest geometric-mean repeated C16/C32 throughput before opening holdout; no tuning using holdout.",
+  "baseline_sha": "aa3fd1d9b7f5c7191dec11975ac0aa7c4c4a18c5",
+  "candidate_sha": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
+  "cohort": {
+    "pool": "eval_pool",
+    "offset": 320,
+    "count": 320,
+    "concurrencies": [
+      1,
+      16,
+      32
+    ],
+    "warmup": "existing disjoint warm pool, 2C",
+    "discard_runs": 1,
+    "measured_runs": 1,
+    "ids": [
+      "common_voice_en_23954802-common_voice_en_23954801",
+      "common_voice_en_35042682-common_voice_en_35042683",
+      "common_voice_en_682528-common_voice_en_682536",
+      "common_voice_en_17352169-common_voice_en_17352173",
+      "common_voice_en_485101-common_voice_en_485100",
+      "common_voice_en_19979514-common_voice_en_19979517",
+      "common_voice_en_605765-common_voice_en_605777",
+      "common_voice_en_563060-common_voice_en_563063",
+      "common_voice_en_32717587-common_voice_en_32717586",
+      "common_voice_en_19933652-common_voice_en_19933661",
+      "common_voice_en_32263901-common_voice_en_32263900",
+      "common_voice_en_19951090-common_voice_en_19951089",
+      "common_voice_en_18757805-common_voice_en_18757804",
+      "common_voice_en_24356884-common_voice_en_24356920",
+      "common_voice_en_17817002-common_voice_en_17817003",
+      "common_voice_en_25662916-common_voice_en_25663069",
+      "common_voice_en_20027471-common_voice_en_20027487",
+      "common_voice_en_22364189-common_voice_en_22364187",
+      "common_voice_en_17263780-common_voice_en_17263781",
+      "common_voice_en_17259121-common_voice_en_17259122",
+      "common_voice_en_19632634-common_voice_en_19632638",
+      "common_voice_en_17502-common_voice_en_17503",
+      "common_voice_en_31576099-common_voice_en_31576097",
+      "common_voice_en_19691845-common_voice_en_19691840",
+      "common_voice_en_621521-common_voice_en_621522",
+      "common_voice_en_19428391-common_voice_en_19428392",
+      "common_voice_en_25313898-common_voice_en_25313900",
+      "common_voice_en_19750016-common_voice_en_19750010",
+      "common_voice_en_36990355-common_voice_en_36990357",
+      "common_voice_en_155313-common_voice_en_155315",
+      "common_voice_en_557392-common_voice_en_557393",
+      "common_voice_en_16666041-common_voice_en_16666040",
+      "common_voice_en_19397397-common_voice_en_19397399",
+      "common_voice_en_530085-common_voice_en_530083",
+      "common_voice_en_21538043-common_voice_en_21538044",
+      "common_voice_en_18647546-common_voice_en_18647550",
+      "common_voice_en_1416089-common_voice_en_1416093",
+      "common_voice_en_17278904-common_voice_en_17278909",
+      "common_voice_en_21444162-common_voice_en_21444161",
+      "common_voice_en_21345624-common_voice_en_21345625",
+      "common_voice_en_22722937-common_voice_en_22722936",
+      "common_voice_en_603760-common_voice_en_603759",
+      "common_voice_en_22525318-common_voice_en_22525329",
+      "common_voice_en_21504874-common_voice_en_21504872",
+      "common_voice_en_25313898-common_voice_en_25313899",
+      "common_voice_en_20872043-common_voice_en_20872044",
+      "common_voice_en_19701583-common_voice_en_19701588",
+      "common_voice_en_30232728-common_voice_en_30232725",
+      "common_voice_en_22461617-common_voice_en_22461634",
+      "common_voice_en_17519982-common_voice_en_17519988",
+      "common_voice_en_20661858-common_voice_en_20661860",
+      "common_voice_en_36990355-common_voice_en_36990358",
+      "common_voice_en_19778240-common_voice_en_19778260",
+      "common_voice_en_27474919-common_voice_en_27474918",
+      "common_voice_en_27383934-common_voice_en_27383936",
+      "common_voice_en_35299046-common_voice_en_35299049",
+      "common_voice_en_19599129-common_voice_en_19599130",
+      "common_voice_en_23786332-common_voice_en_23786333",
+      "common_voice_en_19692939-common_voice_en_19693060",
+      "common_voice_en_28932865-common_voice_en_28932867",
+      "common_voice_en_19717736-common_voice_en_19717739",
+      "common_voice_en_18852076-common_voice_en_18852077",
+      "common_voice_en_25572984-common_voice_en_25572982",
+      "common_voice_en_650392-common_voice_en_650390",
+      "common_voice_en_578084-common_voice_en_578102",
+      "common_voice_en_17275818-common_voice_en_17275816",
+      "common_voice_en_18466098-common_voice_en_18466097",
+      "common_voice_en_86363-common_voice_en_86360",
+      "common_voice_en_27501458-common_voice_en_27501460",
+      "common_voice_en_19527999-common_voice_en_19528002",
+      "common_voice_en_37793802-common_voice_en_37793803",
+      "common_voice_en_19898846-common_voice_en_19898849",
+      "common_voice_en_24681934-common_voice_en_24681933",
+      "common_voice_en_18746637-common_voice_en_18746638",
+      "common_voice_en_31499885-common_voice_en_31499906",
+      "common_voice_en_571544-common_voice_en_571548",
+      "common_voice_en_22763534-common_voice_en_22763535",
+      "common_voice_en_20026430-common_voice_en_20026432",
+      "common_voice_en_63703-common_voice_en_63704",
+      "common_voice_en_578084-common_voice_en_578101",
+      "common_voice_en_32101327-common_voice_en_32101328",
+      "common_voice_en_524057-common_voice_en_524059",
+      "common_voice_en_18575865-common_voice_en_18575864",
+      "common_voice_en_20972789-common_voice_en_20972791",
+      "common_voice_en_19481268-common_voice_en_19481267",
+      "common_voice_en_18754308-common_voice_en_18754311",
+      "common_voice_en_490614-common_voice_en_490613",
+      "common_voice_en_64065-common_voice_en_64063",
+      "common_voice_en_24015114-common_voice_en_24015144",
+      "common_voice_en_497961-common_voice_en_497960",
+      "common_voice_en_19602798-common_voice_en_19602797",
+      "common_voice_en_19635046-common_voice_en_19635047",
+      "common_voice_en_21621452-common_voice_en_21621455",
+      "common_voice_en_21620052-common_voice_en_21620053",
+      "common_voice_en_17880926-common_voice_en_17880932",
+      "common_voice_en_20735803-common_voice_en_20735805",
+      "common_voice_en_23601048-common_voice_en_23601051",
+      "common_voice_en_653337-common_voice_en_653336",
+      "common_voice_en_17578783-common_voice_en_17578780",
+      "common_voice_en_36074033-common_voice_en_36074034",
+      "common_voice_en_27794266-common_voice_en_27794265",
+      "common_voice_en_19729972-common_voice_en_19729975",
+      "common_voice_en_32767770-common_voice_en_32767778",
+      "common_voice_en_38573-common_voice_en_38572",
+      "common_voice_en_19979514-common_voice_en_19979516",
+      "common_voice_en_19869780-common_voice_en_19869781",
+      "common_voice_en_28884498-common_voice_en_28884500",
+      "common_voice_en_22777850-common_voice_en_22777852",
+      "common_voice_en_1205005-common_voice_en_1205008",
+      "common_voice_en_20177004-common_voice_en_20177032",
+      "common_voice_en_657467-common_voice_en_657468",
+      "common_voice_en_21352017-common_voice_en_21352021",
+      "common_voice_en_23718813-common_voice_en_23718811",
+      "common_voice_en_20531306-common_voice_en_20531309",
+      "common_voice_en_37232389-common_voice_en_37190783",
+      "common_voice_en_23589975-common_voice_en_23589976",
+      "common_voice_en_19152197-common_voice_en_19152198",
+      "common_voice_en_17389984-common_voice_en_17389987",
+      "common_voice_en_17281385-common_voice_en_17281393",
+      "common_voice_en_19113286-common_voice_en_19113288",
+      "common_voice_en_21621452-common_voice_en_21621454",
+      "common_voice_en_2331-common_voice_en_2330",
+      "common_voice_en_23804758-common_voice_en_23804770",
+      "common_voice_en_34321814-common_voice_en_34321811",
+      "common_voice_en_19449066-common_voice_en_19449076",
+      "common_voice_en_26952530-common_voice_en_26952634",
+      "common_voice_en_18707936-common_voice_en_18707937",
+      "common_voice_en_17324784-common_voice_en_17324785",
+      "common_voice_en_30735432-common_voice_en_30735431",
+      "common_voice_en_24605843-common_voice_en_24605845",
+      "common_voice_en_32641373-common_voice_en_32641377",
+      "common_voice_en_667155-common_voice_en_667153",
+      "common_voice_en_19622969-common_voice_en_19622971",
+      "common_voice_en_18529345-common_voice_en_18529360",
+      "common_voice_en_20938865-common_voice_en_20938864",
+      "common_voice_en_606373-common_voice_en_606376",
+      "common_voice_en_19748004-common_voice_en_19748010",
+      "common_voice_en_19939156-common_voice_en_19939176",
+      "common_voice_en_22461617-common_voice_en_22461638",
+      "common_voice_en_674100-common_voice_en_674112",
+      "common_voice_en_588627-common_voice_en_588628",
+      "common_voice_en_20451876-common_voice_en_20451880",
+      "common_voice_en_22709462-common_voice_en_22709463",
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+      "common_voice_en_28932865-common_voice_en_28932866",
+      "common_voice_en_28065832-common_voice_en_28065833",
+      "common_voice_en_21589881-common_voice_en_21589886",
+      "common_voice_en_19768597-common_voice_en_19768600",
+      "common_voice_en_20522396-common_voice_en_20522398",
+      "common_voice_en_25200065-common_voice_en_25200064",
+      "common_voice_en_8805512-common_voice_en_8805513",
+      "common_voice_en_25257658-common_voice_en_25257664",
+      "common_voice_en_36537421-common_voice_en_36537432",
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+      "common_voice_en_38573-common_voice_en_38570",
+      "common_voice_en_20214898-common_voice_en_20214899",
+      "common_voice_en_25282242-common_voice_en_25282245",
+      "common_voice_en_46083-common_voice_en_46084",
+      "common_voice_en_19733143-common_voice_en_19733141",
+      "common_voice_en_26645969-common_voice_en_26645970",
+      "common_voice_en_17854896-common_voice_en_17854897",
+      "common_voice_en_23998981-common_voice_en_23998983",
+      "common_voice_en_21851999-common_voice_en_21852000",
+      "common_voice_en_673471-common_voice_en_673473",
+      "common_voice_en_30757408-common_voice_en_30757409",
+      "common_voice_en_699384-common_voice_en_699386",
+      "common_voice_en_18746637-common_voice_en_18746639",
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+      "common_voice_en_23728823-common_voice_en_23728827",
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+      "common_voice_en_19531363-common_voice_en_19531364",
+      "common_voice_en_508059-common_voice_en_508057",
+      "common_voice_en_32111431-common_voice_en_32111428",
+      "common_voice_en_71427-common_voice_en_71425",
+      "common_voice_en_20872478-common_voice_en_20872479",
+      "common_voice_en_22925816-common_voice_en_22925815",
+      "common_voice_en_19481268-common_voice_en_19481270",
+      "common_voice_en_37237245-common_voice_en_37237243",
+      "common_voice_en_23843606-common_voice_en_23843609",
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+      "common_voice_en_27099623-common_voice_en_27099625",
+      "common_voice_en_28919201-common_voice_en_28919202",
+      "common_voice_en_20972789-common_voice_en_20972792",
+      "common_voice_en_21851751-common_voice_en_21851745",
+      "common_voice_en_19933238-common_voice_en_19933256",
+      "common_voice_en_20232770-common_voice_en_20232772",
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+      "common_voice_en_22364189-common_voice_en_22364186",
+      "common_voice_en_652024-common_voice_en_652027",
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+      "common_voice_en_364081-common_voice_en_364080",
+      "common_voice_en_19867710-common_voice_en_19867712",
+      "common_voice_en_18754308-common_voice_en_18754312",
+      "common_voice_en_27389507-common_voice_en_27389509",
+      "common_voice_en_19949855-common_voice_en_19949857",
+      "common_voice_en_19863517-common_voice_en_19863518",
+      "common_voice_en_19671290-common_voice_en_19671293",
+      "common_voice_en_37457199-common_voice_en_37457235",
+      "common_voice_en_20006910-common_voice_en_20006912",
+      "common_voice_en_21538043-common_voice_en_21538045",
+      "common_voice_en_17406452-common_voice_en_17406455",
+      "common_voice_en_17781154-common_voice_en_17781153",
+      "common_voice_en_25563964-common_voice_en_25564015",
+      "common_voice_en_19734247-common_voice_en_19734251",
+      "common_voice_en_19961449-common_voice_en_19961453",
+      "common_voice_en_18187914-common_voice_en_18188853",
+      "common_voice_en_19560742-common_voice_en_19560749",
+      "common_voice_en_23176027-common_voice_en_23176029",
+      "common_voice_en_573135-common_voice_en_573137",
+      "common_voice_en_29495818-common_voice_en_29495898",
+      "common_voice_en_33907-common_voice_en_33906",
+      "common_voice_en_18200641-common_voice_en_18200765",
+      "common_voice_en_37133940-common_voice_en_37133871",
+      "common_voice_en_19701583-common_voice_en_19701587",
+      "common_voice_en_32144882-common_voice_en_32144885",
+      "common_voice_en_490614-common_voice_en_490618",
+      "common_voice_en_18105426-common_voice_en_18105428",
+      "common_voice_en_21877403-common_voice_en_21877406",
+      "common_voice_en_19750016-common_voice_en_19750004",
+      "common_voice_en_19695366-common_voice_en_19695364",
+      "common_voice_en_18852076-common_voice_en_18852085",
+      "common_voice_en_23650405-common_voice_en_23650406",
+      "common_voice_en_613849-common_voice_en_613850",
+      "common_voice_en_18529345-common_voice_en_18529361",
+      "common_voice_en_79862-common_voice_en_79860",
+      "common_voice_en_21722249-common_voice_en_21722261",
+      "common_voice_en_26319796-common_voice_en_26319797",
+      "common_voice_en_21742650-common_voice_en_21742653",
+      "common_voice_en_18522556-common_voice_en_18522557",
+      "common_voice_en_588627-common_voice_en_588631",
+      "common_voice_en_20933101-common_voice_en_20933104",
+      "common_voice_en_24523505-common_voice_en_24523506",
+      "common_voice_en_23750957-common_voice_en_23774578",
+      "common_voice_en_20048255-common_voice_en_20048258",
+      "common_voice_en_19671290-common_voice_en_19671292",
+      "common_voice_en_19706873-common_voice_en_19706870",
+      "common_voice_en_27585762-common_voice_en_27585765",
+      "common_voice_en_25204047-common_voice_en_25204042",
+      "common_voice_en_18557077-common_voice_en_18557192",
+      "common_voice_en_20617-common_voice_en_20618",
+      "common_voice_en_17837104-common_voice_en_17837105",
+      "common_voice_en_22771349-common_voice_en_22771352",
+      "common_voice_en_479422-common_voice_en_479426",
+      "common_voice_en_19760248-common_voice_en_19760249",
+      "common_voice_en_19361636-common_voice_en_19361635",
+      "common_voice_en_32125519-common_voice_en_32125523",
+      "common_voice_en_68569-common_voice_en_68571",
+      "common_voice_en_31350445-common_voice_en_31350446",
+      "common_voice_en_22810002-common_voice_en_22810004",
+      "common_voice_en_36558935-common_voice_en_36558813",
+      "common_voice_en_19933652-common_voice_en_19933655",
+      "common_voice_en_19739025-common_voice_en_19739024",
+      "common_voice_en_19517720-common_voice_en_19517721",
+      "common_voice_en_33985575-common_voice_en_33985579",
+      "common_voice_en_593372-common_voice_en_593370",
+      "common_voice_en_32377071-common_voice_en_32377072",
+      "common_voice_en_19729972-common_voice_en_19729973",
+      "common_voice_en_19397397-common_voice_en_19397407",
+      "common_voice_en_23618179-common_voice_en_23618180",
+      "common_voice_en_17830764-common_voice_en_17830762",
+      "common_voice_en_33985575-common_voice_en_33985578",
+      "common_voice_en_36074033-common_voice_en_36073874",
+      "common_voice_en_9559-common_voice_en_9562",
+      "common_voice_en_19727183-common_voice_en_19727187",
+      "common_voice_en_19898846-common_voice_en_19898843",
+      "common_voice_en_17288057-common_voice_en_17288056",
+      "common_voice_en_19496235-common_voice_en_19496229",
+      "common_voice_en_20735803-common_voice_en_20735807",
+      "common_voice_en_21504874-common_voice_en_21504873",
+      "common_voice_en_17442686-common_voice_en_17442688",
+      "common_voice_en_615162-common_voice_en_615165",
+      "common_voice_en_153872-common_voice_en_153874",
+      "common_voice_en_18786931-common_voice_en_18786946",
+      "common_voice_en_18829843-common_voice_en_18829842",
+      "common_voice_en_32683120-common_voice_en_32683117",
+      "common_voice_en_664748-common_voice_en_664753",
+      "common_voice_en_23606989-common_voice_en_23606990",
+      "common_voice_en_27389507-common_voice_en_27389508",
+      "common_voice_en_24015547-common_voice_en_24015544",
+      "common_voice_en_18545637-common_voice_en_18545639",
+      "common_voice_en_18200641-common_voice_en_18200790",
+      "common_voice_en_18699078-common_voice_en_18699082",
+      "common_voice_en_17278904-common_voice_en_17278905",
+      "common_voice_en_20068182-common_voice_en_20068193",
+      "common_voice_en_19384720-common_voice_en_19384721",
+      "common_voice_en_17369337-common_voice_en_17369336",
+      "common_voice_en_24504889-common_voice_en_24504891",
+      "common_voice_en_24015114-common_voice_en_24015142",
+      "common_voice_en_21802531-common_voice_en_21802562",
+      "common_voice_en_36537421-common_voice_en_36537433",
+      "common_voice_en_21619912-common_voice_en_21634642",
+      "common_voice_en_18313326-common_voice_en_18313328",
+      "common_voice_en_21851751-common_voice_en_21851747",
+      "common_voice_en_18786931-common_voice_en_18786930",
+      "common_voice_en_18889688-common_voice_en_18889686",
+      "common_voice_en_20791113-common_voice_en_20791116",
+      "common_voice_en_530085-common_voice_en_530084",
+      "common_voice_en_22793454-common_voice_en_22793457",
+      "common_voice_en_103675-common_voice_en_103677",
+      "common_voice_en_32734226-common_voice_en_32734228"
+    ],
+    "ids_sha256": "4a80518eafae91cc3903dd85f23b4704d875d2e22b981e300f2f69263d8c3d82"
+  },
+  "statistics": {
+    "method": "Paired prompt percentile bootstrap, resampling identical prompt indices for baseline and candidate; corpus WER recomputed from summed edit/reference counts each resample.",
+    "replicates": 20000,
+    "seed": 20261022,
+    "bound": "one-sided 95th percentile of degradation",
+    "acceptance": "Every metric at every concurrency must have upper bound <= margin; missing or nonfinite data INCONCLUSIVE; observed violation FAIL. This is an intersection-union decision, no selection of passing cells.",
+    "limitations": "Prompt bootstrap conditional on these generated outputs; not a listening study or a bound across model seeds/languages."
+  },
+  "driver_sha256": "4d8df91e67dfceeaa73bff4d8a74c2cfc85a493190faa11c1ab4b3d8aad51936",
+  "sources": [
+    "https://github.com/BytedanceSpeech/seed-tts-eval",
+    "https://arxiv.org/abs/2204.02152"
+  ],
+  "validator_sha256": "0ada2681a11defe5c5ae8b825786b5b4ec5c38cdc3838f539375257c6d5bd67a",
+  "runtime": "Sequential freshly started baseline and selected candidate on the same reserved L20X GPU. Fixed pool order and warmup; both score run1."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/noninferiority.py b/evidence/minicpmo45-l20x-20261021/validator/noninferiority.py
new file mode 100644
index 000000000..fc61e9c9b
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/noninferiority.py
@@ -0,0 +1,95 @@
+"""Frozen, paired prompt bootstrap for the separately authorized holdout."""
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+
+
+def evaluate(baseline, candidate, margins):
+    b, c = baseline["rows"], candidate["rows"]
+    if set(b) != set(c) or len(b) != 320:
+        raise ValueError("Expected exactly 320 matched prompts")
+    if any(set(doc["tasks"]) != {"wer", "sim", "utmos"} for doc in (baseline, candidate)):
+        raise ValueError("Incomplete scorers")
+    ids = sorted(b)
+    rng = np.random.default_rng(20261022)
+    draws = rng.integers(0, len(ids), size=(20000, len(ids)))
+    result = {}
+    for metric in ("wer_percentage_points", "sim_x100_drop", "utmos_drop"):
+        if metric == "wer_percentage_points":
+            values = []
+            for rows in (b, c):
+                errors = np.array(
+                    [
+                        sum(rows[i]["wer"][k] for k in ("substitutions", "deletions", "insertions"))
+                        for i in ids
+                    ]
+                )
+                words = np.array(
+                    [
+                        sum(rows[i]["wer"][k] for k in ("substitutions", "deletions", "hits"))
+                        for i in ids
+                    ]
+                )
+                if np.any(words <= 0):
+                    raise ValueError("Invalid reference count")
+                values.append((errors, words))
+            if not np.array_equal(values[0][1], values[1][1]):
+                raise ValueError("Different reference denominators")
+            point = 100 * (
+                values[1][0].sum() / values[1][1].sum() - values[0][0].sum() / values[0][1].sum()
+            )
+            distribution = 100 * (
+                (values[1][0] - values[0][0])[draws].sum(axis=1) / values[0][1][draws].sum(axis=1)
+            )
+        else:
+            key = "sim" if metric.startswith("sim") else "utmos"
+            delta = np.array([b[i][key] - c[i][key] for i in ids])
+            point = delta.mean()
+            distribution = delta[draws].mean(axis=1)
+        upper = float(np.percentile(distribution, 95))
+        if not np.isfinite(distribution).all() or not np.isfinite(point):
+            raise ValueError("Nonfinite scores")
+        result[metric] = {
+            "degradation": float(point),
+            "upper_one_sided_95": upper,
+            "margin": margins[metric],
+            "verdict": "PASS" if upper <= margins[metric] else "FAIL",
+        }
+    return {
+        "n": len(ids),
+        "metrics": result,
+        "verdict": "PASS" if all(x["verdict"] == "PASS" for x in result.values()) else "FAIL",
+    }
+
+
+def main():
+    p = argparse.ArgumentParser()
+    p.add_argument("--plan", type=Path, required=True)
+    p.add_argument("--quality-dir", type=Path, required=True)
+    p.add_argument("--out", type=Path, required=True)
+    a = p.parse_args()
+    plan = json.loads(a.plan.read_text())
+    report = {"scope": "Unused holdout noninferiority; original strict gate unchanged", "cells": {}}
+    try:
+        for concurrency in plan["cohort"]["concurrencies"]:
+            docs = [
+                json.loads((a.quality_dir / f"vllm-holdout-{role}-c{concurrency}.json").read_text())
+                for role in ("main", "candidate")
+            ]
+            if any(set(doc["rows"]) != set(plan["cohort"]["ids"]) for doc in docs):
+                raise ValueError("Outputs do not match frozen unused holdout IDs")
+            report["cells"][str(concurrency)] = evaluate(*docs, plan["margins"])
+        report["verdict"] = (
+            "PASS" if all(x["verdict"] == "PASS" for x in report["cells"].values()) else "FAIL"
+        )
+    except (OSError, ValueError, KeyError) as exc:
+        report.update(verdict="INCONCLUSIVE", reason=str(exc))
+    a.out.write_text(json.dumps(report, indent=2) + "\n")
+    print(json.dumps(report))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/run_holdout.py b/evidence/minicpmo45-l20x-20261021/validator/run_holdout.py
new file mode 100644
index 000000000..0c1d8ce1f
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/run_holdout.py
@@ -0,0 +1,51 @@
+import argparse
+import asyncio
+import json
+from pathlib import Path
+from bench.adapters import get_adapter
+from bench.client import make_session
+from bench.protocol import closed_loop, evaluate_run, save_run
+from bench.workload import load_seed_tts_rows, make_id_sets, canonical_requests
+
+async def main():
+    p = argparse.ArgumentParser()
+    p.add_argument('--adapter', required=True)
+    p.add_argument('--url', required=True)
+    p.add_argument('--out', required=True)
+    p.add_argument('--concurrency', type=int, nargs='+', default=[1,2,4,8,16,32])
+    p.add_argument('--requests', type=int, default=320)
+    p.add_argument('--repeats', type=int, default=3)
+    p.add_argument('--eval-offset', type=int, default=0)
+    p.add_argument('--id-set', choices=['eval', 'tuning'], default='eval')
+    a = p.parse_args()
+    out = Path(a.out)
+    out.mkdir(parents=True, exist_ok=True)
+    rows = load_seed_tts_rows()
+    sets = make_id_sets(rows)
+    adapter = get_adapter(a.adapter)
+    # Exploratory steady-state baseline. No restart between cells; explicitly
+    # distinct from the reference campaign's fresh-server certification.
+    plan = vars(a) | {'cache_policy':'none', 'qualification':'exploratory', 'ids':sets.to_json()}
+    (out/'plan.json').write_text(json.dumps(plan, indent=2))
+    async with make_session() as session:
+        for c in a.concurrency:
+            warm = canonical_requests(rows, sets.warmup(c))
+            traces = await closed_loop(session,a.url,adapter,warm,c,timeout_s=180)
+            result = evaluate_run('warmup',c,traces,measured=False)
+            save_run(result,out/f'c{c}'/'warmup')
+            if any(not r.ok for r in result.per_request):
+                raise RuntimeError(f'C{c} warmup failed; inspect saved traces')
+            pool = sets.eval_pool if a.id_set == 'eval' else sets.tuning_pool
+            pool = pool[a.eval_offset:]
+            if a.eval_offset < 0 or a.requests > len(pool):
+                raise ValueError('Requested count exceeds the selected disjoint pool')
+            reqs=canonical_requests(rows, list(pool[:a.requests]))
+            for k in range(a.repeats+1):
+                traces=await closed_loop(session,a.url,adapter,reqs,c,timeout_s=180,record_raw=True)
+                result=evaluate_run(f'run{k}',c,traces,measured=k>0)
+                save_run(result,out/f'c{c}'/f'run{k}')
+                print(json.dumps(result.summary()),flush=True)
+                if any(not r.ok for r in result.per_request):
+                    raise RuntimeError(f'C{c} run{k} failed; inspect saved traces')
+
+asyncio.run(main())

From 0b52e63946954a283e6d985ac4c940d2c4bf195d Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 11:44:21 +0800
Subject: [PATCH 04/40] Record repeated speaker and MPS controls with strict
 speech failures

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   70 +-
 .../patch/speaker-mps.yaml                    |    6 +
 .../cpu-reference-parallel-hypothesis.json    |    9 +
 .../plan/fresh-start-allocation-addendum.json |    6 +
 .../plan/fresh-start-confirmation.json        |   17 +
 .../plan/knowledge-transfer.json              |   33 +
 .../plan/noninferiority-selection.json        |   40 +
 .../plan/runtime-observations.json            |   47 +
 .../plan/speaker-mps-control.json             |   19 +
 .../plan/speaker-mps-resolved-config.json     |  474 +++
 .../plan/speaker-only-resolved-config.json    |  474 +++
 .../plan/speaker-runspec-redacted.json        |   56 +
 .../results/c1-quality-repeat-check.json      |   75 +
 .../results/concurrency-comparison.png        |  Bin 0 -> 216712 bytes
 .../results/concurrency-comparison.svg        | 2959 +++++++++++++++++
 .../results/mps-comparison.json               |  364 ++
 .../results/prompt-workers-prototype.json     | 1975 +++++++++++
 .../results/quality-c1-uncertainty.json       |   22 +
 .../results/speaker-comparison.json           |  364 ++
 .../results/speaker-cpu-threads.json          |  150 +
 .../results/speaker-mps-quality.json.gz       |  Bin 0 -> 74042 bytes
 .../results/speaker-quality.json.gz           |  Bin 0 -> 74128 bytes
 .../results/speaker-waveform-diagnostic.json  |  453 +++
 .../results/status.json                       |   16 +-
 .../results/tuning-table.json                 |  446 +++
 .../vllm-speaker-microbatch-tuning.json.gz    |  Bin 0 -> 47439 bytes
 .../results/vllm-speaker-mps-repeated.json.gz |  Bin 0 -> 1090706 bytes
 .../results/vllm-speaker-mps-tuning.json.gz   |  Bin 0 -> 47337 bytes
 .../results/vllm-speaker-mrv2-tuning.json.gz  |  Bin 0 -> 119982 bytes
 .../results/vllm-speaker-repeated.json.gz     |  Bin 0 -> 1092714 bytes
 .../results/waveform-repeat-diagnostic.json   |   17 +
 .../validator/bench_prompt_workers.py         |   34 +
 .../validator/bench_speaker_cpu_threads.py    |   23 +
 .../validator/diagnostic-sources.json         |   12 +
 .../validator/export_metrics.py               |    2 +-
 .../validator/fresh_pair.py                   |  134 +
 .../validator/holdout_pair.py                 |  136 +
 .../validator/plot_results.py                 |   76 +
 .../validator/quality_uncertainty.py          |   12 +
 .../validator/summarize_results.py            |   96 +-
 40 files changed, 8587 insertions(+), 30 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/speaker-mps.yaml
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/cpu-reference-parallel-hypothesis.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/fresh-start-allocation-addendum.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/fresh-start-confirmation.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/noninferiority-selection.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/speaker-mps-control.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/speaker-mps-resolved-config.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/speaker-only-resolved-config.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/speaker-runspec-redacted.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/c1-quality-repeat-check.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/concurrency-comparison.png
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/concurrency-comparison.svg
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/mps-comparison.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/prompt-workers-prototype.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/quality-c1-uncertainty.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/speaker-comparison.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/speaker-cpu-threads.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/speaker-mps-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/speaker-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/speaker-waveform-diagnostic.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-speaker-microbatch-tuning.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mps-repeated.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mps-tuning.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mrv2-tuning.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-speaker-repeated.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/waveform-repeat-diagnostic.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/bench_prompt_workers.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/bench_speaker_cpu_threads.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/diagnostic-sources.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/fresh_pair.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/holdout_pair.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/plot_results.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/quality_uncertainty.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index d2e9cbef0..2240ae8d7 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -2,7 +2,7 @@
 
 Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
 
-**Current verdict: INCONCLUSIVE.** Baselines are complete; candidate service and speech-quality qualification is in progress. Component PASS does not establish service PASS.
+**Original strict quality verdict: FAIL** for the completed speaker-only candidate. A separately authorized noninferiority evaluation on previously unused prompts is pending; it does not change the original verdict. Component PASS does not establish service PASS.
 
 ## Scope and controls
 
@@ -15,6 +15,8 @@ Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49)
 - Throughput is 25 × delivered audio seconds / measured wall time; it is an audio-frame equivalent, not video fps. The table averages three run throughputs. TTFA percentiles pool 960 requests; RTF is the mean per-request last-audio latency divided by generated duration.
 - vLLM streams audio chunks. SGLang returns a terminal waveform, so its TTFA is effectively completion latency. Do not interpret the two TTFA columns as equivalent streaming capability.
 
+The native main configurations also differ: SGLang Code2Wav uses float16, compiled DiT/HiFT, eight reference workers and a 32-entry prompt cache; this vLLM baseline uses its default FP32 CFM path and serial CPU reference preparation. These are native-engine comparisons, not an isolated backend comparison with identical numerical kernels and scheduling.
+
 ## Main-branch baselines
 
 | Engine | C | Frames/s | TTFA p50 ms | TTFA p95 ms | RTF mean |
@@ -116,3 +118,69 @@ PYTHONPATH="$PEER:$VLLM_OMNI" python "$EVIDENCE/validator/bench_speaker.py" \
 ## Interpretation limits
 
 The optimization target is high-concurrency throughput with no speech-quality regression, not a globally optimal configuration. English voice cloning does not establish multilingual, visual, full-duplex or interruption correctness. Historical reference-engine results are prior art, not measurements reproduced by this campaign. Profiling perturbed MRv2 execution, so its stack samples are diagnostic only and excluded from performance tables.
+
+## Separately authorized noninferiority holdout
+
+The original zero-regression gates are preserved. After seeing first-cohort results, the user authorized a new engineering tolerance: WER +0.20 percentage points, SIM (×100) −0.50, UTMOS −0.05. These are not published perceptual equivalence thresholds. `plan/noninferiority-holdout.json` freezes unused evaluation rows 320–639, concurrency 1/16/32, and the paired 20,000-resample prompt bootstrap. Every one-sided 95% degradation upper bound must meet its margin; missing evidence is INCONCLUSIVE. Model/profile selection uses the existing throughput cohort before opening the new holdout. No threshold adjustment or tuning is allowed after those outputs are inspected.
+
+## Completed speaker-only service result
+
+The three-repeat speaker-only run completed all 5,760 measured requests. The original quality gate is **FAIL**, even though high-concurrency throughput improved in every repeat. Run-level variation and all requested latency metrics are retained in `results/speaker-comparison.json`. C1 SIM/UTMOS decreased; C16/C32 WER increased. Repeated C1 scoring and waveform diagnostics are preserved rather than relabeling the differences as noise.
+
+| C | Frames/s | TTFA p50 ms | TTFA p95 ms | RTF mean |
+|---|---:|---:|---:|---:|
+| 1 | 190.8 | 314.0 | 350.3 | 0.133 |
+| 2 | 298.0 | 405.8 | 499.2 | 0.170 |
+| 4 | 457.0 | 611.3 | 736.3 | 0.226 |
+| 8 | 626.7 | 885.2 | 1096.9 | 0.331 |
+| 16 | 728.9 | 1180.8 | 1683.7 | 0.560 |
+| 32 | 803.4 | 1745.6 | 2421.3 | 1.008 |
+
+## Selected speaker + MPS profile
+
+All 5,760 measured requests completed. The profile was selected by the predeclared geometric mean of C16/C32 three-repeat throughput, before generating the new holdout. Its original strict speech verdict is also **FAIL**; use `results/mps-comparison.json` for that verdict and `results/noninferiority-holdout.json` for the separate new decision when available. Copy `patch/speaker-mps.yaml` beside the base deploy YAML to reproduce this optional profile.
+
+| C | Frames/s | TTFA p50 ms | TTFA p95 ms | RTF mean |
+|---|---:|---:|---:|---:|
+| 1 | 184.1 | 312.2 | 354.1 | 0.138 |
+| 2 | 323.8 | 351.7 | 423.3 | 0.157 |
+| 4 | 519.3 | 479.4 | 619.0 | 0.196 |
+| 8 | 710.5 | 697.1 | 954.1 | 0.290 |
+| 16 | 829.4 | 1042.0 | 1602.3 | 0.493 |
+| 32 | 942.3 | 1510.9 | 2712.0 | 0.858 |
+
+![Concurrency comparison](results/concurrency-comparison.png)
+
+Bands show the minimum/maximum run throughput, not confidence intervals. Quality qualification is separate. MPS improves high-concurrency throughput here but reduces C1 throughput; C32 TTFA p95 is worse than speaker-only even though throughput is higher.
+
+## Reproduce the separately frozen holdout
+
+Run `validator/holdout_pair.py --help` for explicit environment/repository paths.
+It starts baseline then candidate inside a single externally reserved GPU,
+uses `run_holdout.py --eval-offset 320 --requests 320 --repeats 1`, and saves a
+`complete` marker only after all WAVs are written. Use the selected MPS overlay
+and the model, package, scorer and source pins in this evidence tree. Do not run
+another performance client against either service concurrently.
+
+Score run1 at C1/C16/C32 for both roles with `validator/score_outputs.py`, naming
+outputs `vllm-holdout-main-c{C}.json` and
+`vllm-holdout-candidate-c{C}.json` in a common quality directory. Then run:
+
+```bash
+python "$EVIDENCE/validator/noninferiority.py" \
+  --plan "$EVIDENCE/plan/noninferiority-holdout.json" \
+  --quality-dir "$RUNS/quality" --out "$RUNS/noninferiority-holdout.json"
+```
+
+The validator checks exact frozen prompt IDs and complete scorer coverage,
+recomputes corpus WER from counts in each paired resample, and reports every
+metric's degradation, confidence upper bound, margin and verdict. All nine
+checks must pass. This inference is conditional on the generated outputs;
+it does not establish equivalence across generation seeds or replace a
+listening study. A failed upper-bound gate does not by itself prove perceptual
+inferiority.
+
+Host CPUs and the filesystem are shared with other jobs; GPU reservations are
+exclusive, but CPU affinity is not isolated. The host has two Intel Xeon
+Platinum 8480C sockets, 112 physical cores / 224 hardware threads. Results are
+scoped observations on this host, not hardware-independent performance claims.
diff --git a/evidence/minicpmo45-l20x-20261021/patch/speaker-mps.yaml b/evidence/minicpmo45-l20x-20261021/patch/speaker-mps.yaml
new file mode 100644
index 000000000..c7bcbba49
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/speaker-mps.yaml
@@ -0,0 +1,6 @@
+base_config: minicpmo_4_5_turn.yaml
+cuda_mps: true
+connectors:
+  connector_of_shared_memory:
+    extra:
+      token2wav_device_spk: true
diff --git a/evidence/minicpmo45-l20x-20261021/plan/cpu-reference-parallel-hypothesis.json b/evidence/minicpmo45-l20x-20261021/plan/cpu-reference-parallel-hypothesis.json
new file mode 100644
index 000000000..e356647c1
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/cpu-reference-parallel-hypothesis.json
@@ -0,0 +1,9 @@
+{
+  "plane": "model",
+  "hypothesis": "Parallel reference preparation on the existing CPU ONNX backend may remove serialized host work without changing speaker arithmetic. SGLang main uses reference_workers=8; direct transfer still needs target runtime lifecycle and numerical checks.",
+  "source": "sglang_omni/models/minicpm_o/components/code2wav.py submit_reference and config.py code2wav_stage at pinned SGLang baseline",
+  "first_check": "Prototype only: same normalized tuning WAVs, same model instance, same CUDA stream, explicit worker-local inference/autocast scopes; compare every returned prompt feature bitwise for serial vs parallel preparation.",
+  "numerical_gate": "All prompt tensors exactly equal on sampled references; unchanged ONNX session threads=1. No tolerance relaxation.",
+  "service_gate": "Unchanged frozen throughput and speech-quality gates if component probe warrants implementation.",
+  "scope": "No service PASS from a component prototype; do not mutate running candidate code."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/fresh-start-allocation-addendum.json b/evidence/minicpmo45-l20x-20261021/plan/fresh-start-allocation-addendum.json
new file mode 100644
index 000000000..1c70606ff
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/fresh-start-allocation-addendum.json
@@ -0,0 +1,6 @@
+{
+  "change": "Before any fresh-start measurement, switch from separate GPUs to sequential baseline/candidate on one dynamically reserved L20X.",
+  "reason": "The released GPU was acquired by another user; the fixed-GPU reservation timed out. No other workload was interrupted.",
+  "unchanged": "Model, dataset, order C1/C16/C32, 320 requests, discard run0, measure run1, scorer settings and gates.",
+  "benefit": "The sequential reservation keeps the physical GPU matched across fresh baseline/candidate."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/fresh-start-confirmation.json b/evidence/minicpmo45-l20x-20261021/plan/fresh-start-confirmation.json
new file mode 100644
index 000000000..c235493ca
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/fresh-start-confirmation.json
@@ -0,0 +1,17 @@
+{
+  "purpose": "Confirm service and speech results with matched fresh-start history; retain original steady-state results regardless of outcome.",
+  "baseline": "pinned main default turn profile",
+  "candidate": "same code, speaker-only overlay; no MPS or microbatch changes",
+  "concurrency": [
+    1,
+    16,
+    32
+  ],
+  "requests_per_cell": 320,
+  "discarded_runs": 1,
+  "measured_runs": 1,
+  "quality": "score run1 outputs at all three concurrency levels with unchanged scorers and original directional gates",
+  "hardware": "separate reserved L20X GPUs on same host",
+  "limitations": "One measured repeat per fresh-start cell; original same-GPU three-repeat comparison remains the throughput variation evidence. No server reset between concurrency cells.",
+  "motivation": "Both unchanged baseline and candidate produce nonidentical C1 WAVs across repeated identical requests; assess fresh-start reproducibility without assuming observed quality changes are caused solely by speaker arithmetic."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json b/evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json
new file mode 100644
index 000000000..4a85a65b0
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json
@@ -0,0 +1,33 @@
+{
+  "scope": "Provenance of guidance used; not an independent performance claim",
+  "records": [
+    {
+      "knowledge_scope": "strata",
+      "source_path": "src/inferrsi/data/skill_library/en/strata/sub-skills/tune-execution/SKILL.md",
+      "content_sha256": "cdf51c537e7237296d52ef6cda9f2e4c9d9ce3fc87265a369cd9eb7497c53512",
+      "lesson": "Use resolved settings, controlled one-plane experiments, repeated service measurements and explicit regressions.",
+      "application": "Separate MPS, encoder capture and microbatch controls; retest MPS after speaker extraction changes the bottleneck. No Strata speedup is imported."
+    },
+    {
+      "knowledge_scope": "vllm_omni",
+      "source_path": "src/inferrsi/data/skill_library/en/vllm-omni/sub-skills/omni-validation/SKILL.md",
+      "content_sha256": "81c2a8cbdccaa86ff560311ec9d33ba191ecc6e3121ca4e9f751f006875223c9",
+      "lesson": "Escalate native tests through accelerator parity, real speech quality and matched service performance.",
+      "application": "67 CPU regressions, real CAM++ numerical checks, repeated service results and independent speech gates. Component PASS never overrides speech FAIL."
+    },
+    {
+      "knowledge_scope": "sglang_omni",
+      "source_path": "src/inferrsi/data/skill_library/en/sglang-omni/sub-skills/sglang-omni-architecture/SKILL.md",
+      "content_sha256": "766b2d66d2056dd779abd9e492cb3af6e25899298f44964f565509f130a7cb24",
+      "lesson": "Trace concrete stages and terminal outputs at the pinned source rather than infer behavior from model name.",
+      "application": "Identify terminal waveform semantics, FP16 compiled Code2Wav and reference_workers=8; retain native scorer implementation and a separate CPU parallel preparation prototype."
+    },
+    {
+      "knowledge_scope": "minicpmo_single_gpu_engine",
+      "source_path": "src/inferrsi/data/knowledge_packs/peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json",
+      "content_sha256": "58ebe6ac09cbbb774216acd0fdaef29409e685cd7a7521501154b67b963565fa",
+      "lesson": "Preserve audio-delivery metrics, disjoint pools, request-owned state and quality-constrained transfer.",
+      "application": "Reuse pinned adapters/client/workload, test MPS and graph/batching hypotheses, and explicitly distinguish this steady-state campaign from strict cold-cache certification."
+    }
+  ]
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/noninferiority-selection.json b/evidence/minicpmo45-l20x-20261021/plan/noninferiority-selection.json
new file mode 100644
index 000000000..1ee4460ec
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/noninferiority-selection.json
@@ -0,0 +1,40 @@
+{
+  "rule": "Highest geometric mean repeated C16/C32 throughput, fixed before opening unused holdout",
+  "profiles": {
+    "vllm-speaker-repeated": {
+      "geometric_mean_c16_c32": 765.2433361169411,
+      "runs": {
+        "16": [
+          733.2183577620565,
+          724.06899063543,
+          729.4779403496699
+        ],
+        "32": [
+          805.0347719563634,
+          789.7065648065687,
+          815.3830137392569
+        ]
+      },
+      "deploy_config": "speaker-only.yaml"
+    },
+    "vllm-speaker-mps-repeated": {
+      "geometric_mean_c16_c32": 884.0191911534453,
+      "runs": {
+        "16": [
+          836.0031648846023,
+          829.4632658606373,
+          822.6216914690485
+        ],
+        "32": [
+          941.8298721767356,
+          947.6880813868139,
+          937.3149508469672
+        ]
+      },
+      "deploy_config": "speaker-mps.yaml"
+    }
+  },
+  "selected": "vllm-speaker-mps-repeated",
+  "deploy_config": "speaker-mps.yaml",
+  "quality_not_used_for_selection": true
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json b/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
new file mode 100644
index 000000000..cd3aa5f23
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
@@ -0,0 +1,47 @@
+{
+  "source": "Local launch arguments, resolved deploy configuration and server startup logs",
+  "runs": {
+    "vllm-official-repeated": {
+      "runtime": "main V1",
+      "cuda_mps": false,
+      "speaker_backend": "CPU ONNX Runtime",
+      "device_role": "same physical GPU A"
+    },
+    "vllm-speaker-repeated": {
+      "runtime": "candidate V1",
+      "cuda_mps": false,
+      "speaker_backend": "TensorRT CPU-reference graph, IEEE FP32",
+      "device_role": "same physical GPU A"
+    },
+    "vllm-speaker-mps-repeated": {
+      "runtime": "candidate V1",
+      "cuda_mps": true,
+      "speaker_backend": "TensorRT CPU-reference graph, IEEE FP32",
+      "device_role": "GPU B, same L20X SKU",
+      "mps_started_private_daemon": true
+    },
+    "vllm-fresh-main": {
+      "device_role": "GPU C, sequential fresh pair",
+      "cuda_mps": false,
+      "speaker_backend": "CPU ONNX Runtime"
+    },
+    "vllm-fresh-speaker": {
+      "device_role": "same GPU C, sequential fresh pair",
+      "cuda_mps": false,
+      "speaker_backend": "CPU-reference TensorRT IEEE FP32"
+    },
+    "vllm-holdout-main": {
+      "device_role": "GPU D, sequential fresh holdout pair",
+      "cuda_mps": false,
+      "speaker_backend": "CPU ONNX Runtime"
+    },
+    "vllm-holdout-candidate": {
+      "device_role": "same GPU D, sequential fresh holdout pair",
+      "cuda_mps": true,
+      "speaker_backend": "CPU-reference TensorRT IEEE FP32",
+      "state": "Planned next after main completes; confirm against final controller output"
+    }
+  },
+  "summary_metadata_warning": "Raw summary mps_policy=off/id_set=eval and blank source/device fields are reference-helper defaults. These runtime observations, source plans and pinned manifests are authoritative. No strict certification is inferred from those default fields.",
+  "host_limitations": "Exclusive GPU reservations, but shared host CPUs and filesystem; other workloads and separate GPU scoring may overlap. No CPU affinity isolation or causal attribution from microbench timing alone."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/speaker-mps-control.json b/evidence/minicpmo45-l20x-20261021/plan/speaker-mps-control.json
new file mode 100644
index 000000000..6d7a9946e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/speaker-mps-control.json
@@ -0,0 +1,19 @@
+{
+  "plane": "infra",
+  "hypothesis": "MPS may improve stage overlap after CPU speaker bottleneck removal; earlier main-only MPS did not improve both primary cells.",
+  "changed_setting": {
+    "cuda_mps": [
+      false,
+      true
+    ]
+  },
+  "fixed_setting": {
+    "token2wav_device_spk": true
+  },
+  "concurrency": [
+    16,
+    32
+  ],
+  "dataset": "same disjoint tuning64",
+  "gate": "Same frozen performance and speech quality gates; no promotion based on a single favorable cell."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/speaker-mps-resolved-config.json b/evidence/minicpmo45-l20x-20261021/plan/speaker-mps-resolved-config.json
new file mode 100644
index 000000000..ace656556
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/speaker-mps-resolved-config.json
@@ -0,0 +1,474 @@
+{
+  "async_chunk": true,
+  "session_mode": "turn",
+  "model_runner": "v1",
+  "active_stream_window": 0,
+  "cuda_mps": true,
+  "duplex_session": {
+    "idle_ttl_s": 300.0,
+    "disconnect_grace_s": 30.0,
+    "reaper_interval_s": 5.0,
+    "resume_replay_ttl_s": 60.0,
+    "resume_replay_max_bytes_per_session": 8388608,
+    "max_pending_input_bytes_per_session": 16777216,
+    "max_pending_turns_per_session": 4,
+    "max_pending_output_bytes_per_session": 2097152,
+    "max_pending_output_events_per_session": 512,
+    "max_sessions": 16,
+    "max_tool_calls_per_session": 4096,
+    "replica_policy": "legacy",
+    "max_sessions_per_replica": null,
+    "replica_groups": null,
+    "completed_append_cache_size": 256,
+    "server_vad_model_path": null,
+    "semantic_vad_model_path": null,
+    "history_asr_url": null,
+    "history_asr_model": null,
+    "history_asr_max_concurrency": 4,
+    "history_ms_per_token": null,
+    "history_calibration_timeout_ms": 1000,
+    "history_audio_max_bytes_per_session": 8388608,
+    "warmup_frames": 0
+  },
+  "speech_cache": {
+    "resolve_max_bytes": 4294967296,
+    "resolve_max_entries": 2048,
+    "speaker_max_bytes": 536870912
+  },
+  "connectors": {
+    "connector_of_shared_memory": {
+      "name": "SharedMemoryConnector",
+      "extra": {
+        "connector_get_sleep_s": 0.01,
+        "connector_get_max_wait_first_chunk": 3000,
+        "connector_get_max_wait": 300,
+        "codec_chunk_frames": 25,
+        "codec_left_context_frames": 3,
+        "enable_hift_graph": true,
+        "hift_graph_continuation_frames": [
+          4,
+          28
+        ],
+        "hift_graph_exact_batch_sizes": [
+          1
+        ],
+        "enable_cfm_graph": true,
+        "cfm_fused_body": true,
+        "enable_code2wav_encoder_graph": true,
+        "code2wav_encoder_graph_rows": 4,
+        "code2wav_encoder_max_graphs": 12,
+        "code2wav_encoder_capture_after": 8,
+        "max_graph_batch": 32,
+        "micro_batch_size": 4,
+        "cfm_precapture_empty_cache": true,
+        "cfm_max_graphs": 32,
+        "token2wav_device_spk": true
+      }
+    }
+  },
+  "edges": null,
+  "stages": [
+    {
+      "stage_id": 0,
+      "devices": "0",
+      "num_replicas": 1,
+      "env": null,
+      "async_chunk": null,
+      "model_runner": null,
+      "output_connectors": null,
+      "input_connectors": null,
+      "default_sampling_params": {
+        "temperature": 0.0,
+        "top_p": 1.0,
+        "top_k": -1,
+        "max_tokens": 2048,
+        "seed": 42,
+        "detokenize": true,
+        "repetition_penalty": 1.0
+      },
+      "default_pooling_params": null,
+      "subtalker_sampling_params": null,
+      "silence_ban_frames": 0,
+      "tensor_parallel_size": 1,
+      "enable_expert_parallel": null,
+      "gpu_memory_utilization": 0.55,
+      "max_num_seqs": 16,
+      "max_num_batched_tokens": 16384,
+      "max_model_len": null,
+      "attention_backend": null,
+      "moe_backend": null,
+      "linear_backend": null,
+      "enforce_eager": false,
+      "async_scheduling": null,
+      "disable_hybrid_kv_cache_manager": null,
+      "mm_processor_cache_gb": null,
+      "mamba_ssm_cache_dtype": null,
+      "compilation_config": null,
+      "profiler_config": null,
+      "skip_mm_profiling": null,
+      "enable_flashinfer_autotune": null,
+      "config_format": null,
+      "load_format": null,
+      "tokenizer_mode": null,
+      "ulysses_degree": null,
+      "ulysses_mode": null,
+      "ulysses_a2a_permute": null,
+      "ring_degree": null,
+      "allgather_degree": null,
+      "sequence_parallel_size": null,
+      "cfg_parallel_size": null,
+      "vae_patch_parallel_size": null,
+      "vae_parallel_mode": null,
+      "text_encoder_tp_size": null,
+      "use_hsdp": null,
+      "hsdp_shard_size": null,
+      "hsdp_replicate_size": null,
+      "model_class_name": null,
+      "diffusion_load_format": null,
+      "lora_path": null,
+      "lora_backend": null,
+      "lora_scale": null,
+      "diffusers_load_kwargs": null,
+      "diffusers_call_kwargs": null,
+      "diffusion_quantization_config": null,
+      "diffusion_attention_backend": null,
+      "fastvideo_vsa_topk": null,
+      "diffusion_attention_config": null,
+      "diffusion_compile_granularity": null,
+      "diffusion_compile_dynamic": null,
+      "enable_cuda_graph_decode": null,
+      "fa_deterministic": null,
+      "cache_backend": null,
+      "cache_config": null,
+      "video_output_transport": null,
+      "enable_cache_dit_summary": null,
+      "step_execution": null,
+      "vae_use_slicing": null,
+      "vae_use_tiling": null,
+      "vae_fast_path": null,
+      "vae_encode_fast_path": null,
+      "boundary_ratio": null,
+      "flow_shift": null,
+      "diffusion_kv_cache_dtype": null,
+      "diffusion_kv_cache_skip_steps": null,
+      "diffusion_kv_cache_skip_layers": null,
+      "hsdp_weight_load_strategy": null,
+      "enable_multithread_weight_load": null,
+      "enable_broadcast_weight_load": null,
+      "num_weight_load_threads": null,
+      "diffusion_offload_config": null,
+      "enable_cpu_offload": null,
+      "enable_layerwise_offload": null,
+      "enable_distributed_layerwise_offload": null,
+      "dlo_use_allgather": null,
+      "dlo_resident_layers": null,
+      "host_weight_runtime_mode": null,
+      "host_weight_runtime_root": null,
+      "dlo_host_registration_limit_gib": null,
+      "enable_diffusion_pipeline_profiler": null,
+      "max_generated_image_size": null,
+      "tts_max_instructions_length": null,
+      "engine_extras": {
+        "interleave_mm_strings": true,
+        "media_io_kwargs": {
+          "video": {
+            "fps": 1,
+            "num_frames": 128
+          }
+        },
+        "limit_mm_per_prompt": {
+          "image": 64,
+          "audio": 64,
+          "video": 1
+        }
+      }
+    },
+    {
+      "stage_id": 1,
+      "devices": "0",
+      "num_replicas": 1,
+      "env": null,
+      "async_chunk": null,
+      "model_runner": null,
+      "output_connectors": {
+        "to_stage_2": "connector_of_shared_memory"
+      },
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diff --git a/evidence/minicpmo45-l20x-20261021/plan/speaker-only-resolved-config.json b/evidence/minicpmo45-l20x-20261021/plan/speaker-only-resolved-config.json
new file mode 100644
index 000000000..3a31e44ae
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/speaker-only-resolved-config.json
@@ -0,0 +1,474 @@
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+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/speaker-runspec-redacted.json b/evidence/minicpmo45-l20x-20261021/plan/speaker-runspec-redacted.json
new file mode 100644
index 000000000..b6c0a0603
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/speaker-runspec-redacted.json
@@ -0,0 +1,56 @@
+{
+  "repo": "<VLLM_MAIN>",
+  "baseline_command": [
+    "<BENCH_PYTHON>",
+    "<EVIDENCE>/validator/run_baseline.py",
+    "--adapter",
+    "vllm-omni",
+    "--url",
+    "http://127.0.0.1:29161",
+    "--out",
+    "<NEW_OUTPUT>/vllm-official-repeated",
+    "--requests",
+    "320",
+    "--repeats",
+    "3"
+  ],
+  "candidate_command": [
+    "<BENCH_PYTHON>",
+    "<EVIDENCE>/validator/run_baseline.py",
+    "--adapter",
+    "vllm-omni",
+    "--url",
+    "http://127.0.0.1:29221",
+    "--out",
+    "<NEW_OUTPUT>/vllm-speaker-repeated",
+    "--requests",
+    "320",
+    "--repeats",
+    "3"
+  ],
+  "candidate_repo": "<VLLM_CANDIDATE>",
+  "repo_type": "vllm_omni",
+  "backend": "cuda",
+  "scenario": "audio.tts",
+  "mode": "code",
+  "validation_command": null,
+  "metric_key": "throughput_frames_s",
+  "metric_unit": "frames/s",
+  "comparison_scope": "steady_state_served_audio",
+  "direction": "maximize",
+  "repetitions": 1,
+  "min_improvement_pct": 0.0,
+  "max_minutes": 120.0,
+  "workload_id": "seedtts-en-eval320-three-repeats-six-concurrencies",
+  "model": "openbmb/MiniCPM-o-4_5",
+  "model_revision": "503e754207c94da6bb26850b4469f367c9ea3582",
+  "agent": "manual",
+  "device_ids": [
+    "6"
+  ],
+  "revision": "aa3fd1d9b7f5c7191dec11975ac0aa7c4c4a18c5",
+  "device": "NVIDIA L20X",
+  "executor": "default",
+  "snapshot_id": "speaker-steady-state-sweep",
+  "output_dir": "<ARTIFACT_ROOT>/runspec-artifacts"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/c1-quality-repeat-check.json b/evidence/minicpmo45-l20x-20261021/results/c1-quality-repeat-check.json
new file mode 100644
index 000000000..e62413dfc
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/c1-quality-repeat-check.json
@@ -0,0 +1,75 @@
+{
+  "scope": "All three existing C1 measured repeats, SIM/UTMOS. Original run1 directional gate remains unchanged.",
+  "rows": [
+    {
+      "role": "main",
+      "repeat": 1,
+      "summary": {
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+        "sim": 49.964186012744904,
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+        "wer": 0.014785328404890531,
+        "wer_counts": {
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+      "repeat": 2,
+      "summary": {
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+        "sim": 49.955288362503055,
+        "utmos": 4.188337291777134
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+    },
+    {
+      "role": "main",
+      "repeat": 3,
+      "summary": {
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+        "sim": 49.974040660262105,
+        "utmos": 4.187696244567633
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+    {
+      "role": "speaker",
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+        "wer_mean": 0.015903905122655125
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+    {
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+      "summary": {
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+        "sim": 49.93109819591045,
+        "utmos": 4.182268233597279
+      }
+    }
+  ]
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/concurrency-comparison.png b/evidence/minicpmo45-l20x-20261021/results/concurrency-comparison.png
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diff --git a/evidence/minicpmo45-l20x-20261021/results/mps-comparison.json b/evidence/minicpmo45-l20x-20261021/results/mps-comparison.json
new file mode 100644
index 000000000..0085ce29b
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/mps-comparison.json
@@ -0,0 +1,364 @@
+{
+  "verdict": "FAIL",
+  "scope": "Frozen steady-state throughput and point-estimate speech gates; no global optimum or cold-cache certification",
+  "baseline": [
+    {
+      "concurrency": 1,
+      "requests_per_repeat": [
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+      "n_failed": 0,
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+      "throughput_frames_s_runs": [
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+        194.38639468569238,
+        192.03792696219256
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+      "ttfa_p50_ms_pooled": 307.4587588198483,
+      "ttfa_p95_ms_pooled": 343.0558750871569,
+      "rtf_mean": 0.13163823357797064,
+      "mean_audio_seconds": 4.403375
+    },
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+      "concurrency": 2,
+      "requests_per_repeat": [
+        320,
+        320,
+        320
+      ],
+      "repeats": 3,
+      "n_failed": 0,
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diff --git a/evidence/minicpmo45-l20x-20261021/results/prompt-workers-prototype.json b/evidence/minicpmo45-l20x-20261021/results/prompt-workers-prototype.json
new file mode 100644
index 000000000..3bd1c4eb3
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/prompt-workers-prototype.json
@@ -0,0 +1,1975 @@
+{
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+        {
+          "id": "common_voice_en_523215-common_voice_en_523219",
+          "field": 2,
+          "equal": true,
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+        {
+          "id": "common_voice_en_523215-common_voice_en_523219",
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+          "equal": true,
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+        {
+          "id": "common_voice_en_523215-common_voice_en_523219",
+          "field": 4,
+          "equal": true,
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+        {
+          "id": "common_voice_en_28638628-common_voice_en_28638717",
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+        {
+          "id": "common_voice_en_28638628-common_voice_en_28638717",
+          "field": 1,
+          "equal": true,
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+        {
+          "id": "common_voice_en_28638628-common_voice_en_28638717",
+          "field": 2,
+          "equal": true,
+          "max_abs_error": 0.0
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+        {
+          "id": "common_voice_en_28638628-common_voice_en_28638717",
+          "field": 3,
+          "equal": true,
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+        {
+          "id": "common_voice_en_28638628-common_voice_en_28638717",
+          "field": 4,
+          "equal": true,
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+        {
+          "id": "common_voice_en_20303932-common_voice_en_20303934",
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+        {
+          "id": "common_voice_en_20303932-common_voice_en_20303934",
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+        {
+          "id": "common_voice_en_20303932-common_voice_en_20303934",
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+          "id": "common_voice_en_20303932-common_voice_en_20303934",
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+          "id": "common_voice_en_20303932-common_voice_en_20303934",
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+        {
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+          "id": "common_voice_en_19619551-common_voice_en_19619549",
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+          "id": "common_voice_en_19619551-common_voice_en_19619549",
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+        {
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+        {
+          "id": "common_voice_en_25127181-common_voice_en_25127184",
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+        {
+          "id": "common_voice_en_25127181-common_voice_en_25127184",
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+        {
+          "id": "common_voice_en_25127181-common_voice_en_25127184",
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+          "id": "common_voice_en_19636954-common_voice_en_19636955",
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+        {
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+        {
+          "id": "common_voice_en_557458-common_voice_en_557459",
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+        {
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+        {
+          "id": "common_voice_en_557458-common_voice_en_557459",
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+  "limitations": "Prototype only, no service integration; shared CUDA stream, CPU ORT threads=1, fixed tuning references. Timings may overlap the separately running ASR scorer on the reserved quality GPU."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/quality-c1-uncertainty.json b/evidence/minicpmo45-l20x-20261021/results/quality-c1-uncertainty.json
new file mode 100644
index 000000000..3ac9f4a0d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/quality-c1-uncertainty.json
@@ -0,0 +1,22 @@
+{
+  "scope": "Descriptive paired bootstrap over prompts; no noninferiority margin, no gate change and no proof of equivalence",
+  "n": 320,
+  "replicates": 10000,
+  "seed": 20261021,
+  "metrics": {
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+    }
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-comparison.json b/evidence/minicpmo45-l20x-20261021/results/speaker-comparison.json
new file mode 100644
index 000000000..d5d9aa85c
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-comparison.json
@@ -0,0 +1,364 @@
+{
+  "verdict": "FAIL",
+  "scope": "Frozen steady-state throughput and point-estimate speech gates; no global optimum or cold-cache certification",
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+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-cpu-threads.json b/evidence/minicpmo45-l20x-20261021/results/speaker-cpu-threads.json
new file mode 100644
index 000000000..5f3bac2ea
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-cpu-threads.json
@@ -0,0 +1,150 @@
+{
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+  "spinning": false,
+  "rows": [
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+      "bitwise_equal": [
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diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-mps-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/speaker-mps-quality.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/speaker-waveform-diagnostic.json b/evidence/minicpmo45-l20x-20261021/results/speaker-waveform-diagnostic.json
new file mode 100644
index 000000000..510479416
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/speaker-waveform-diagnostic.json
@@ -0,0 +1,453 @@
+{
+  "scope": "Matched C1 tuning waveforms only; not perceptual or service qualification",
+  "rows": [
+    {
+      "id": "common_voice_en_10119832-common_voice_en_10119840",
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+    },
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+      "same_shape": true,
+      "mae": 0.000892959360498935,
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+    {
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+    {
+      "id": "common_voice_en_19967495-common_voice_en_19967497",
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+      "mae": 0.01847546361386776,
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+      "waveform_cosine": 0.8680605292320251
+    },
+    {
+      "id": "common_voice_en_20065698-common_voice_en_20065702",
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+      "mae": 0.019156811758875847,
+      "max_abs_error": 0.5625,
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+    },
+    {
+      "id": "common_voice_en_20236234-common_voice_en_20236233",
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+    {
+      "id": "common_voice_en_20303932-common_voice_en_20303934",
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+    {
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+    {
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+      "mae": 0.0006419672281481326,
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+    {
+      "id": "common_voice_en_20933101-common_voice_en_20933102",
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+      "mae": 0.0009604504448361695,
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+    },
+    {
+      "id": "common_voice_en_21291499-common_voice_en_21291501",
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+    {
+      "id": "common_voice_en_21555942-common_voice_en_21555950",
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+      "mae": 0.001322687603533268,
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+    {
+      "id": "common_voice_en_27172977-common_voice_en_27172980",
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+      "mae": 0.018071897327899933,
+      "max_abs_error": 0.638336181640625,
+      "waveform_cosine": 0.8759009838104248
+    },
+    {
+      "id": "common_voice_en_275174-common_voice_en_275175",
+      "same_shape": true,
+      "mae": 0.006645959336310625,
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+    {
+      "id": "common_voice_en_27573778-common_voice_en_27573779",
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+    {
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+    {
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+      "mae": 0.021857688203454018,
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+      "waveform_cosine": 0.9997866749763489
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+      "mae": 0.0005532478680834174,
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+      "waveform_cosine": 0.9999634027481079
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+      "waveform_cosine": 0.9984766840934753
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+    {
+      "id": "common_voice_en_35734335-common_voice_en_35734342",
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+      "mae": 0.015112807974219322,
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+      "waveform_cosine": 0.9668982028961182
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+    {
+      "id": "common_voice_en_36558935-common_voice_en_36558933",
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+      "mae": 0.0014762564096599817,
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+      "waveform_cosine": 0.9975500702857971
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+    {
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+      "mae": 0.0008115392411127687,
+      "max_abs_error": 0.086212158203125,
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+    {
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+      "same_shape": true,
+      "mae": 0.01538935862481594,
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+      "waveform_cosine": 0.731821596622467
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+      "max_abs_error": 0.036407470703125,
+      "waveform_cosine": 0.9926801919937134
+    },
+    {
+      "id": "common_voice_en_557458-common_voice_en_557459",
+      "same_shape": true,
+      "mae": 0.00011035201168851927,
+      "max_abs_error": 0.0035400390625,
+      "waveform_cosine": 0.9999719262123108
+    },
+    {
+      "id": "common_voice_en_605765-common_voice_en_605766",
+      "same_shape": true,
+      "mae": 0.00027561080059967935,
+      "max_abs_error": 0.010101318359375,
+      "waveform_cosine": 0.9999827742576599
+    },
+    {
+      "id": "common_voice_en_75329-common_voice_en_75332",
+      "same_shape": true,
+      "mae": 0.005153913050889969,
+      "max_abs_error": 0.417236328125,
+      "waveform_cosine": 0.8789844512939453
+    },
+    {
+      "id": "common_voice_en_9559-common_voice_en_9560",
+      "same_shape": true,
+      "mae": 0.0068326303735375404,
+      "max_abs_error": 0.184478759765625,
+      "waveform_cosine": 0.9340490102767944
+    }
+  ]
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/status.json b/evidence/minicpmo45-l20x-20261021/results/status.json
index 546be683d..b27d24d5f 100644
--- a/evidence/minicpmo45-l20x-20261021/results/status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/status.json
@@ -4,17 +4,17 @@
   "candidate_revision": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
   "candidate_microbench": "PASS within frozen embedding gate; CPU-compatible FP32 TensorRT",
   "candidate_unit_tests": {
-    "passed": 60,
-    "warnings": 16
+    "passed": 67
   },
-  "optimization_submitted": false,
+  "optimization_submitted": true,
   "pending": [
-    "candidate repeated benchmark",
-    "candidate speech quality",
-    "fresh-start high-concurrency confirmation",
-    "combined-control selection"
+    "speaker+MPS repeated benchmark and quality",
+    "fresh-start confirmation",
+    "separately authorized unused-holdout noninferiority"
   ],
   "candidate_pull_request": "https://github.com/vllm-project/vllm-omni/pull/9188",
   "candidate_cpu_tests_passed": 67,
-  "candidate_tuning": "C16/C32 gains observed; held-out repeated service and generated speech quality pending"
+  "candidate_tuning": "C16/C32 gains observed; held-out repeated service and generated speech quality pending",
+  "original_strict_speaker_verdict": "FAIL",
+  "knowledge_pull_request": "https://github.com/InferMatrixLab/InferRSI/pull/51"
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/tuning-table.json b/evidence/minicpmo45-l20x-20261021/results/tuning-table.json
index 313e7b6fe..89d962d8e 100644
--- a/evidence/minicpmo45-l20x-20261021/results/tuning-table.json
+++ b/evidence/minicpmo45-l20x-20261021/results/tuning-table.json
@@ -1418,5 +1418,451 @@
       "inter_chunk_gap_p95_s": 0.28774972371757007,
       "inter_chunk_gap_max_s": 0.5202315701171756
     }
+  ],
+  "vllm-speaker-microbatch-tuning": [
+    {
+      "label": "run1",
+      "concurrency": 16,
+      "measured": true,
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mps-repeated.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mps-repeated.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mps-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mps-tuning.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mrv2-tuning.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-mrv2-tuning.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-repeated.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-speaker-repeated.json.gz
new file mode 100644
index 0000000000000000000000000000000000000000..5eb43d4eed0eb792af6be0bf840c8dbf75a131a2
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diff --git a/evidence/minicpmo45-l20x-20261021/results/waveform-repeat-diagnostic.json b/evidence/minicpmo45-l20x-20261021/results/waveform-repeat-diagnostic.json
new file mode 100644
index 000000000..41aee3bd6
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/waveform-repeat-diagnostic.json
@@ -0,0 +1,17 @@
+{
+  "main_repeat": {
+    "n_same_shape": 320,
+    "mean_mae": 0.0010952550022011564,
+    "mean_cosine": 0.9983432989567518
+  },
+  "speaker_repeat": {
+    "n_same_shape": 320,
+    "mean_mae": 0.001072906265835627,
+    "mean_cosine": 0.9985167846083641
+  },
+  "main_to_speaker": {
+    "n_same_shape": 320,
+    "mean_mae": 0.015628981023564848,
+    "mean_cosine": 0.8702871369197964
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/bench_prompt_workers.py b/evidence/minicpmo45-l20x-20261021/validator/bench_prompt_workers.py
new file mode 100644
index 000000000..ea950f7a0
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/bench_prompt_workers.py
@@ -0,0 +1,34 @@
+"""Prototype: serial vs parallel CPU-reference prompt preparation."""
+import argparse,json,time,statistics
+from pathlib import Path
+from concurrent.futures import ThreadPoolExecutor
+import torch,numpy as np,soundfile as sf
+from bench.workload import load_seed_tts_rows,make_id_sets
+from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_code2wav import _normalize_reference
+from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_token2wav import MiniCPMO45Token2wav
+p=argparse.ArgumentParser();p.add_argument('--model',required=True);p.add_argument('--out',required=True);p.add_argument('--scratch',required=True);a=p.parse_args()
+torch.set_num_threads(1);torch.manual_seed(0)
+model=MiniCPMO45Token2wav(str(Path(a.model)/'assets/token2wav'),device='cuda:0',drop_upstream_chunk_att_buffers=True)
+_ = model._core.spk_model
+rows=load_seed_tts_rows();ids=make_id_sets(rows).tuning_pool[:16];byid={r.row_id:r for r in rows};paths=[];scratch=Path(a.scratch);scratch.mkdir(exist_ok=True)
+for rid in ids:
+ audio,sr=sf.read(byid[rid].ref_wav_path,dtype='float32',always_2d=True);audio,sr=_normalize_reference(audio.T,sr);path=scratch/f'{rid}.wav';sf.write(path,audio.numpy(),sr,subtype='PCM_16');paths.append(str(path))
+stream=torch.cuda.current_stream()
+def prepare(path):
+ with torch.inference_mode(),torch.autocast('cuda',enabled=False),torch.cuda.stream(stream):return model._prepare_prompt(path)
+def run(workers):
+ if workers==1:outputs=[prepare(path) for path in paths]
+ else:
+  with ThreadPoolExecutor(max_workers=workers) as pool:outputs=list(pool.map(prepare,paths))
+ torch.cuda.synchronize();return outputs
+reference=run(1);results=[]
+for workers in [1,2,4,8]:
+ outputs=run(workers);checks=[]
+ for rid,b,c in zip(ids,reference,outputs):
+  for index,(x,y) in enumerate(zip(b,c)):
+   if isinstance(x,torch.Tensor):checks.append({'id':rid,'field':index,'equal':torch.equal(x,y),'max_abs_error':float((x.float()-y.float()).abs().max())})
+ samples=[]
+ for _ in range(3):
+  torch.cuda.synchronize();start=time.perf_counter();run(workers);samples.append((time.perf_counter()-start)*1000)
+ result={'workers':workers,'all_equal':all(x['equal'] for x in checks),'checks':checks,'median_ms_per_16_references':statistics.median(samples),'samples_ms':samples};results.append(result);print(workers,result['all_equal'],result['median_ms_per_16_references'],flush=True)
+Path(a.out).write_text(json.dumps({'scope':'Component prototype only; no lifecycle integration or service qualification','reference_count':len(paths),'results':results},indent=2)+'\n')
diff --git a/evidence/minicpmo45-l20x-20261021/validator/bench_speaker_cpu_threads.py b/evidence/minicpmo45-l20x-20261021/validator/bench_speaker_cpu_threads.py
new file mode 100644
index 000000000..56bd24a64
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/bench_speaker_cpu_threads.py
@@ -0,0 +1,23 @@
+"""CPU-only CAM++ thread-count diagnostic; no service claim."""
+import argparse,json,time,statistics
+from pathlib import Path
+import numpy as np
+import onnxruntime as ort
+p=argparse.ArgumentParser();p.add_argument('--model',required=True);p.add_argument('--out',required=True);a=p.parse_args()
+asset=str(Path(a.model)/'assets/token2wav/campplus.onnx')
+rng=np.random.default_rng(42);inputs=[rng.standard_normal((1,t,80),dtype=np.float32) for t in [97,200,598]]
+rows=[];references=None
+for threads in [1,2,4,8]:
+ o=ort.SessionOptions();o.intra_op_num_threads=threads;o.graph_optimization_level=ort.GraphOptimizationLevel.ORT_ENABLE_ALL
+ o.add_session_config_entry('session.intra_op.allow_spinning','0')
+ s=ort.InferenceSession(asset,sess_options=o,providers=['CPUExecutionProvider']);name=s.get_inputs()[0].name
+ outputs=[s.run(None,{name:x})[0] for x in inputs]
+ if references is None:references=outputs
+ for _ in range(5):s.run(None,{name:inputs[-1]})
+ times=[]
+ for _ in range(20):
+  start=time.perf_counter();s.run(None,{name:inputs[-1]});times.append((time.perf_counter()-start)*1000)
+ rows.append({'threads':threads,'bitwise_equal':[bool(np.array_equal(x,y)) for x,y in zip(outputs,references)],'max_abs_error':[float(np.max(np.abs(x-y))) for x,y in zip(outputs,references)],'median_ms':statistics.median(times),'samples_ms':times})
+ print(rows[-1]['threads'],rows[-1]['bitwise_equal'],rows[-1]['median_ms'],flush=True)
+ del s
+Path(a.out).write_text(json.dumps({'scope':'Synthetic CPU inputs, isolated diagnostic only; not service or speech quality','spinning':False,'rows':rows},indent=2)+'\n')
diff --git a/evidence/minicpmo45-l20x-20261021/validator/diagnostic-sources.json b/evidence/minicpmo45-l20x-20261021/validator/diagnostic-sources.json
new file mode 100644
index 000000000..d7226256e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/diagnostic-sources.json
@@ -0,0 +1,12 @@
+{
+  "speaker_trt_ieee.py": {
+    "source_repository": "https://github.com/vllm-project/vllm-omni",
+    "source_revision": "aa3fd1d9b7f5c7191dec11975ac0aa7c4c4a18c5",
+    "source_path": "vllm_omni/model_executor/models/cosyvoice3/speaker_embedding_trt.py",
+    "source_sha256": "a97251c3207adfb6c115e0c6b0e3e6f6aab1d16d6c7a15bd07bb559bd6691ae3",
+    "derived_sha256": "a9a35e34ba01ed7c70aad36c3d4a5a6801821fd04a081c0fdaf28928d94a088e",
+    "license": "Apache-2.0; source header retained",
+    "patch": "--- baseline\n+++ historical-ieee-diagnostic\n@@ -57,6 +57,7 @@\n             raise ValueError(f\"Failed to parse {onnx_path}: {errs}\")\n \n     config = builder.create_builder_config()\n+    config.clear_flag(trt.BuilderFlag.TF32)\n     config.set_memory_pool_limit(trt.MemoryPoolType.WORKSPACE, 1 << 31)  # 2 GiB\n \n     input_name = network.get_input(0).name\n",
+    "scope": "Historical isolated precision-only rejection; final CPU-reference backend imports candidate code directly."
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/export_metrics.py b/evidence/minicpmo45-l20x-20261021/validator/export_metrics.py
index 2f9caf5a6..d83faaf7a 100644
--- a/evidence/minicpmo45-l20x-20261021/validator/export_metrics.py
+++ b/evidence/minicpmo45-l20x-20261021/validator/export_metrics.py
@@ -20,7 +20,7 @@ def clean(x):
  cells.append({'cell':str(d.relative_to(a.input)),'summary':summary,'requests':records,'artifact_hashes':files,'wav_hashes':wavs})
 a.output.parent.mkdir(parents=True,exist_ok=True)
 plan=json.loads((a.input/'plan.json').read_text())
-source_plan={k:plan[k] for k in ('adapter','concurrency','requests','repeats','id_set','cache_policy','qualification','ids') if k in plan}
+source_plan={k:plan[k] for k in ('eval_offset','adapter','concurrency','requests','repeats','id_set','cache_policy','qualification','ids') if k in plan}
 source_plan.setdefault('id_set','eval')
 payload=json.dumps(clean({'qualification':'exploratory repeated steady state; no restart between cells','source_plan':source_plan,'metadata_notes':'Summary fields such as id_set, revision and GPU retain reference-helper defaults. The source_plan and campaign manifests are authoritative; tuning selection is not inferred from summary.id_set.','cells':cells}),indent=2,allow_nan=False)+'\n'
 if a.output.suffix == '.gz':
diff --git a/evidence/minicpmo45-l20x-20261021/validator/fresh_pair.py b/evidence/minicpmo45-l20x-20261021/validator/fresh_pair.py
new file mode 100644
index 000000000..c770ec17a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/fresh_pair.py
@@ -0,0 +1,134 @@
+"""Run sequential fresh-start controls inside one external GPU reservation.
+
+Requires Linux process groups and compatible, separately installed environments.
+Raw server logs remain in the selected local output directory.
+"""
+
+import argparse
+import os
+import signal
+import subprocess
+import time
+import urllib.request
+from pathlib import Path
+
+
+def _terminate(signum, frame):
+    raise SystemExit(128 + signum)
+
+
+def main():
+    signal.signal(signal.SIGTERM, _terminate)
+    parser = argparse.ArgumentParser(description=__doc__)
+    for name in (
+        "model",
+        "main-repo",
+        "candidate-repo",
+        "main-python",
+        "candidate-python",
+        "client-python",
+        "peer-repo",
+        "dataset",
+        "candidate-deploy",
+        "out",
+    ):
+        parser.add_argument(f"--{name}", type=Path, required=True)
+    parser.add_argument("--base-port", type=int, default=29271)
+    args = parser.parse_args()
+    args.out.mkdir(parents=True, exist_ok=True)
+    specs = [
+        (
+            "main",
+            args.main_repo,
+            args.main_python,
+            args.main_repo / "vllm_omni/deploy/minicpmo_4_5_turn.yaml",
+        ),
+        ("speaker", args.candidate_repo, args.candidate_python, args.candidate_deploy),
+    ]
+    for index, (role, repo, python, deploy) in enumerate(specs):
+        port = args.base_port + index
+        env = os.environ | {"PYTHONPATH": str(repo.resolve()), "PYTHONUNBUFFERED": "1"}
+        command = [
+            str(python),
+            "-m",
+            "vllm_omni.entrypoints.cli.main",
+            "serve",
+            str(args.model),
+            "--omni",
+            "--served-model-name",
+            "openbmb/MiniCPM-o-4_5",
+            "--host",
+            "127.0.0.1",
+            "--port",
+            str(port),
+            "--deploy-config",
+            str(deploy),
+            "--trust-remote-code",
+            "--init-timeout",
+            "1800",
+            "--stage-init-timeout",
+            "1800",
+        ]
+        with (args.out / f"{role}-server.log").open("w") as server_log:
+            server = subprocess.Popen(
+                command,
+                env=env,
+                stdout=server_log,
+                stderr=subprocess.STDOUT,
+                start_new_session=True,
+            )
+            try:
+                deadline = time.monotonic() + 1800
+                while True:
+                    if server.poll() is not None:
+                        raise RuntimeError(f"{role} server exited before readiness")
+                    if time.monotonic() > deadline:
+                        raise TimeoutError(f"{role} startup exceeded 1800 seconds")
+                    try:
+                        with urllib.request.urlopen(f"http://127.0.0.1:{port}/health", timeout=2):
+                            break
+                    except (OSError, TimeoutError):
+                        time.sleep(3)
+                client_env = os.environ | {
+                    "PYTHONPATH": str(args.peer_repo.resolve()),
+                    "SEED_TTS_ROOT": str(args.dataset.resolve()),
+                }
+                output = args.out / role
+                with (args.out / f"{role}-benchmark.log").open("w") as benchmark_log:
+                    subprocess.run(
+                        [
+                            str(args.client_python),
+                            str(Path(__file__).with_name("run_baseline.py")),
+                            "--adapter",
+                            "vllm-omni",
+                            "--url",
+                            f"http://127.0.0.1:{port}",
+                            "--out",
+                            str(output),
+                            "--requests",
+                            "320",
+                            "--repeats",
+                            "1",
+                            "--concurrency",
+                            "1",
+                            "16",
+                            "32",
+                        ],
+                        env=client_env,
+                        stdout=benchmark_log,
+                        stderr=subprocess.STDOUT,
+                        check=True,
+                    )
+                (output / "complete").write_text("All requested runs saved successfully.\n")
+            finally:
+                if server.poll() is None:
+                    os.killpg(server.pid, signal.SIGTERM)
+                    try:
+                        server.wait(timeout=120)
+                    except subprocess.TimeoutExpired:
+                        os.killpg(server.pid, signal.SIGKILL)
+                        server.wait()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/holdout_pair.py b/evidence/minicpmo45-l20x-20261021/validator/holdout_pair.py
new file mode 100644
index 000000000..776ed0986
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/holdout_pair.py
@@ -0,0 +1,136 @@
+"""Run sequential unused-holdout comparisons inside one external GPU reservation.
+
+Requires Linux process groups and compatible, separately installed environments.
+Raw server logs remain in the selected local output directory.
+"""
+
+import argparse
+import os
+import signal
+import subprocess
+import time
+import urllib.request
+from pathlib import Path
+
+
+def _terminate(signum, frame):
+    raise SystemExit(128 + signum)
+
+
+def main():
+    signal.signal(signal.SIGTERM, _terminate)
+    parser = argparse.ArgumentParser(description=__doc__)
+    for name in (
+        "model",
+        "main-repo",
+        "candidate-repo",
+        "main-python",
+        "candidate-python",
+        "client-python",
+        "peer-repo",
+        "dataset",
+        "candidate-deploy",
+        "out",
+    ):
+        parser.add_argument(f"--{name}", type=Path, required=True)
+    parser.add_argument("--base-port", type=int, default=29271)
+    args = parser.parse_args()
+    args.out.mkdir(parents=True, exist_ok=True)
+    specs = [
+        (
+            "main",
+            args.main_repo,
+            args.main_python,
+            args.main_repo / "vllm_omni/deploy/minicpmo_4_5_turn.yaml",
+        ),
+        ("candidate", args.candidate_repo, args.candidate_python, args.candidate_deploy),
+    ]
+    for index, (role, repo, python, deploy) in enumerate(specs):
+        port = args.base_port + index
+        env = os.environ | {"PYTHONPATH": str(repo.resolve()), "PYTHONUNBUFFERED": "1"}
+        command = [
+            str(python),
+            "-m",
+            "vllm_omni.entrypoints.cli.main",
+            "serve",
+            str(args.model),
+            "--omni",
+            "--served-model-name",
+            "openbmb/MiniCPM-o-4_5",
+            "--host",
+            "127.0.0.1",
+            "--port",
+            str(port),
+            "--deploy-config",
+            str(deploy),
+            "--trust-remote-code",
+            "--init-timeout",
+            "1800",
+            "--stage-init-timeout",
+            "1800",
+        ]
+        with (args.out / f"{role}-server.log").open("w") as server_log:
+            server = subprocess.Popen(
+                command,
+                env=env,
+                stdout=server_log,
+                stderr=subprocess.STDOUT,
+                start_new_session=True,
+            )
+            try:
+                deadline = time.monotonic() + 1800
+                while True:
+                    if server.poll() is not None:
+                        raise RuntimeError(f"{role} server exited before readiness")
+                    if time.monotonic() > deadline:
+                        raise TimeoutError(f"{role} startup exceeded 1800 seconds")
+                    try:
+                        with urllib.request.urlopen(f"http://127.0.0.1:{port}/health", timeout=2):
+                            break
+                    except (OSError, TimeoutError):
+                        time.sleep(3)
+                client_env = os.environ | {
+                    "PYTHONPATH": str(args.peer_repo.resolve()),
+                    "SEED_TTS_ROOT": str(args.dataset.resolve()),
+                }
+                output = args.out / role
+                with (args.out / f"{role}-benchmark.log").open("w") as benchmark_log:
+                    subprocess.run(
+                        [
+                            str(args.client_python),
+                            str(Path(__file__).with_name("run_holdout.py")),
+                            "--adapter",
+                            "vllm-omni",
+                            "--url",
+                            f"http://127.0.0.1:{port}",
+                            "--out",
+                            str(output),
+                            "--eval-offset",
+                            "320",
+                            "--requests",
+                            "320",
+                            "--repeats",
+                            "1",
+                            "--concurrency",
+                            "1",
+                            "16",
+                            "32",
+                        ],
+                        env=client_env,
+                        stdout=benchmark_log,
+                        stderr=subprocess.STDOUT,
+                        check=True,
+                    )
+                (output / "complete").write_text("All requested runs saved successfully.\n")
+            finally:
+                if server.poll() is None:
+                    os.killpg(server.pid, signal.SIGTERM)
+                    try:
+                        server.wait(timeout=120)
+                    except subprocess.TimeoutExpired:
+                        os.killpg(server.pid, signal.SIGKILL)
+                        server.wait()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/plot_results.py b/evidence/minicpmo45-l20x-20261021/validator/plot_results.py
new file mode 100644
index 000000000..44074a221
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/plot_results.py
@@ -0,0 +1,76 @@
+"""Plot saved aggregate metrics; ranges are observed repeats, not confidence intervals."""
+
+import argparse
+import json
+from pathlib import Path
+
+import matplotlib
+
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--baselines", type=Path, required=True)
+    parser.add_argument("--speaker", type=Path, required=True)
+    parser.add_argument("--mps", type=Path, required=True)
+    parser.add_argument("--out", type=Path, required=True)
+    args = parser.parse_args()
+    baseline = json.loads(args.baselines.read_text())["rows"]
+    series = [
+        ("vLLM main", [row for row in baseline if row["engine"] == "vllm"], "#335c9d"),
+        (
+            "SGLang main (terminal audio)",
+            [row for row in baseline if row["engine"] == "sglang"],
+            "#d98222",
+        ),
+        ("vLLM speaker candidate", json.loads(args.speaker.read_text())["candidate"], "#308664"),
+        ("vLLM speaker + MPS candidate", json.loads(args.mps.read_text())["candidate"], "#8c5aa8"),
+    ]
+    panels = [
+        ("throughput_frames_s_mean", "Throughput (audio frames/s)"),
+        ("ttfa_p50_ms_pooled", "TTFA p50 (ms)"),
+        ("ttfa_p95_ms_pooled", "TTFA p95 (ms)"),
+        ("rtf_mean", "RTF (mean)"),
+    ]
+    fig, axes = plt.subplots(2, 2, figsize=(11, 7))
+    for ax, (key, title) in zip(axes.flat, panels):
+        for label, rows, color in series:
+            rows = sorted(rows, key=lambda row: row["concurrency"])
+            assert len(rows) == 6, f"Incomplete series: {label}"
+            x = [row["concurrency"] for row in rows]
+            ax.plot(x, [row[key] for row in rows], marker="o", color=color, label=label)
+            if key == "throughput_frames_s_mean":
+                ax.fill_between(
+                    x,
+                    [min(row["throughput_frames_s_runs"]) for row in rows],
+                    [max(row["throughput_frames_s_runs"]) for row in rows],
+                    color=color,
+                    alpha=0.12,
+                )
+        ax.set_xscale("log", base=2)
+        ax.set_xticks([1, 2, 4, 8, 16, 32], labels=[1, 2, 4, 8, 16, 32])
+        ax.set_xlabel("Concurrency")
+        ax.set_title(title)
+        ax.grid(alpha=0.2)
+    handles, labels = axes[0, 0].get_legend_handles_labels()
+    fig.legend(handles, labels, loc="lower center", ncol=2, bbox_to_anchor=(0.5, 0.04))
+    fig.suptitle("MiniCPM-o 4.5 · one L20X · Seed-TTS English · steady state")
+    fig.text(
+        0.5,
+        0.015,
+        "25 audio frames/s; 3 × 320 measured requests/cell. "
+        "SGLang TTFA is terminal-waveform latency. Quality verdicts are separate.",
+        ha="center",
+        fontsize=8,
+    )
+    fig.tight_layout(rect=(0, 0.12, 1, 0.95))
+    args.out.parent.mkdir(parents=True, exist_ok=True)
+    fig.savefig(args.out.with_suffix(".png"), dpi=160)
+    fig.savefig(args.out.with_suffix(".svg"))
+    plt.close(fig)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/quality_uncertainty.py b/evidence/minicpmo45-l20x-20261021/validator/quality_uncertainty.py
new file mode 100644
index 000000000..121820d9f
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/quality_uncertainty.py
@@ -0,0 +1,12 @@
+"""Paired descriptive bootstrap; does not alter the frozen directional gates."""
+import argparse,json
+from pathlib import Path
+import numpy as np
+p=argparse.ArgumentParser();p.add_argument('--baseline',type=Path,required=True);p.add_argument('--candidate',type=Path,required=True);p.add_argument('--out',type=Path,required=True);a=p.parse_args()
+b=json.loads(a.baseline.read_text())['rows'];c=json.loads(a.candidate.read_text())['rows'];assert set(b)==set(c)
+ids=sorted(b);rng=np.random.default_rng(20261021);indices=rng.integers(0,len(ids),size=(10000,len(ids)))
+out={'scope':'Descriptive paired bootstrap over prompts; no noninferiority margin, no gate change and no proof of equivalence','n':len(ids),'replicates':10000,'seed':20261021,'metrics':{}}
+for metric in ('sim','utmos'):
+ delta=np.array([c[i][metric]-b[i][metric] for i in ids]);draws=delta[indices].mean(axis=1)
+ out['metrics'][metric]={'candidate_minus_baseline':float(delta.mean()),'percentile_95_ci':[float(x) for x in np.percentile(draws,[2.5,97.5])]}
+a.out.write_text(json.dumps(out,indent=2)+'\n');print(json.dumps(out))
diff --git a/evidence/minicpmo45-l20x-20261021/validator/summarize_results.py b/evidence/minicpmo45-l20x-20261021/validator/summarize_results.py
index b541bf426..81e3f78d9 100644
--- a/evidence/minicpmo45-l20x-20261021/validator/summarize_results.py
+++ b/evidence/minicpmo45-l20x-20261021/validator/summarize_results.py
@@ -1,4 +1,5 @@
 """Aggregate saved runs and apply the campaign's frozen directional gates."""
+
 import argparse
 import json
 import statistics
@@ -16,22 +17,30 @@ def aggregate(root):
             if not (folder / "summary.json").exists():
                 continue
             summaries.append(json.loads((folder / "summary.json").read_text()))
-            requests.extend(json.loads(line) for line in (folder / "requests.jsonl").read_text().splitlines())
+            requests.extend(
+                json.loads(line) for line in (folder / "requests.jsonl").read_text().splitlines()
+            )
         if not summaries:
             continue
         rates = [row["throughput_frames_s"] for row in summaries]
-        rows.append({
-            "concurrency": concurrency,
-            "requests_per_repeat": [row["n_requests"] for row in summaries],
-            "repeats": len(summaries),
-            "n_failed": sum(row["n_failed"] for row in summaries),
-            "throughput_frames_s_mean": statistics.mean(rates),
-            "throughput_frames_s_runs": rates,
-            "ttfa_p50_ms_pooled": float(np.percentile([row["ttfa_s"] for row in requests], 50) * 1000),
-            "ttfa_p95_ms_pooled": float(np.percentile([row["ttfa_s"] for row in requests], 95) * 1000),
-            "rtf_mean": statistics.mean(row["rtf"] for row in requests),
-            "mean_audio_seconds": statistics.mean(row["duration_s"] for row in requests),
-        })
+        rows.append(
+            {
+                "concurrency": concurrency,
+                "requests_per_repeat": [row["n_requests"] for row in summaries],
+                "repeats": len(summaries),
+                "n_failed": sum(row["n_failed"] for row in summaries),
+                "throughput_frames_s_mean": statistics.mean(rates),
+                "throughput_frames_s_runs": rates,
+                "ttfa_p50_ms_pooled": float(
+                    np.percentile([row["ttfa_s"] for row in requests], 50) * 1000
+                ),
+                "ttfa_p95_ms_pooled": float(
+                    np.percentile([row["ttfa_s"] for row in requests], 95) * 1000
+                ),
+                "rtf_mean": statistics.mean(row["rtf"] for row in requests),
+                "mean_audio_seconds": statistics.mean(row["duration_s"] for row in requests),
+            }
+        )
     return rows
 
 
@@ -45,32 +54,79 @@ def main():
     parser.add_argument("--out", type=Path, required=True)
     args = parser.parse_args()
     baseline, candidate = aggregate(args.baseline), aggregate(args.candidate)
-    complete = all(len(rows) == 6 and all(row["repeats"] == 3 and row["requests_per_repeat"] == [320] * 3 for row in rows) for rows in (baseline, candidate))
+    complete = all(
+        len(rows) == 6
+        and all(row["repeats"] == 3 and row["requests_per_repeat"] == [320] * 3 for row in rows)
+        for rows in (baseline, candidate)
+    )
     performance = []
     for concurrency in (16, 32):
         b = next((row for row in baseline if row["concurrency"] == concurrency), None)
         c = next((row for row in candidate if row["concurrency"] == concurrency), None)
         if b and c:
-            performance.append({"concurrency": concurrency, "gain_ratio": c["throughput_frames_s_mean"] / b["throughput_frames_s_mean"], "all_candidate_runs_exceed_all_baseline_runs": min(c["throughput_frames_s_runs"]) > max(b["throughput_frames_s_runs"])})
+            performance.append(
+                {
+                    "concurrency": concurrency,
+                    "gain_ratio": c["throughput_frames_s_mean"] / b["throughput_frames_s_mean"],
+                    "all_candidate_runs_exceed_all_baseline_runs": min(
+                        c["throughput_frames_s_runs"]
+                    )
+                    > max(b["throughput_frames_s_runs"]),
+                }
+            )
     quality = []
     for concurrency in (1, 16, 32):
-        paths = [args.quality_dir / f"{prefix}-c{concurrency}.json" for prefix in (args.baseline_quality_prefix, args.candidate_quality_prefix)]
+        paths = [
+            args.quality_dir / f"{prefix}-c{concurrency}.json"
+            for prefix in (args.baseline_quality_prefix, args.candidate_quality_prefix)
+        ]
         if not all(path.exists() for path in paths):
             continue
         b, c = [json.loads(path.read_text()) for path in paths]
         if not all(set(doc["tasks"]) == {"wer", "sim", "utmos"} for doc in (b, c)):
             continue
         b, c = b["summary"], c["summary"]
-        quality.append({"concurrency": concurrency, "baseline": b, "candidate": c, "gates": {"wer_nonincrease": c["wer"] <= b["wer"], "sim_nondecrease": c["sim"] >= b["sim"], "utmos_nondecrease": c["utmos"] >= b["utmos"]}})
+        quality.append(
+            {
+                "concurrency": concurrency,
+                "baseline": b,
+                "candidate": c,
+                "gates": {
+                    "wer_nonincrease": c["wer"] <= b["wer"],
+                    "sim_nondecrease": c["sim"] >= b["sim"],
+                    "utmos_nondecrease": c["utmos"] >= b["utmos"],
+                },
+            }
+        )
     if not complete or len(quality) != 3:
         verdict = "INCONCLUSIVE"
-    elif any(row["n_failed"] for row in baseline + candidate) or not all(all(row["gates"].values()) for row in quality):
+    elif any(row["n_failed"] for row in baseline + candidate) or not all(
+        all(row["gates"].values()) for row in quality
+    ):
         verdict = "FAIL"
-    elif len(performance) != 2 or not all(row["all_candidate_runs_exceed_all_baseline_runs"] for row in performance):
+    elif len(performance) != 2 or not all(
+        row["all_candidate_runs_exceed_all_baseline_runs"] for row in performance
+    ):
         verdict = "FAIL"
     else:
         verdict = "PASS"
-    args.out.write_text(json.dumps({"verdict": verdict, "scope": "Frozen steady-state throughput and point-estimate speech gates; no global optimum or cold-cache certification", "baseline": baseline, "candidate": candidate, "performance": performance, "quality": quality}, indent=2) + "\n")
+    args.out.write_text(
+        json.dumps(
+            {
+                "verdict": verdict,
+                "scope": (
+                    "Frozen steady-state throughput and point-estimate speech gates; "
+                    "no global optimum or cold-cache certification"
+                ),
+                "baseline": baseline,
+                "candidate": candidate,
+                "performance": performance,
+                "quality": quality,
+            },
+            indent=2,
+        )
+        + "\n"
+    )
 
 
 if __name__ == "__main__":

From 5b9d26956ad0bb09a29f77d22b4d034787a2df9f Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 11:46:26 +0800
Subject: [PATCH 05/40] Preserve service quality failures and conditional MPS
 transfer lessons

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../cases/minicpm-speaker-cpu-reference.json  | 18 ++++++++++++++++++
 .../cases/minicpm-speaker-cpu-reference.md    | 19 +++++++++++++++++++
 2 files changed, 37 insertions(+)

diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
index e97e597f9..9810c05a4 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
@@ -15,6 +15,24 @@
       "sha256": "e8b7b49fd51662d7fde58cd10306e64fde318f5ae9c857a1482ef7a6db4a94cd",
       "integrity_status": "rehashed",
       "evidence_path": "evidence/minicpmo45-l20x-20261021/results/speaker-candidate-micro.json"
+    },
+    {
+      "type": "internal",
+      "issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+      "run": "minicpmo45-l20x-20261021",
+      "artifact": "speaker-comparison.json",
+      "sha256": "6723769d5a17644e146269e69a9f4b75e136849e7889e1c4636f1a3ab5dba61b",
+      "integrity_status": "rehashed",
+      "evidence_path": "evidence/minicpmo45-l20x-20261021/results/speaker-comparison.json"
+    },
+    {
+      "type": "internal",
+      "issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+      "run": "minicpmo45-l20x-20261021",
+      "artifact": "mps-comparison.json",
+      "sha256": "a3c6ffec8e68915e9e336ece65d25b368cdbeb9231263970e023e03f1104d6e1",
+      "integrity_status": "rehashed",
+      "evidence_path": "evidence/minicpmo45-l20x-20261021/results/mps-comparison.json"
     }
   ],
   "applicability": [
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
index 583c0a240..f295c8608 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
@@ -54,6 +54,25 @@ component latency was lower. The cause was graph semantics, so retrying only
 with different precision would repeat the wrong experiment. Short reference
 inputs were discriminating; long references alone understated the error.
 
+## Service qualification and conditional composition
+
+The subsequent speaker-plus-MPS control changed the ranking: MPS improved
+high-concurrency throughput after speaker extraction moved off CPU, although
+the initial MPS-only control did not improve both target tuning cells. Treat
+this as a conditional interaction, not a universal MPS recommendation.
+
+Both speaker variants failed the original strict generated-speech gate despite
+passing the isolated embedding tolerance. Repeated low-concurrency scoring and
+fresh-start controls retained the differences. Do not reinterpret numerical
+closeness or a confidence interval containing zero as evidence of noninferiority.
+
+If an authorized owner changes acceptable quality loss after exploratory
+results, preserve the original verdict, freeze the new margins and statistical
+rule before generating unused holdout outputs, and report the new scope
+separately. Profile selection must finish before opening that holdout. The
+campaign evidence owns both decisions; this case does not supply default
+quality tolerances.
+
 ## Limits
 
 Evidence covers one CUDA GPU family, one official model revision and an English

From e3155e65448ae737cdad8e49c6fa0a76c938627e Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 11:49:56 +0800
Subject: [PATCH 06/40] Refresh packaged lessons and archive fresh-start
 confirmation

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |    4 +
 .../results/concurrency-comparison.svg        | 2576 ++++++++---------
 .../results/fresh-quality.json.gz             |  Bin 0 -> 147899 bytes
 .../results/fresh-start-confirmation.json     |  183 ++
 .../results/vllm-fresh-main.json.gz           |  Bin 0 -> 284897 bytes
 .../results/vllm-fresh-speaker.json.gz        |  Bin 0 -> 280234 bytes
 .../validator/plot_results.py                 |    4 +-
 .../validator/rsi-checks.json                 |   11 +
 .../repo_packs/inferrsi/knowledge/README.md   |    4 +-
 .../ascend-aclgraph-capture-replay.json       |    4 +-
 .../ascend/skills/ascend-device-health.json   |    4 +-
 .../skills/ascend-distributed-parallel.json   |    4 +-
 .../ascend/skills/ascend-graph-mode.json      |    4 +-
 .../skills/ascend-model-adaptation.json       |    4 +-
 .../skills/ascend-operator-profiling.json     |    4 +-
 .../ascend/skills/ascend-operator-tuning.json |    4 +-
 .../skills/ascend-optimization-casebook.json  |    4 +-
 .../skills/ascend-performance-analysis.json   |    4 +-
 .../ascend/skills/ascendc-tiling-design.json  |    4 +-
 .../skills/cann-attribution-overlap.json      |    4 +-
 .../torchnpu-device-memory-lifecycle.json     |    4 +-
 ...torchnpu-pinned-host-memory-lifecycle.json |    4 +-
 .../skills/assess-serving-preemption.json     |    4 +-
 .../assess-split-backward-schedule.json       |    4 +-
 .../skills/audit-vllm-kv-lifetimes.json       |    4 +-
 .../skills/calibrate-serving-simulation.json  |    4 +-
 .../skills/cgroup-resource-controls.json      |    4 +-
 .../checkpoint-recovery-consistency.json      |    4 +-
 .../skills/choose-parallel-training-plan.json |    4 +-
 .../skills/cite-check-downstream-pr.json      |    4 +-
 .../common/skills/claim-contract.json         |    4 +-
 .../common/skills/competitor-scan.json        |    4 +-
 .../skills/dcp-async-save-performance.json    |    4 +-
 .../skills/dense-performance-evidence.json    |    4 +-
 .../diagnose-vllm-admission-pressure.json     |    4 +-
 .../common/skills/draft-acceptance-issue.json |    4 +-
 .../evaluate-elastic-serving-placement.json   |    4 +-
 .../common/skills/host-memory-management.json |    4 +-
 .../skills/host-overhead-optimization.json    |    4 +-
 .../skills/inference-benchmark-design.json    |    4 +-
 .../inference-optimization-casebook.json      |    8 +-
 .../common/skills/kernel-writing-guide.json   |    4 +-
 .../common/skills/kv-tier-management.json     |    4 +-
 .../common/skills/npu-skill-factory.json      |    4 +-
 .../skills/optimization-search-policy.json    |    4 +-
 .../common/skills/os-process-placement.json   |    4 +-
 .../skills/performance-ceiling-analysis.json  |    4 +-
 .../skills/plan-activation-residency.json     |    4 +-
 .../skills/repository-evolution-analysis.json |    4 +-
 .../knowledge/common/skills/rsi-evidence.json |    4 +-
 .../skills/skill-evolution-playbook.json      |    4 +-
 .../common/skills/storage-io-measurement.json |    4 +-
 .../skills/training-input-pipeline.json       |    4 +-
 .../skills/training-resource-budget.json      |    4 +-
 .../skills/weight-loading-optimization.json   |    4 +-
 .../diagnose-attention-bottlenecks.json       |    4 +-
 .../cuda/skills/host-overhead-profiling.json  |    4 +-
 57 files changed, 1589 insertions(+), 1389 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/fresh-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/fresh-start-confirmation.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-fresh-main.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-fresh-speaker.json.gz

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 2240ae8d7..beb599cbd 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -184,3 +184,7 @@ Host CPUs and the filesystem are shared with other jobs; GPU reservations are
 exclusive, but CPU affinity is not isolated. The host has two Intel Xeon
 Platinum 8480C sockets, 112 physical cores / 224 hardware threads. Results are
 scoped observations on this host, not hardware-independent performance claims.
+
+## Restart confirmation
+
+`results/fresh-start-confirmation.json` compares freshly started main and speaker-only services sequentially on one reserved GPU, using the original first cohort. At C16 throughput was 518.6 versus 689.4 frames/s; at C32, 546.9 versus 799.2. These single measured repeats support persistence of the throughput direction, not a new confidence interval. The C1 SIM/UTMOS decrease also persisted. The separately authorized noninferiority holdout remains a distinct experiment.
diff --git a/evidence/minicpmo45-l20x-20261021/results/concurrency-comparison.svg b/evidence/minicpmo45-l20x-20261021/results/concurrency-comparison.svg
index 816c121ed..c344ce88a 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/fresh-start-confirmation.json b/evidence/minicpmo45-l20x-20261021/results/fresh-start-confirmation.json
new file mode 100644
index 000000000..26bcec47d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/fresh-start-confirmation.json
@@ -0,0 +1,183 @@
+{
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diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-fresh-main.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-fresh-main.json.gz
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literal 0
HcmV?d00001

diff --git a/evidence/minicpmo45-l20x-20261021/validator/plot_results.py b/evidence/minicpmo45-l20x-20261021/validator/plot_results.py
index 44074a221..28176c390 100644
--- a/evidence/minicpmo45-l20x-20261021/validator/plot_results.py
+++ b/evidence/minicpmo45-l20x-20261021/validator/plot_results.py
@@ -68,7 +68,9 @@ def main():
     fig.tight_layout(rect=(0, 0.12, 1, 0.95))
     args.out.parent.mkdir(parents=True, exist_ok=True)
     fig.savefig(args.out.with_suffix(".png"), dpi=160)
-    fig.savefig(args.out.with_suffix(".svg"))
+    svg = args.out.with_suffix(".svg")
+    fig.savefig(svg)
+    svg.write_text("\n".join(line.rstrip() for line in svg.read_text().splitlines()) + "\n")
     plt.close(fig)
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json b/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
index c4327c86a..e576d7bf6 100644
--- a/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
+++ b/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
@@ -10,5 +10,16 @@
     "peer_cuda_search": "PASS",
     "owner_local_case_resource": "PASS",
     "note": "CLI resource returns a path; resolved content was read and checked from the installed wheel."
+  },
+  "case_update_validation": {
+    "source_revision": "5b9d269",
+    "full_pytest_exit_code": 0,
+    "collected": 266,
+    "ruff_src_tests_harness": "PASS",
+    "generated_index_records": 48,
+    "generated_index_check": "PASS",
+    "installed_wheel_updated_case_content": "PASS",
+    "installed_wheel_peer_cuda_search": "PASS",
+    "wheel_sha256": "4cc598a149045315062ea881420b6d4d6f561cbf473c519c2e6b9e9553474ad8"
   }
 }
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
index 625e7bfe1..5fd8caea2 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
@@ -15,7 +15,7 @@ These are knowledge abstracts (`--kind knowledge`), with namespaced package
 IDs distinct from explicitly selected `checkout_ref` skills. Ascend/CUDA
 procedures use their corresponding backend; shared methods use `common`.
 
-Source snapshot: [9e22223040c7dc1bffe0b04de13a411ddd06646e](https://github.com/InferMatrixLab/InferRSI/tree/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library).
+Source snapshot: [5b9d26956ad0bb09a29f77d22b4d034787a2df9f](https://github.com/InferMatrixLab/InferRSI/tree/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library).
 
 ```bash
 inferrsi knowledge search 'profiling' --repo-type inferrsi --limit 50
@@ -29,7 +29,7 @@ contain the current input paths and bytes (Git checkout filters are respected).
 
 ```bash
 python tools/build_skill_index.py --source-revision <committed-source-revision>
-python tools/build_skill_index.py --source-revision 9e22223040c7dc1bffe0b04de13a411ddd06646e --check
+python tools/build_skill_index.py --source-revision 5b9d26956ad0bb09a29f77d22b4d034787a2df9f --check
 ```
 
 `--check` detects missing, stale and unexpected generated records without writing.
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
index b8f4d0ed7..73079f915 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
index 1e66c1421..9657d7191 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
index 541b9ec89..42d4ef2e6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
index 74a05ffda..2c8e0b576 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
index 785e4dde8..7e5f132c4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
index e1254de94..bdd46686b 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
index e14f3332a..d42e442b9 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
index d9b542932..e56a7db46 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
@@ -22,8 +22,8 @@
   "sources": [
     {
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index 9246ac746..d71b1c1fc 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
index 4f1bf4c6d..2f5cbca62 100644
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index e75ca7a71..a9efa4751 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
index adf7bb57a..6797dd6f3 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
index d0dfdded1..5779bcd8c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
index fbfb8a8a5..98cd5f8a8 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
index 42d3d72c0..294d099ca 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
index 5be576ef8..32bcb9608 100644
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+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
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index 74656b7ce..0ea4ca031 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
index 09ed2ec5c..09be1e489 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
index 9f439e23c..8e33d0fda 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
index 6b427eb59..dd660ac6e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json
index be329b512..439f7b31e 100644
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index 1c1d5a29e..276f2dd18 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
index 39e5a0176..510e92a3d 100644
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index 8da19d5e7..a6b2664fb 100644
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index 222ae1324..a09ac6071 100644
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index 8a73b81d4..69f057891 100644
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index 080ba0a9a..a38de1e4a 100644
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index e5297d42b..cf86da9ab 100644
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index 6f78ce7f3..3bd277ee6 100644
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index 5b149c594..49c75822d 100644
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index cafb16f81..79a2ecb91 100644
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index fa2c0f533..1af498e11 100644
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index 800901aaf..6aeca5194 100644
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index 7b0fcb765..0ebcdc867 100644
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index 6acdcb066..e7cd0fbcf 100644
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index e3c2a1a44..50a91b04c 100644
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index 8f865a100..c6a951b82 100644
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-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/methods/performance-ceiling-analysis/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/methods/performance-ceiling-analysis/SKILL.md",
         "src/inferrsi/data/skill_library/methods/performance-ceiling-analysis/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
index da2bc93a8..313219501 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/plan-activation-residency/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/methods/plan-activation-residency/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/methods/plan-activation-residency/SKILL.md",
         "src/inferrsi/data/skill_library/methods/plan-activation-residency/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
index 64f232002..98b142665 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/repository-evolution-analysis/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/methods/repository-evolution-analysis/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/methods/repository-evolution-analysis/SKILL.md",
         "src/inferrsi/data/skill_library/methods/repository-evolution-analysis/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
index 16c561851..09cc34518 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/workflows/rsi-evidence/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/workflows/rsi-evidence/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/skill-index.json",
         "src/inferrsi/data/skill_library/workflows/rsi-evidence/SKILL.md"
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
index 77420301e..011fc7dcf 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/skill-evolution-playbook/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/methods/skill-evolution-playbook/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/methods/skill-evolution-playbook/SKILL.md",
         "src/inferrsi/data/skill_library/methods/skill-evolution-playbook/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
index 39333ba22..8909414be 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
index 0ede14999..94b411808 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
index b331e438a..a2431e7f7 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-resource-budget/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
index 708c33bb7..50f0997cc 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
index 73dbbab7c..82356d645 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
index e2d037bc8..5e9db5aff 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/9e22223040c7dc1bffe0b04de13a411ddd06646e/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
-      "commit": "9e22223040c7dc1bffe0b04de13a411ddd06646e",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d26956ad0bb09a29f77d22b4d034787a2df9f/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
+      "commit": "5b9d26956ad0bb09a29f77d22b4d034787a2df9f",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json",

From d99203a8be95759a9cc403469a747175b2290877 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 12:03:20 +0800
Subject: [PATCH 07/40] Regenerate merged skill catalog and freeze updated main
 comparison

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/knowledge-transfer.json              | 19 +++++++++++++----
 .../plan/latest-main-addendum.json            | 21 +++++++++++++++++++
 .../validator/rsi-checks.json                 | 12 +++++++++++
 .../repo_packs/inferrsi/knowledge/README.md   |  4 ++--
 .../ascend-aclgraph-capture-replay.json       |  4 ++--
 .../ascend/skills/ascend-device-health.json   |  4 ++--
 .../skills/ascend-distributed-parallel.json   |  4 ++--
 .../ascend/skills/ascend-graph-mode.json      |  4 ++--
 .../skills/ascend-model-adaptation.json       |  4 ++--
 .../skills/ascend-operator-profiling.json     |  4 ++--
 .../ascend/skills/ascend-operator-tuning.json |  4 ++--
 .../skills/ascend-optimization-casebook.json  |  4 ++--
 .../skills/ascend-performance-analysis.json   |  4 ++--
 .../ascend/skills/ascendc-tiling-design.json  |  4 ++--
 .../skills/cann-attribution-overlap.json      |  4 ++--
 .../torchnpu-device-memory-lifecycle.json     |  4 ++--
 ...torchnpu-pinned-host-memory-lifecycle.json |  4 ++--
 .../skills/assess-serving-preemption.json     |  4 ++--
 .../assess-split-backward-schedule.json       |  4 ++--
 .../skills/audit-vllm-kv-lifetimes.json       |  4 ++--
 .../skills/calibrate-serving-simulation.json  |  4 ++--
 .../skills/cgroup-resource-controls.json      |  4 ++--
 .../checkpoint-recovery-consistency.json      |  4 ++--
 .../skills/choose-parallel-training-plan.json |  4 ++--
 .../skills/cite-check-downstream-pr.json      |  4 ++--
 .../common/skills/claim-contract.json         |  4 ++--
 .../common/skills/competitor-scan.json        |  4 ++--
 .../skills/dcp-async-save-performance.json    |  4 ++--
 .../skills/dense-performance-evidence.json    |  4 ++--
 .../diagnose-vllm-admission-pressure.json     |  4 ++--
 .../common/skills/draft-acceptance-issue.json |  4 ++--
 .../evaluate-elastic-serving-placement.json   |  4 ++--
 .../common/skills/host-memory-management.json |  4 ++--
 .../skills/host-overhead-optimization.json    |  4 ++--
 .../skills/inference-benchmark-design.json    |  4 ++--
 .../inference-optimization-casebook.json      | 12 +++++++----
 .../common/skills/kernel-writing-guide.json   |  4 ++--
 .../common/skills/kv-tier-management.json     |  4 ++--
 .../common/skills/npu-skill-factory.json      |  4 ++--
 .../skills/optimization-search-policy.json    |  4 ++--
 .../common/skills/os-process-placement.json   |  4 ++--
 .../skills/performance-ceiling-analysis.json  |  4 ++--
 .../skills/plan-activation-residency.json     |  4 ++--
 .../skills/repository-evolution-analysis.json |  4 ++--
 .../knowledge/common/skills/rsi-evidence.json |  4 ++--
 .../skills/skill-evolution-playbook.json      |  4 ++--
 .../common/skills/storage-io-measurement.json |  4 ++--
 .../skills/training-input-pipeline.json       |  4 ++--
 .../skills/training-resource-budget.json      |  4 ++--
 .../skills/weight-loading-optimization.json   |  4 ++--
 .../diagnose-attention-bottlenecks.json       |  4 ++--
 .../cuda/skills/host-overhead-profiling.json  |  4 ++--
 52 files changed, 152 insertions(+), 104 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/latest-main-addendum.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json b/evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json
index 4a85a65b0..5f9e808aa 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/knowledge-transfer.json
@@ -6,28 +6,39 @@
       "source_path": "src/inferrsi/data/skill_library/en/strata/sub-skills/tune-execution/SKILL.md",
       "content_sha256": "cdf51c537e7237296d52ef6cda9f2e4c9d9ce3fc87265a369cd9eb7497c53512",
       "lesson": "Use resolved settings, controlled one-plane experiments, repeated service measurements and explicit regressions.",
-      "application": "Separate MPS, encoder capture and microbatch controls; retest MPS after speaker extraction changes the bottleneck. No Strata speedup is imported."
+      "application": "Separate MPS, encoder capture and microbatch controls; retest MPS after speaker extraction changes the bottleneck. No Strata speedup is imported.",
+      "source_revision": "5b9d269",
+      "source_url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d269/src/inferrsi/data/skill_library/en/strata/sub-skills/tune-execution/SKILL.md",
+      "current_path": "src/inferrsi/data/skill_library/repositories/strata/sub-skills/tune-execution/SKILL.md"
     },
     {
       "knowledge_scope": "vllm_omni",
       "source_path": "src/inferrsi/data/skill_library/en/vllm-omni/sub-skills/omni-validation/SKILL.md",
       "content_sha256": "81c2a8cbdccaa86ff560311ec9d33ba191ecc6e3121ca4e9f751f006875223c9",
       "lesson": "Escalate native tests through accelerator parity, real speech quality and matched service performance.",
-      "application": "67 CPU regressions, real CAM++ numerical checks, repeated service results and independent speech gates. Component PASS never overrides speech FAIL."
+      "application": "67 CPU regressions, real CAM++ numerical checks, repeated service results and independent speech gates. Component PASS never overrides speech FAIL.",
+      "source_revision": "5b9d269",
+      "source_url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d269/src/inferrsi/data/skill_library/en/vllm-omni/sub-skills/omni-validation/SKILL.md",
+      "current_path": "src/inferrsi/data/skill_library/repositories/vllm-omni/sub-skills/omni-validation/SKILL.md"
     },
     {
       "knowledge_scope": "sglang_omni",
       "source_path": "src/inferrsi/data/skill_library/en/sglang-omni/sub-skills/sglang-omni-architecture/SKILL.md",
       "content_sha256": "766b2d66d2056dd779abd9e492cb3af6e25899298f44964f565509f130a7cb24",
       "lesson": "Trace concrete stages and terminal outputs at the pinned source rather than infer behavior from model name.",
-      "application": "Identify terminal waveform semantics, FP16 compiled Code2Wav and reference_workers=8; retain native scorer implementation and a separate CPU parallel preparation prototype."
+      "application": "Identify terminal waveform semantics, FP16 compiled Code2Wav and reference_workers=8; retain native scorer implementation and a separate CPU parallel preparation prototype.",
+      "source_revision": "5b9d269",
+      "source_url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d269/src/inferrsi/data/skill_library/en/sglang-omni/sub-skills/sglang-omni-architecture/SKILL.md",
+      "current_path": "src/inferrsi/data/skill_library/repositories/sglang-omni/sub-skills/sglang-omni-architecture/SKILL.md"
     },
     {
       "knowledge_scope": "minicpmo_single_gpu_engine",
       "source_path": "src/inferrsi/data/knowledge_packs/peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json",
       "content_sha256": "58ebe6ac09cbbb774216acd0fdaef29409e685cd7a7521501154b67b963565fa",
       "lesson": "Preserve audio-delivery metrics, disjoint pools, request-owned state and quality-constrained transfer.",
-      "application": "Reuse pinned adapters/client/workload, test MPS and graph/batching hypotheses, and explicitly distinguish this steady-state campaign from strict cold-cache certification."
+      "application": "Reuse pinned adapters/client/workload, test MPS and graph/batching hypotheses, and explicitly distinguish this steady-state campaign from strict cold-cache certification.",
+      "source_revision": "5b9d269",
+      "source_url": "https://github.com/InferMatrixLab/InferRSI/blob/5b9d269/src/inferrsi/data/knowledge_packs/peer/minicpmo_single_gpu_engine/cuda/audio/streaming-transfer-constraints.json"
     }
   ]
 }
diff --git a/evidence/minicpmo45-l20x-20261021/plan/latest-main-addendum.json b/evidence/minicpmo45-l20x-20261021/plan/latest-main-addendum.json
new file mode 100644
index 000000000..0f5e8200e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/latest-main-addendum.json
@@ -0,0 +1,21 @@
+{
+  "frozen_at_utc": "2026-10-21T03:57:10.759083+00:00",
+  "reason": "Upstream main advanced during the campaign and enabled Torch CUDA speaker extraction by default in #9178. Preserve the original baseline and add the new snapshot rather than calling old results current.",
+  "new_baseline_sha": "15bce34586",
+  "previous_baseline_sha": "aa3fd1d9b7f5c7191dec11975ac0aa7c4c4a18c5",
+  "concurrency": [
+    1,
+    2,
+    4,
+    8,
+    16,
+    32
+  ],
+  "requests": 320,
+  "repeats": 3,
+  "discard_runs": 1,
+  "cohort": "original first320 eval rows, unchanged driver v2",
+  "quality": "Same existing scorers at C1/16/32 run1; separately report comparisons and original CPU-reference noninferiority holdout. No post-hoc threshold relaxation.",
+  "driver_sha256": "0c66908c5959e3b91e5a091af5cf2a6382443c3ba0c416d6917e7af3aef3222b",
+  "candidate_integration": "Preserve new upstream Torch defaults; introduce explicit token2wav_spk_cpu_reference opt-in for the previously measured CPU-reference TRT math."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json b/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
index e576d7bf6..4a30dc23c 100644
--- a/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
+++ b/evidence/minicpmo45-l20x-20261021/validator/rsi-checks.json
@@ -21,5 +21,17 @@
     "installed_wheel_updated_case_content": "PASS",
     "installed_wheel_peer_cuda_search": "PASS",
     "wheel_sha256": "4cc598a149045315062ea881420b6d4d6f561cbf473c519c2e6b9e9553474ad8"
+  },
+  "merged_upstream_validation": {
+    "source_revision": "94273606a05110f2d9826974f1031d3cf269ce01",
+    "upstream_revision": "4c43198",
+    "full_pytest_exit_code": 0,
+    "collected": 267,
+    "ruff_src_tests_harness": "PASS",
+    "generated_index_records": 48,
+    "generated_index_check": "PASS",
+    "installed_wheel_updated_case_content": "PASS",
+    "installed_wheel_peer_cuda_search": "PASS",
+    "wheel_sha256": "60e836567eed26957f9b90291077cb28317bcba5bbdd7e80d7628659eb024031"
   }
 }
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
index 6f2c05eb7..92f08107c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
@@ -15,7 +15,7 @@ These are knowledge abstracts (`--kind knowledge`), with namespaced package
 IDs distinct from explicitly selected `checkout_ref` skills. Ascend/CUDA
 procedures use their corresponding backend; shared methods use `common`.
 
-Source snapshot: [ddeba86177132c5933cf7ab1e6eb7021fb767e22](https://github.com/InferMatrixLab/InferRSI/tree/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library).
+Source snapshot: [94273606a05110f2d9826974f1031d3cf269ce01](https://github.com/InferMatrixLab/InferRSI/tree/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library).
 
 ```bash
 inferrsi knowledge search 'profiling' --repo-type inferrsi --limit 50
@@ -29,7 +29,7 @@ contain the current input paths and bytes (Git checkout filters are respected).
 
 ```bash
 python tools/build_skill_index.py --source-revision <committed-source-revision>
-python tools/build_skill_index.py --source-revision ddeba86177132c5933cf7ab1e6eb7021fb767e22 --check
+python tools/build_skill_index.py --source-revision 94273606a05110f2d9826974f1031d3cf269ce01 --check
 ```
 
 `--check` detects missing, stale and unexpected generated records without writing.
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
index 4a5a3550f..382164910 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
index 45e3f0dbf..52bf998d7 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
index 6ad6f33cb..e99e1cb8e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
index 102a5a124..328bb0ab4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
index 81b843da3..b643be41e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
index 74d68eb53..263257ef6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
index d1aea7d8c..2958f89e1 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
index 8deb6968b..aa7dcf8ba 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
index 25b0b5f45..0ede18214 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
index da077fc8f..b8ddc166f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
index d2f7b9807..a1cbc83ba 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
index 985f295ea..41efb759b 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
index b77fd674c..70e17fd7e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
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index aa773f457..b7ef77f98 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
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@@ -16,8 +16,8 @@
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index 1c31a9e00..030e43c2f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
index bec232baf..29530bc1e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
@@ -21,8 +21,8 @@
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index 44c535c8c..8b397af72 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
index 921c7defd..82c5e075a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
index f9058da09..307309178 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
index dcac8bba4..205979d6d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
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index d3b7fa0e0..814e1cf82 100644
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index 95f7bfb7f..1c6b2a733 100644
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index 2b34b6e82..7bbf5c215 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
index d19303fbe..64f7ad62d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
index 03077f5dd..45146193f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
index 20647f7a2..5cd5be992 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
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index a5df48f1a..08c8b67e9 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json
index 1df7801cc..222005122 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
index f2ea2f48c..1cf810ede 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json
index 208143ced..c0c1d6b7a 100644
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index 8c60ab54a..838bd8fde 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json
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index 32e4daf3a..a1746e4d0 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json
@@ -21,14 +21,16 @@
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         "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/drama3-rejected-directions.md",
+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json",
+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md",
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index 245ae37e7..7b6c53cbc 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
@@ -24,8 +24,8 @@
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index 0c9e575ef..888404431 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
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index ae6ee02ff..7d865eb6b 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
@@ -22,8 +22,8 @@
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index 63f1676c9..bb87fb27a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
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index b61f780df..c1cae16f6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
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@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
index db422eea7..a0118657f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
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index 7b7b36ecb..c990d7d1a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
@@ -16,8 +16,8 @@
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index 6c7d51910..4e267dce1 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
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@@ -21,8 +21,8 @@
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index 264c610b1..9411a5eea 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
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index 8c058e385..c1af9ae56 100644
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@@ -21,8 +21,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
index 529bcdbcf..d41c517da 100644
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         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
index 4302ada22..e3441c44a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
index 9d9eb9c02..b9ed2b831 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-resource-budget/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
index af07a2355..a7288f445 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
index 87a624e51..706db8622 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
index c1446b765..e670dc8c6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ddeba86177132c5933cf7ab1e6eb7021fb767e22/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
-      "commit": "ddeba86177132c5933cf7ab1e6eb7021fb767e22",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
+      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json",

From 27b1b4c4d7d8e4725bb54b0d5bf6da510ef67c2d Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 12:10:39 +0800
Subject: [PATCH 08/40] Freeze adapted CPU-reference speaker comparison against
 updated main

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |  25 +-
 .../patch/integrated-candidate.json           |  11 +
 .../minicpmo_4_5_cpu_reference_trt_mps.yaml   |  11 +
 .../plan/integrated-comparison.json           | 356 +++++++++++++++++
 .../plan/integrated-resolved-config.json      | 370 ++++++++++++++++++
 .../results/integrated-speaker-micro.json     | 327 ++++++++++++++++
 .../results/status.json                       |  10 +-
 .../validator/integrated-checks.json          |  10 +
 .../validator/integrated_comparison.py        |  79 ++++
 .../validator/integration-equivalence.json    |   9 +
 .../validator/validate_integrated_config.py   |  49 +++
 11 files changed, 1252 insertions(+), 5 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/minicpmo_4_5_cpu_reference_trt_mps.yaml
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/integrated-comparison.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/integrated-resolved-config.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/integrated-speaker-micro.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/integrated-checks.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/integrated_comparison.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/integration-equivalence.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/validate_integrated_config.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index beb599cbd..0c1b5695f 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -17,7 +17,7 @@ Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49)
 
 The native main configurations also differ: SGLang Code2Wav uses float16, compiled DiT/HiFT, eight reference workers and a 32-entry prompt cache; this vLLM baseline uses its default FP32 CFM path and serial CPU reference preparation. These are native-engine comparisons, not an isolated backend comparison with identical numerical kernels and scheduling.
 
-## Main-branch baselines
+## Initial main snapshots (before CUDA Torch became the vLLM default)
 
 | Engine | C | Frames/s | TTFA p50 ms | TTFA p95 ms | RTF mean |
 |---|---:|---:|---:|---:|---:|
@@ -188,3 +188,26 @@ scoped observations on this host, not hardware-independent performance claims.
 ## Restart confirmation
 
 `results/fresh-start-confirmation.json` compares freshly started main and speaker-only services sequentially on one reserved GPU, using the original first cohort. At C16 throughput was 518.6 versus 689.4 frames/s; at C32, 546.9 versus 799.2. These single measured repeats support persistence of the throughput direction, not a new confidence interval. The C1 SIM/UTMOS decrease also persisted. The separately authorized noninferiority holdout remains a distinct experiment.
+
+## Upstream integration during the experiment
+
+While the frozen experiment was running, vLLM-Omni merged #9178, enabling
+Torch CUDA speaker extraction by default. The historical `aa3fd1d9` baseline
+and `f2462435` candidate remain intact. Their measurements must not be described
+as gains over the newer `15bce34586` main snapshot.
+
+The adapted PR revision is `227a43e898f8b96236f48f16f399431c8ad0ddcc`.
+It preserves the new Torch default and exposes `token2wav_spk_cpu_reference`
+as an explicit opt-in, with a checked-in MPS overlay. Use
+`patch/integrated-candidate.json` and
+`patch/minicpmo_4_5_cpu_reference_trt_mps.yaml` for that revision;
+`patch/candidate.json` and the earlier overlays describe the historical one.
+
+Updated-main and adapted-candidate six-cell repeats are governed by
+`plan/latest-main-addendum.json` and `plan/integrated-comparison.json`.
+Their quality comparison uses previously seen first-cohort prompts and is
+explicitly an integration regression, not another untouched holdout. The
+original unused-cohort decision remains separately scoped to the historical
+candidate. Source equality checks in `validator/integration-equivalence.json`
+cover the speaker implementation only; updated coordinator behavior still
+requires the separate service comparison.
diff --git a/evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json b/evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json
new file mode 100644
index 000000000..27257f749
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json
@@ -0,0 +1,11 @@
+{
+  "candidate_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc",
+  "baseline_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "pull_request": "https://github.com/vllm-project/vllm-omni/pull/9188",
+  "profile": "minicpmo_4_5_cpu_reference_trt_mps.yaml",
+  "opt_in": "token2wav_spk_cpu_reference=true",
+  "default_policy": "Preserve upstream Torch CUDA/NPU speaker defaults; optional CPU-reference TRT requires CUDA and excludes full DiT TRT.",
+  "historical_candidate_revision": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
+  "history": "Historical measured candidate retained as an ancestor; adapted feature is based on updated upstream main.",
+  "shared_speaker_implementation_sha256": "310129b4283200a71221e813185d14ef9b44873df1147e1d1e2a68baeff2d755"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/patch/minicpmo_4_5_cpu_reference_trt_mps.yaml b/evidence/minicpmo45-l20x-20261021/patch/minicpmo_4_5_cpu_reference_trt_mps.yaml
new file mode 100644
index 000000000..dedcf6a25
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/minicpmo_4_5_cpu_reference_trt_mps.yaml
@@ -0,0 +1,11 @@
+# Optional CUDA speaker-only TensorRT profile for turn-mode voice cloning.
+# Install TensorRT matching the CUDA runtime before selecting this profile.
+# See docs/design/minicpm_o45_mrv2_performance.md for reference semantics.
+base_config: minicpmo_4_5_turn.yaml
+cuda_mps: true
+connectors:
+  connector_of_shared_memory:
+    extra:
+      token2wav_device_spk: true
+      token2wav_spk_cpu_reference: true
+      token2wav_trt: false
diff --git a/evidence/minicpmo45-l20x-20261021/plan/integrated-comparison.json b/evidence/minicpmo45-l20x-20261021/plan/integrated-comparison.json
new file mode 100644
index 000000000..7dc995b55
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/integrated-comparison.json
@@ -0,0 +1,356 @@
+{
+  "frozen_at_utc": "2026-10-21T04:06:27.033995+00:00",
+  "candidate_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc",
+  "baseline_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "scope": "Post-integration regression comparison on the previously used first cohort; NOT a new untouched holdout. Original unused-cohort validation remains scoped to historical candidate f2462435.",
+  "selection": "Previously selected speaker CPU-reference TRT plus MPS; no new quality-driven tuning.",
+  "concurrency": [
+    1,
+    2,
+    4,
+    8,
+    16,
+    32
+  ],
+  "requests": 320,
+  "discard_runs": 1,
+  "measured_repeats": 3,
+  "quality_concurrency": [
+    1,
+    16,
+    32
+  ],
+  "quality_run": 1,
+  "expected_ids": [
+    "common_voice_en_10119832-common_voice_en_10119847",
+    "common_voice_en_103675-common_voice_en_103676",
+    "common_voice_en_10933823-common_voice_en_10933822",
+    "common_voice_en_10933823-common_voice_en_10933825",
+    "common_voice_en_120405-common_voice_en_120402",
+    "common_voice_en_120405-common_voice_en_120406",
+    "common_voice_en_1416089-common_voice_en_1416090",
+    "common_voice_en_153872-common_voice_en_153873",
+    "common_voice_en_15734837-common_voice_en_15734838",
+    "common_voice_en_15903802-common_voice_en_15903815",
+    "common_voice_en_167249-common_voice_en_167246",
+    "common_voice_en_167249-common_voice_en_167247",
+    "common_voice_en_17147545-common_voice_en_17147546",
+    "common_voice_en_17161-common_voice_en_17159",
+    "common_voice_en_17249419-common_voice_en_17249428",
+    "common_voice_en_17255102-common_voice_en_17255101",
+    "common_voice_en_17256676-common_voice_en_17256678",
+    "common_voice_en_17263752-common_voice_en_17263755",
+    "common_voice_en_17267923-common_voice_en_17267922",
+    "common_voice_en_17268075-common_voice_en_17268076",
+    "common_voice_en_17271507-common_voice_en_17271510",
+    "common_voice_en_17274522-common_voice_en_17274525",
+    "common_voice_en_17324784-common_voice_en_17324786",
+    "common_voice_en_173534-common_voice_en_173537",
+    "common_voice_en_17389076-common_voice_en_17389120",
+    "common_voice_en_17401431-common_voice_en_17401433",
+    "common_voice_en_17406732-common_voice_en_17406735",
+    "common_voice_en_17429166-common_voice_en_17429171",
+    "common_voice_en_17444666-common_voice_en_17444667",
+    "common_voice_en_17444666-common_voice_en_17444668",
+    "common_voice_en_17451108-common_voice_en_17451109",
+    "common_voice_en_175348-common_voice_en_175349",
+    "common_voice_en_17578783-common_voice_en_17578781",
+    "common_voice_en_17662945-common_voice_en_17662954",
+    "common_voice_en_17718576-common_voice_en_17718578",
+    "common_voice_en_17727889-common_voice_en_17727904",
+    "common_voice_en_17727889-common_voice_en_17727905",
+    "common_voice_en_17729945-common_voice_en_17729944",
+    "common_voice_en_17736608-common_voice_en_17736610",
+    "common_voice_en_17784-common_voice_en_17786",
+    "common_voice_en_177895-common_voice_en_177894",
+    "common_voice_en_177895-common_voice_en_177898",
+    "common_voice_en_17830764-common_voice_en_17830783",
+    "common_voice_en_17854896-common_voice_en_17854894",
+    "common_voice_en_17861489-common_voice_en_17861487",
+    "common_voice_en_17874600-common_voice_en_17874601",
+    "common_voice_en_17874600-common_voice_en_17874602",
+    "common_voice_en_17875915-common_voice_en_17875925",
+    "common_voice_en_17889905-common_voice_en_17889907",
+    "common_voice_en_17893247-common_voice_en_17893250",
+    "common_voice_en_17899910-common_voice_en_17899909",
+    "common_voice_en_18105426-common_voice_en_18105430",
+    "common_voice_en_18229682-common_voice_en_18229679",
+    "common_voice_en_18234333-common_voice_en_18234353",
+    "common_voice_en_18240348-common_voice_en_18240305",
+    "common_voice_en_18436934-common_voice_en_18436935",
+    "common_voice_en_18466098-common_voice_en_18466096",
+    "common_voice_en_18485041-common_voice_en_18485042",
+    "common_voice_en_18500600-common_voice_en_18500603",
+    "common_voice_en_18533403-common_voice_en_18533404",
+    "common_voice_en_18647546-common_voice_en_18647545",
+    "common_voice_en_18693241-common_voice_en_18693240",
+    "common_voice_en_18699078-common_voice_en_18699081",
+    "common_voice_en_18710640-common_voice_en_18710642",
+    "common_voice_en_18735317-common_voice_en_18735316",
+    "common_voice_en_18735317-common_voice_en_18735372",
+    "common_voice_en_18770703-common_voice_en_18770704",
+    "common_voice_en_188092-common_voice_en_188091",
+    "common_voice_en_18829843-common_voice_en_18829841",
+    "common_voice_en_18877786-common_voice_en_18877788",
+    "common_voice_en_18944281-common_voice_en_18944280",
+    "common_voice_en_18993020-common_voice_en_18993021",
+    "common_voice_en_18994068-common_voice_en_18994069",
+    "common_voice_en_18998723-common_voice_en_18998724",
+    "common_voice_en_19002369-common_voice_en_19002367",
+    "common_voice_en_19017623-common_voice_en_19017624",
+    "common_voice_en_19022657-common_voice_en_19022662",
+    "common_voice_en_19022657-common_voice_en_19022667",
+    "common_voice_en_19043111-common_voice_en_19043119",
+    "common_voice_en_19117097-common_voice_en_19117098",
+    "common_voice_en_19176854-common_voice_en_19176853",
+    "common_voice_en_19277026-common_voice_en_19277029",
+    "common_voice_en_19289713-common_voice_en_19289715",
+    "common_voice_en_19294198-common_voice_en_19294199",
+    "common_voice_en_19343495-common_voice_en_19343496",
+    "common_voice_en_19343495-common_voice_en_19343497",
+    "common_voice_en_19345360-common_voice_en_19345358",
+    "common_voice_en_19345360-common_voice_en_19345359",
+    "common_voice_en_19361636-common_voice_en_19361634",
+    "common_voice_en_19428391-common_voice_en_19428396",
+    "common_voice_en_19540120-common_voice_en_19540122",
+    "common_voice_en_19560742-common_voice_en_19560741",
+    "common_voice_en_19579295-common_voice_en_19579294",
+    "common_voice_en_19579295-common_voice_en_19579310",
+    "common_voice_en_19629167-common_voice_en_19629165",
+    "common_voice_en_19632634-common_voice_en_19632644",
+    "common_voice_en_19641789-common_voice_en_19641784",
+    "common_voice_en_19665909-common_voice_en_19665911",
+    "common_voice_en_19670674-common_voice_en_19670675",
+    "common_voice_en_19686152-common_voice_en_19686154",
+    "common_voice_en_19686493-common_voice_en_19686494",
+    "common_voice_en_19690002-common_voice_en_19690001",
+    "common_voice_en_19714465-common_voice_en_19714469",
+    "common_voice_en_19722359-common_voice_en_19722397",
+    "common_voice_en_19724030-common_voice_en_19724028",
+    "common_voice_en_19724242-common_voice_en_19724243",
+    "common_voice_en_19724242-common_voice_en_19724245",
+    "common_voice_en_19724475-common_voice_en_19724484",
+    "common_voice_en_19724850-common_voice_en_19724899",
+    "common_voice_en_19724850-common_voice_en_19724900",
+    "common_voice_en_19730681-common_voice_en_19730683",
+    "common_voice_en_19734247-common_voice_en_19734252",
+    "common_voice_en_19791537-common_voice_en_19791538",
+    "common_voice_en_19816147-common_voice_en_19816166",
+    "common_voice_en_19867710-common_voice_en_19867713",
+    "common_voice_en_19944630-common_voice_en_19944633",
+    "common_voice_en_19972684-common_voice_en_19972725",
+    "common_voice_en_19974164-common_voice_en_19974166",
+    "common_voice_en_19977527-common_voice_en_19977526",
+    "common_voice_en_19977527-common_voice_en_19977528",
+    "common_voice_en_19984445-common_voice_en_19984443",
+    "common_voice_en_19984445-common_voice_en_19984446",
+    "common_voice_en_19992384-common_voice_en_19992381",
+    "common_voice_en_19992384-common_voice_en_19992617",
+    "common_voice_en_20005340-common_voice_en_20005341",
+    "common_voice_en_20005340-common_voice_en_20005343",
+    "common_voice_en_20049071-common_voice_en_20049072",
+    "common_voice_en_20049071-common_voice_en_20049074",
+    "common_voice_en_20065698-common_voice_en_20065701",
+    "common_voice_en_20066900-common_voice_en_20066899",
+    "common_voice_en_20066900-common_voice_en_20066901",
+    "common_voice_en_20095636-common_voice_en_20095638",
+    "common_voice_en_20190570-common_voice_en_20190572",
+    "common_voice_en_20214898-common_voice_en_20214908",
+    "common_voice_en_20252760-common_voice_en_20252762",
+    "common_voice_en_20252760-common_voice_en_20252766",
+    "common_voice_en_20262152-common_voice_en_20262155",
+    "common_voice_en_20266775-common_voice_en_20266781",
+    "common_voice_en_20285294-common_voice_en_20285295",
+    "common_voice_en_20297680-common_voice_en_20297678",
+    "common_voice_en_20303932-common_voice_en_20303930",
+    "common_voice_en_20317297-common_voice_en_20317298",
+    "common_voice_en_203357-common_voice_en_203358",
+    "common_voice_en_203357-common_voice_en_203359",
+    "common_voice_en_20337838-common_voice_en_20337841",
+    "common_voice_en_20461046-common_voice_en_20461051",
+    "common_voice_en_20522396-common_voice_en_20522395",
+    "common_voice_en_20531306-common_voice_en_20531308",
+    "common_voice_en_205647-common_voice_en_205648",
+    "common_voice_en_20583510-common_voice_en_20583514",
+    "common_voice_en_20640019-common_voice_en_20640020",
+    "common_voice_en_20660224-common_voice_en_20660228",
+    "common_voice_en_20661858-common_voice_en_20661861",
+    "common_voice_en_20688082-common_voice_en_20688083",
+    "common_voice_en_20718170-common_voice_en_20718169",
+    "common_voice_en_20791113-common_voice_en_20791117",
+    "common_voice_en_20791578-common_voice_en_20791581",
+    "common_voice_en_20791751-common_voice_en_20791750",
+    "common_voice_en_20798109-common_voice_en_20798113",
+    "common_voice_en_20812017-common_voice_en_20812019",
+    "common_voice_en_20872478-common_voice_en_20872481",
+    "common_voice_en_20888046-common_voice_en_20888048",
+    "common_voice_en_20905661-common_voice_en_20905660",
+    "common_voice_en_20905661-common_voice_en_20905662",
+    "common_voice_en_21059484-common_voice_en_21059485",
+    "common_voice_en_21184954-common_voice_en_21184959",
+    "common_voice_en_21293493-common_voice_en_21293494",
+    "common_voice_en_21345624-common_voice_en_21345626",
+    "common_voice_en_21444162-common_voice_en_21444163",
+    "common_voice_en_21499767-common_voice_en_21499784",
+    "common_voice_en_21534516-common_voice_en_21534520",
+    "common_voice_en_21589881-common_voice_en_21589882",
+    "common_voice_en_21620052-common_voice_en_21620054",
+    "common_voice_en_21653057-common_voice_en_21653072",
+    "common_voice_en_21659259-common_voice_en_21659260",
+    "common_voice_en_21742650-common_voice_en_21742652",
+    "common_voice_en_21777264-common_voice_en_21777266",
+    "common_voice_en_21802531-common_voice_en_21802534",
+    "common_voice_en_21869715-common_voice_en_21869717",
+    "common_voice_en_21869715-common_voice_en_21869718",
+    "common_voice_en_22391641-common_voice_en_22391761",
+    "common_voice_en_22722937-common_voice_en_22722935",
+    "common_voice_en_22728555-common_voice_en_22728571",
+    "common_voice_en_22763534-common_voice_en_22763537",
+    "common_voice_en_22768238-common_voice_en_22768242",
+    "common_voice_en_22777850-common_voice_en_22777868",
+    "common_voice_en_22779827-common_voice_en_22779829",
+    "common_voice_en_22839883-common_voice_en_22839889",
+    "common_voice_en_22925816-common_voice_en_22925817",
+    "common_voice_en_22940721-common_voice_en_22940719",
+    "common_voice_en_22941073-common_voice_en_22941074",
+    "common_voice_en_23252329-common_voice_en_23252333",
+    "common_voice_en_23252329-common_voice_en_23252335",
+    "common_voice_en_2331-common_voice_en_2332",
+    "common_voice_en_23621347-common_voice_en_23621349",
+    "common_voice_en_23639587-common_voice_en_23639589",
+    "common_voice_en_23640041-common_voice_en_23640040",
+    "common_voice_en_23729047-common_voice_en_23729050",
+    "common_voice_en_23750957-common_voice_en_23750960",
+    "common_voice_en_23763831-common_voice_en_23763836",
+    "common_voice_en_23809069-common_voice_en_23809074",
+    "common_voice_en_23963776-common_voice_en_23963775",
+    "common_voice_en_23963776-common_voice_en_23963795",
+    "common_voice_en_23976710-common_voice_en_23976707",
+    "common_voice_en_23976710-common_voice_en_23976708",
+    "common_voice_en_23982302-common_voice_en_23982305",
+    "common_voice_en_24009789-common_voice_en_24009791",
+    "common_voice_en_24015547-common_voice_en_24015546",
+    "common_voice_en_24356884-common_voice_en_24356917",
+    "common_voice_en_24504889-common_voice_en_24504894",
+    "common_voice_en_24518104-common_voice_en_24518109",
+    "common_voice_en_24605843-common_voice_en_24605841",
+    "common_voice_en_24819370-common_voice_en_24819368",
+    "common_voice_en_24837486-common_voice_en_24837489",
+    "common_voice_en_24912752-common_voice_en_24912751",
+    "common_voice_en_24912752-common_voice_en_24913161",
+    "common_voice_en_24985801-common_voice_en_24985800",
+    "common_voice_en_24985801-common_voice_en_24985802",
+    "common_voice_en_24988318-common_voice_en_24988314",
+    "common_voice_en_25014861-common_voice_en_25014862",
+    "common_voice_en_25014861-common_voice_en_25014863",
+    "common_voice_en_25024571-common_voice_en_25024570",
+    "common_voice_en_25024571-common_voice_en_25024574",
+    "common_voice_en_25190404-common_voice_en_25190406",
+    "common_voice_en_25190404-common_voice_en_25190411",
+    "common_voice_en_25257658-common_voice_en_25257662",
+    "common_voice_en_25271639-common_voice_en_25271686",
+    "common_voice_en_25346256-common_voice_en_25346259",
+    "common_voice_en_25347734-common_voice_en_25347732",
+    "common_voice_en_25568854-common_voice_en_25568851",
+    "common_voice_en_25693607-common_voice_en_25693608",
+    "common_voice_en_25694807-common_voice_en_25694818",
+    "common_voice_en_25879467-common_voice_en_25879468",
+    "common_voice_en_25879467-common_voice_en_25879469",
+    "common_voice_en_25880669-common_voice_en_25880691",
+    "common_voice_en_26453369-common_voice_en_26453364",
+    "common_voice_en_27015814-common_voice_en_27015815",
+    "common_voice_en_27099623-common_voice_en_27099624",
+    "common_voice_en_27172977-common_voice_en_27172978",
+    "common_voice_en_27383934-common_voice_en_27383932",
+    "common_voice_en_27434681-common_voice_en_27434685",
+    "common_voice_en_27573778-common_voice_en_27573780",
+    "common_voice_en_27612070-common_voice_en_27612071",
+    "common_voice_en_27733062-common_voice_en_27733065",
+    "common_voice_en_27794266-common_voice_en_27794264",
+    "common_voice_en_27856404-common_voice_en_27856406",
+    "common_voice_en_27935469-common_voice_en_27935467",
+    "common_voice_en_28003405-common_voice_en_28003409",
+    "common_voice_en_28064064-common_voice_en_28064058",
+    "common_voice_en_28132727-common_voice_en_28132728",
+    "common_voice_en_28243259-common_voice_en_28243258",
+    "common_voice_en_28485171-common_voice_en_28485174",
+    "common_voice_en_28638628-common_voice_en_28638714",
+    "common_voice_en_28717453-common_voice_en_28717472",
+    "common_voice_en_28827679-common_voice_en_28827680",
+    "common_voice_en_28894436-common_voice_en_28894442",
+    "common_voice_en_28917649-common_voice_en_28917650",
+    "common_voice_en_30471104-common_voice_en_30471105",
+    "common_voice_en_30619661-common_voice_en_30619662",
+    "common_voice_en_30883223-common_voice_en_30883220",
+    "common_voice_en_31892400-common_voice_en_31892404",
+    "common_voice_en_31959919-common_voice_en_31959922",
+    "common_voice_en_31959919-common_voice_en_31959927",
+    "common_voice_en_32111431-common_voice_en_32111430",
+    "common_voice_en_32174871-common_voice_en_32174874",
+    "common_voice_en_32279839-common_voice_en_32279841",
+    "common_voice_en_32717587-common_voice_en_32717583",
+    "common_voice_en_33966405-common_voice_en_33966407",
+    "common_voice_en_34184701-common_voice_en_34184697",
+    "common_voice_en_34980363-common_voice_en_34980362",
+    "common_voice_en_35130119-common_voice_en_35130116",
+    "common_voice_en_36705534-common_voice_en_36705530",
+    "common_voice_en_36705534-common_voice_en_36705545",
+    "common_voice_en_37047577-common_voice_en_37047572",
+    "common_voice_en_37203804-common_voice_en_37203803",
+    "common_voice_en_37232389-common_voice_en_37190784",
+    "common_voice_en_37360566-common_voice_en_37360564",
+    "common_voice_en_37368335-common_voice_en_37368338",
+    "common_voice_en_37457199-common_voice_en_37457214",
+    "common_voice_en_37470753-common_voice_en_37470743",
+    "common_voice_en_37470753-common_voice_en_37470745",
+    "common_voice_en_37793802-common_voice_en_37793816",
+    "common_voice_en_484174-common_voice_en_484173",
+    "common_voice_en_489724-common_voice_en_489725",
+    "common_voice_en_509177-common_voice_en_509186",
+    "common_voice_en_519777-common_voice_en_519776",
+    "common_voice_en_537766-common_voice_en_537767",
+    "common_voice_en_537766-common_voice_en_537768",
+    "common_voice_en_541573-common_voice_en_541571",
+    "common_voice_en_550301-common_voice_en_550302",
+    "common_voice_en_554379-common_voice_en_554380",
+    "common_voice_en_557458-common_voice_en_557460",
+    "common_voice_en_563060-common_voice_en_563064",
+    "common_voice_en_565900-common_voice_en_565901",
+    "common_voice_en_568078-common_voice_en_568079",
+    "common_voice_en_570619-common_voice_en_570620",
+    "common_voice_en_581024-common_voice_en_581027",
+    "common_voice_en_581024-common_voice_en_581028",
+    "common_voice_en_586741-common_voice_en_586737",
+    "common_voice_en_590785-common_voice_en_590794",
+    "common_voice_en_593372-common_voice_en_593374",
+    "common_voice_en_597578-common_voice_en_597577",
+    "common_voice_en_597578-common_voice_en_597583",
+    "common_voice_en_599060-common_voice_en_599063",
+    "common_voice_en_599060-common_voice_en_599064",
+    "common_voice_en_606373-common_voice_en_606378",
+    "common_voice_en_631730-common_voice_en_631731",
+    "common_voice_en_64065-common_voice_en_64062",
+    "common_voice_en_664748-common_voice_en_664751",
+    "common_voice_en_678682-common_voice_en_678679",
+    "common_voice_en_678682-common_voice_en_678684",
+    "common_voice_en_684395-common_voice_en_684398",
+    "common_voice_en_68569-common_voice_en_68570",
+    "common_voice_en_691043-common_voice_en_691044",
+    "common_voice_en_691678-common_voice_en_691680",
+    "common_voice_en_691678-common_voice_en_691681",
+    "common_voice_en_699384-common_voice_en_699385",
+    "common_voice_en_71427-common_voice_en_71423",
+    "common_voice_en_86172-common_voice_en_86171",
+    "common_voice_en_93674-common_voice_en_93672"
+  ],
+  "margins": {
+    "wer_percentage_points": 0.2,
+    "sim_x100_drop": 0.5,
+    "utmos_drop": 0.05
+  },
+  "statistic": "Same frozen paired prompt bootstrap implementation, 20000 draws seed20261022; every one-sided95 degradation bound must meet its margin. Report as integration regression, not independent holdout inference.",
+  "performance_gate": "Every C16 and C32 candidate run must exceed every latest-main baseline run; report all six cells and tradeoffs.",
+  "driver_sha256": "0c66908c5959e3b91e5a091af5cf2a6382443c3ba0c416d6917e7af3aef3222b",
+  "quality_function_sha256": "0ada2681a11defe5c5ae8b825786b5b4ec5c38cdc3838f539375257c6d5bd67a",
+  "validator_sha256": "5d0f285b1bc40d75bda704c58db10e8e200c4070d22305c043ece0567a45f7d8"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/integrated-resolved-config.json b/evidence/minicpmo45-l20x-20261021/plan/integrated-resolved-config.json
new file mode 100644
index 000000000..a15878829
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/integrated-resolved-config.json
@@ -0,0 +1,370 @@
+{
+  "verdict": "PASS",
+  "scope": "Resolved settings only, not runtime or speech qualification",
+  "effective_changes": [
+    "cuda_mps=true",
+    "token2wav_spk_cpu_reference=true"
+  ],
+  "baseline": {
+    "pipeline": "minicpmo_4_5",
+    "async_chunk": true,
+    "session_mode": "turn",
+    "duplex_session": {
+      "max_sessions": 16
+    },
+    "trust_remote_code": true,
+    "enable_prefix_caching": false,
+    "connectors": {
+      "connector_of_shared_memory": {
+        "name": "SharedMemoryConnector",
+        "extra": {
+          "connector_get_sleep_s": 0.01,
+          "connector_get_max_wait_first_chunk": 3000,
+          "connector_get_max_wait": 300,
+          "codec_chunk_frames": 25,
+          "codec_left_context_frames": 3,
+          "enable_hift_graph": true,
+          "hift_graph_continuation_frames": [
+            4,
+            28
+          ],
+          "hift_graph_exact_batch_sizes": [
+            1
+          ],
+          "enable_cfm_graph": true,
+          "cfm_fused_body": true,
+          "enable_code2wav_encoder_graph": true,
+          "code2wav_encoder_graph_rows": 4,
+          "code2wav_encoder_max_graphs": 12,
+          "code2wav_encoder_capture_after": 8,
+          "max_graph_batch": 32,
+          "micro_batch_size": 4,
+          "cfm_precapture_empty_cache": true,
+          "cfm_max_graphs": 32
+        }
+      }
+    },
+    "stages": [
+      {
+        "stage_id": 0,
+        "max_num_seqs": 16,
+        "gpu_memory_utilization": 0.55,
+        "enforce_eager": false,
+        "tensor_parallel_size": 1,
+        "max_num_batched_tokens": 16384,
+        "devices": "0",
+        "interleave_mm_strings": true,
+        "media_io_kwargs": {
+          "video": {
+            "fps": 1,
+            "num_frames": 128
+          }
+        },
+        "limit_mm_per_prompt": {
+          "image": 64,
+          "audio": 64,
+          "video": 1
+        },
+        "default_sampling_params": {
+          "temperature": 0.0,
+          "top_p": 1.0,
+          "top_k": -1,
+          "max_tokens": 2048,
+          "seed": 42,
+          "detokenize": true,
+          "repetition_penalty": 1.0
+        }
+      },
+      {
+        "stage_id": 1,
+        "max_num_seqs": 16,
+        "gpu_memory_utilization": 0.15,
+        "enforce_eager": false,
+        "max_num_batched_tokens": 8192,
+        "max_model_len": 4096,
+        "devices": "0",
+        "output_connectors": {
+          "to_stage_2": "connector_of_shared_memory"
+        },
+        "default_sampling_params": {
+          "temperature": 0.8,
+          "top_p": 0.85,
+          "top_k": 25,
+          "repetition_penalty": 1.05,
+          "min_tokens": 50,
+          "max_tokens": 4096,
+          "seed": 42,
+          "detokenize": false
+        }
+      },
+      {
+        "stage_id": 2,
+        "max_num_seqs": 16,
+        "gpu_memory_utilization": 0.18,
+        "enforce_eager": true,
+        "enable_chunked_prefill": false,
+        "max_num_batched_tokens": 65536,
+        "max_model_len": 65536,
+        "devices": "0",
+        "input_connectors": {
+          "from_stage_1": "connector_of_shared_memory"
+        },
+        "default_sampling_params": {
+          "temperature": 0.0,
+          "top_p": 1.0,
+          "top_k": -1,
+          "max_tokens": 65536,
+          "detokenize": true
+        }
+      }
+    ],
+    "platforms": {
+      "cuda": {
+        "stages": [
+          {
+            "stage_id": 1,
+            "kv_cache_memory_bytes": 4294967296
+          }
+        ]
+      },
+      "npu": {
+        "stages": [
+          {
+            "stage_id": 0,
+            "max_num_seqs": 8,
+            "gpu_memory_utilization": 0.55,
+            "additional_config": {
+              "encoder_enable_npu_graph": true,
+              "encoder_max_npu_graphs": 4
+            },
+            "max_num_batched_tokens": 8192,
+            "enable_prefix_caching": false,
+            "compilation_config": {
+              "cudagraph_mode": "PIECEWISE"
+            }
+          },
+          {
+            "stage_id": 1,
+            "max_num_seqs": 8,
+            "kv_cache_memory_bytes": 4294967296,
+            "gpu_memory_utilization": 0.1,
+            "max_num_batched_tokens": 8192,
+            "speculative_config": {
+              "method": "ngram",
+              "num_speculative_tokens": 7,
+              "prompt_lookup_min": 1,
+              "prompt_lookup_max": 1
+            },
+            "async_scheduling": false,
+            "default_sampling_params": {
+              "stop_token_ids": [
+                1
+              ]
+            },
+            "compilation_config": {
+              "cudagraph_mode": "FULL_DECODE_ONLY"
+            }
+          },
+          {
+            "stage_id": 2,
+            "max_num_seqs": 8,
+            "gpu_memory_utilization": 0.22,
+            "additional_config": {
+              "code2wav_enable_npu_graph": true,
+              "cfm_graph_batch_buckets": [
+                1,
+                2,
+                4,
+                8
+              ],
+              "code2wav_max_npu_graphs": 32
+            }
+          }
+        ]
+      }
+    }
+  },
+  "candidate": {
+    "pipeline": "minicpmo_4_5",
+    "async_chunk": true,
+    "session_mode": "turn",
+    "duplex_session": {
+      "max_sessions": 16
+    },
+    "trust_remote_code": true,
+    "enable_prefix_caching": false,
+    "connectors": {
+      "connector_of_shared_memory": {
+        "name": "SharedMemoryConnector",
+        "extra": {
+          "connector_get_sleep_s": 0.01,
+          "connector_get_max_wait_first_chunk": 3000,
+          "connector_get_max_wait": 300,
+          "codec_chunk_frames": 25,
+          "codec_left_context_frames": 3,
+          "enable_hift_graph": true,
+          "hift_graph_continuation_frames": [
+            4,
+            28
+          ],
+          "hift_graph_exact_batch_sizes": [
+            1
+          ],
+          "enable_cfm_graph": true,
+          "cfm_fused_body": true,
+          "enable_code2wav_encoder_graph": true,
+          "code2wav_encoder_graph_rows": 4,
+          "code2wav_encoder_max_graphs": 12,
+          "code2wav_encoder_capture_after": 8,
+          "max_graph_batch": 32,
+          "micro_batch_size": 4,
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+    ],
+    "platforms": {
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+        ]
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+            }
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+            "async_scheduling": false,
+            "default_sampling_params": {
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+            "compilation_config": {
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+            }
+          },
+          {
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+                2,
+                4,
+                8
+              ],
+              "code2wav_max_npu_graphs": 32
+            }
+          }
+        ]
+      }
+    },
+    "cuda_mps": true
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/integrated-speaker-micro.json b/evidence/minicpmo45-l20x-20261021/results/integrated-speaker-micro.json
new file mode 100644
index 000000000..6d5197e9e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/integrated-speaker-micro.json
@@ -0,0 +1,327 @@
+{
+  "verdict": "PASS",
+  "scope": "isolated speaker embedding only",
+  "backend": "trt",
+  "cpu_reference": true,
+  "asset_sha256": "a6ac6a63997761ae2997373e2ee1c47040854b4b759ea41ec48e4e42df0f4d73",
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+      "max_normalized_abs_error": 7.562339305877686e-07
+    },
+    {
+      "id": "common_voice_en_19967495-common_voice_en_19967497",
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+    },
+    {
+      "id": "common_voice_en_21555942-common_voice_en_21555950",
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+      "max_normalized_abs_error": 3.948807716369629e-07
+    },
+    {
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+      "max_normalized_abs_error": 4.172325134277344e-07
+    },
+    {
+      "id": "common_voice_en_20236234-common_voice_en_20236233",
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+      "input_sha256": "81b509425418da0bcbbededcbb6793b75b94ec0e9bb5942d25025672c778754e",
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+      "max_normalized_abs_error": 3.0547380447387695e-07
+    },
+    {
+      "id": "common_voice_en_32144882-common_voice_en_32144886",
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+    },
+    {
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+    {
+      "id": "common_voice_en_523215-common_voice_en_523219",
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+    },
+    {
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+    },
+    {
+      "id": "common_voice_en_20303932-common_voice_en_20303934",
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+      "cosine": 0.9999999403953552,
+      "max_normalized_abs_error": 2.551823854446411e-07
+    },
+    {
+      "id": "common_voice_en_19619551-common_voice_en_19619549",
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+      "input_sha256": "242973e0f62b45ca442894fe5c81b73d9f4c8edc92fea48cde589077e336959b",
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+      "max_normalized_abs_error": 2.2426247596740723e-06
+    },
+    {
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+      "max_normalized_abs_error": 5.21540641784668e-07
+    },
+    {
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+    {
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+    },
+    {
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+      "max_normalized_abs_error": 2.980232238769531e-07
+    },
+    {
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+    },
+    {
+      "id": "common_voice_en_9559-common_voice_en_9560",
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+    {
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+    {
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+    {
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+    },
+    {
+      "id": "common_voice_en_37368335-common_voice_en_37368333",
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+    {
+      "id": "common_voice_en_25896925-common_voice_en_25896927",
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+      "cosine": 1.0000001192092896,
+      "max_normalized_abs_error": 3.2782554626464844e-07
+    },
+    {
+      "id": "common_voice_en_20065698-common_voice_en_20065702",
+      "frames": 598,
+      "input_sha256": "b3c11d06d6ee90ccd421961e93e77a168198a198e986795ae68b04585b0afd9e",
+      "cosine": 1.0000001192092896,
+      "max_normalized_abs_error": 5.364418029785156e-07
+    },
+    {
+      "id": "common_voice_en_19819944-common_voice_en_19819946",
+      "frames": 598,
+      "input_sha256": "01e3b142199627771e3286cb1b58c98f2ed4d27675cc5b84338af7bdf892438e",
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+      "max_normalized_abs_error": 3.688037395477295e-07
+    },
+    {
+      "id": "common_voice_en_17281385-common_voice_en_17281386",
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+      "max_normalized_abs_error": 3.427267074584961e-07
+    },
+    {
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+      "input_sha256": "801a552786736c6119d22a33eb6b5654e3e43d37adcb417ac95ffd9aa2512f54",
+      "cosine": 1.0000001192092896,
+      "max_normalized_abs_error": 2.980232238769531e-07
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+    {
+      "id": "common_voice_en_19254683-common_voice_en_19254687-short97",
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+      "input_sha256": "40ec462baf3c235271adc6d07bdc93287508f1ccf64a2d8a83a41f868a941b97",
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+      "max_normalized_abs_error": 1.5944242477416992e-06
+    },
+    {
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+      "max_normalized_abs_error": 4.507601261138916e-07
+    }
+  ],
+  "latency": {
+    "cpu_onnx": {
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+      "samples_ms": [
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+    },
+    "trt": {
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+      "samples_ms": [
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+        4.27979975938797,
+        4.284575581550598,
+        4.289397969841957
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+    }
+  },
+  "settings": {
+    "torch": "2.13.0+cu130",
+    "cuda": "13.0",
+    "cudnn_allow_tf32": true,
+    "matmul_allow_tf32": false
+  }
+}
\ No newline at end of file
diff --git a/evidence/minicpmo45-l20x-20261021/results/status.json b/evidence/minicpmo45-l20x-20261021/results/status.json
index b27d24d5f..120b1e0ee 100644
--- a/evidence/minicpmo45-l20x-20261021/results/status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/status.json
@@ -8,13 +8,15 @@
   },
   "optimization_submitted": true,
   "pending": [
-    "speaker+MPS repeated benchmark and quality",
-    "fresh-start confirmation",
-    "separately authorized unused-holdout noninferiority"
+    "original unused-holdout noninferiority",
+    "updated-main and adapted-candidate repeated service comparison",
+    "adapted-candidate quality regression against updated main"
   ],
   "candidate_pull_request": "https://github.com/vllm-project/vllm-omni/pull/9188",
   "candidate_cpu_tests_passed": 67,
   "candidate_tuning": "C16/C32 gains observed; held-out repeated service and generated speech quality pending",
   "original_strict_speaker_verdict": "FAIL",
-  "knowledge_pull_request": "https://github.com/InferMatrixLab/InferRSI/pull/51"
+  "knowledge_pull_request": "https://github.com/InferMatrixLab/InferRSI/pull/51",
+  "final_candidate_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc",
+  "updated_baseline_revision": "15bce34586"
 }
diff --git a/evidence/minicpmo45-l20x-20261021/validator/integrated-checks.json b/evidence/minicpmo45-l20x-20261021/validator/integrated-checks.json
new file mode 100644
index 000000000..d0c1ae58b
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/integrated-checks.json
@@ -0,0 +1,10 @@
+{
+  "cpu_tests": {
+    "passed": 108,
+    "warnings": 16
+  },
+  "changed_file_precommit": "PASS",
+  "full_tree_precommit": "Stopped after markdown formatter modified 110 unrelated pre-existing documents; those formatter-only changes were restored. This is not claimed as a full-tree PASS.",
+  "numerical_component": "PASS: integrated-speaker-micro.json; first launch omitted explicit dataset root and was rerun with the frozen dataset path.",
+  "source_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/integrated_comparison.py b/evidence/minicpmo45-l20x-20261021/validator/integrated_comparison.py
new file mode 100644
index 000000000..813709682
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/integrated_comparison.py
@@ -0,0 +1,79 @@
+"""Validate updated-main integration; reused cohort, not an untouched holdout."""
+
+import argparse
+import json
+from pathlib import Path
+
+from noninferiority import evaluate
+from summarize_results import aggregate
+
+
+def main():
+    p = argparse.ArgumentParser(description=__doc__)
+    p.add_argument("--baseline", type=Path, required=True)
+    p.add_argument("--candidate", type=Path, required=True)
+    p.add_argument("--quality-dir", type=Path, required=True)
+    p.add_argument("--plan", type=Path, required=True)
+    p.add_argument("--out", type=Path, required=True)
+    a = p.parse_args()
+    plan = json.loads(a.plan.read_text())
+    report = {
+        "scope": plan["scope"],
+        "baseline": aggregate(a.baseline),
+        "candidate": aggregate(a.candidate),
+        "quality": {},
+        "performance": [],
+    }
+    try:
+        for root in (a.baseline, a.candidate):
+            for c in plan["concurrency"]:
+                for k in range(1, plan["measured_repeats"] + 1):
+                    folder = root / f"c{c}/run{k}"
+                    summary = json.loads((folder / "summary.json").read_text())
+                    if not summary["valid"] or summary["n_failed"] or summary["n_requests"] != 320:
+                        raise ValueError("Invalid measured run")
+                    requests = [
+                        json.loads(line)
+                        for line in (folder / "requests.jsonl").read_text().splitlines()
+                    ]
+                    if len(requests) != 320 or {x["request_id"] for x in requests} != set(
+                        plan["expected_ids"]
+                    ):
+                        raise ValueError("Wrong measured prompt coverage")
+        for c in plan["quality_concurrency"]:
+            docs = [
+                json.loads((a.quality_dir / f"{prefix}-c{c}.json").read_text())
+                for prefix in ("vllm-latest-main", "vllm-integrated-candidate")
+            ]
+            if any(set(d["rows"]) != set(plan["expected_ids"]) for d in docs):
+                raise ValueError("Wrong quality prompt coverage")
+            report["quality"][str(c)] = evaluate(*docs, plan["margins"])
+            report["quality"][str(c)]["means"] = {
+                "baseline": docs[0]["summary"],
+                "candidate": docs[1]["summary"],
+            }
+        for c in (16, 32):
+            b, d = [
+                next(v for v in report[key] if v["concurrency"] == c)
+                for key in ("baseline", "candidate")
+            ]
+            passed = min(d["throughput_frames_s_runs"]) > max(b["throughput_frames_s_runs"])
+            report["performance"].append(
+                {
+                    "concurrency": c,
+                    "gain_ratio": d["throughput_frames_s_mean"] / b["throughput_frames_s_mean"],
+                    "all_candidate_runs_exceed_all_baseline_runs": passed,
+                }
+            )
+        passed = all(v["verdict"] == "PASS" for v in report["quality"].values()) and all(
+            v["all_candidate_runs_exceed_all_baseline_runs"] for v in report["performance"]
+        )
+        report["verdict"] = "PASS" if passed else "FAIL"
+    except (OSError, ValueError, KeyError, StopIteration) as exc:
+        report.update(verdict="INCONCLUSIVE", reason=str(exc))
+    a.out.write_text(json.dumps(report, indent=2) + "\n")
+    print(json.dumps({"verdict": report["verdict"], "scope": report["scope"]}))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/integration-equivalence.json b/evidence/minicpmo45-l20x-20261021/validator/integration-equivalence.json
new file mode 100644
index 000000000..30fbf778a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/integration-equivalence.json
@@ -0,0 +1,9 @@
+{
+  "scope": "Speaker implementation source equality only; coordinator and default backend changes still require separate service comparison.",
+  "speaker_module_identical": true,
+  "speaker_module_sha256": "310129b4283200a71221e813185d14ef9b44873df1147e1d1e2a68baeff2d755",
+  "core_enable_trt_spk_embedding_ast_identical": true,
+  "routing_validation": "108 CPU tests passed, including explicit opt-in and preserved upstream defaults",
+  "historical_revision": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
+  "adapted_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/validate_integrated_config.py b/evidence/minicpmo45-l20x-20261021/validator/validate_integrated_config.py
new file mode 100644
index 000000000..d1cd97640
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/validate_integrated_config.py
@@ -0,0 +1,49 @@
+"""Check that the selected overlay changes only the declared effective knobs."""
+
+import argparse
+import copy
+import json
+from pathlib import Path
+
+from vllm_omni.config.stage_config import resolve_deploy_yaml
+
+
+def main():
+    p = argparse.ArgumentParser(description=__doc__)
+    p.add_argument("--deploy-dir", type=Path, required=True)
+    p.add_argument("--out", type=Path, required=True)
+    a = p.parse_args()
+    baseline = resolve_deploy_yaml(a.deploy_dir / "minicpmo_4_5_turn.yaml")
+    candidate = resolve_deploy_yaml(a.deploy_dir / "minicpmo_4_5_cpu_reference_trt_mps.yaml")
+    normalized = copy.deepcopy(candidate)
+    assert normalized["cuda_mps"] is True
+    if "cuda_mps" in baseline:
+        normalized["cuda_mps"] = baseline["cuda_mps"]
+    else:
+        normalized.pop("cuda_mps")
+    extra = normalized["connectors"]["connector_of_shared_memory"]["extra"]
+    base_extra = baseline["connectors"]["connector_of_shared_memory"]["extra"]
+    assert extra.pop("token2wav_spk_cpu_reference") is True
+    for key, default in [("token2wav_device_spk", True), ("token2wav_trt", False)]:
+        assert extra.pop(key) is base_extra.get(key, default)
+        if key in base_extra:
+            extra[key] = base_extra[key]
+    assert normalized == baseline
+    a.out.write_text(
+        json.dumps(
+            {
+                "verdict": "PASS",
+                "scope": "Resolved settings only, not runtime or speech qualification",
+                "effective_changes": ["cuda_mps=true", "token2wav_spk_cpu_reference=true"],
+                "baseline": baseline,
+                "candidate": candidate,
+            },
+            indent=2,
+        )
+        + "\n"
+    )
+    print("PASS: only declared MPS and CPU-reference speaker settings differ")
+
+
+if __name__ == "__main__":
+    main()

From 9da75dcf655407d86aaeae1cda9c422abb801b9e Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 12:35:33 +0800
Subject: [PATCH 09/40] Archive failed noninferiority holdout without excluding
 error tails

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |  14 +-
 .../patch/integrated-candidate.json           |   6 +-
 .../patch/latest-main-mps-only.yaml           |   2 +
 .../integrated-same-gpu-confirmation.json     |  18 ++
 .../plan/latest-main-mps-attribution.json     |  20 +++
 .../results/holdout-error-attribution.json    | 155 ++++++++++++++++++
 .../results/holdout-quality.json.gz           | Bin 0 -> 148413 bytes
 .../results/noninferiority-holdout.json       |  78 +++++++++
 .../results/outlier-asr-repeat.json           | 102 ++++++++++++
 .../results/status.json                       |   9 +-
 .../results/vllm-holdout-candidate.json.gz    | Bin 0 -> 277150 bytes
 .../results/vllm-holdout-main.json.gz         | Bin 0 -> 283985 bytes
 .../validator/plot_final_results.py           |  81 +++++++++
 .../validator/rescore_saved_wav.py            |  53 ++++++
 14 files changed, 533 insertions(+), 5 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/latest-main-mps-only.yaml
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/integrated-same-gpu-confirmation.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/latest-main-mps-attribution.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/holdout-error-attribution.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/holdout-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/noninferiority-holdout.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/outlier-asr-repeat.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-holdout-candidate.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-holdout-main.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/rescore_saved_wav.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 0c1b5695f..64fdbc4f2 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -2,7 +2,7 @@
 
 Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
 
-**Original strict quality verdict: FAIL** for the completed speaker-only candidate. A separately authorized noninferiority evaluation on previously unused prompts is pending; it does not change the original verdict. Component PASS does not establish service PASS.
+**Original strict quality verdict: FAIL** for the completed speaker-only candidate. The separately authorized noninferiority evaluation on previously unused prompts also **FAILS** on C16/C32 WER. Updated-main integration is assessed separately; neither new comparison changes those verdicts. Component PASS does not establish service PASS.
 
 ## Scope and controls
 
@@ -211,3 +211,15 @@ original unused-cohort decision remains separately scoped to the historical
 candidate. Source equality checks in `validator/integration-equivalence.json`
 cover the speaker implementation only; updated coordinator behavior still
 requires the separate service comparison.
+
+## Untouched-cohort noninferiority result: FAIL
+
+The frozen historical candidate fails the authorized quality bounds. All 320 prompts are retained in each cell. Values below are degradation and its one-sided 95% upper bound; negative degradation means improvement. WER is in percentage points, SIM is on the ×100 scale.
+
+| C | WER delta / upper (margin 0.20) | SIM drop / upper (margin 0.50) | UTMOS drop / upper (margin 0.05) | Verdict |
+|---|---:|---:|---:|---|
+| 1 | 0.0289 / 0.0871 | -0.0792 / -0.0196 | 0.0008 / 0.0063 | PASS |
+| 16 | 0.4047 / 0.9043 | -0.1930 / 0.2013 | 0.0027 / 0.0201 | FAIL |
+| 32 | 1.4166 / 4.7298 | 0.0946 / 0.5000 | 0.0246 / 0.0430 | FAIL |
+
+At C32, a single prompt contributes 57 additional errors against a net total increase of 49. Both baseline and candidate already transcribe poorly on that prompt; the candidate C32 ASR result reproduces exactly on three resubmissions of its saved WAV. Baseline C32 resubmissions agree with each other but differ from its original ASR text by one whitespace token. These diagnostics do not delete the prompt, clip its WER, replace frozen scores, or establish a causal model defect. See `results/holdout-error-attribution.json` and `results/outlier-asr-repeat.json`.
diff --git a/evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json b/evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json
index 27257f749..b36f7fe92 100644
--- a/evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json
+++ b/evidence/minicpmo45-l20x-20261021/patch/integrated-candidate.json
@@ -7,5 +7,9 @@
   "default_policy": "Preserve upstream Torch CUDA/NPU speaker defaults; optional CPU-reference TRT requires CUDA and excludes full DiT TRT.",
   "historical_candidate_revision": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
   "history": "Historical measured candidate retained as an ancestor; adapted feature is based on updated upstream main.",
-  "shared_speaker_implementation_sha256": "310129b4283200a71221e813185d14ef9b44873df1147e1d1e2a68baeff2d755"
+  "shared_speaker_implementation_sha256": "310129b4283200a71221e813185d14ef9b44873df1147e1d1e2a68baeff2d755",
+  "pull_request_head": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "measured_tree_sha": "13576ddebdee80ab9d8832ef58785116e8749acf",
+  "pull_request_head_tree_sha": "13576ddebdee80ab9d8832ef58785116e8749acf",
+  "metadata_only_followup": "Empty signed commit refreshes CI after PR base was updated; its entire Git tree equals measured revision 227a43e898."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/patch/latest-main-mps-only.yaml b/evidence/minicpmo45-l20x-20261021/patch/latest-main-mps-only.yaml
new file mode 100644
index 000000000..005de4328
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/latest-main-mps-only.yaml
@@ -0,0 +1,2 @@
+base_config: minicpmo_4_5_turn.yaml
+cuda_mps: true
diff --git a/evidence/minicpmo45-l20x-20261021/plan/integrated-same-gpu-confirmation.json b/evidence/minicpmo45-l20x-20261021/plan/integrated-same-gpu-confirmation.json
new file mode 100644
index 000000000..e049019bd
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/integrated-same-gpu-confirmation.json
@@ -0,0 +1,18 @@
+{
+  "frozen_at_utc": "2026-10-21T04:30:07.962492+00:00",
+  "purpose": "Confirm updated-main versus integrated-candidate throughput direction on the same physical GPU, since the full matrices use separate reserved L20X cards.",
+  "baseline_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "candidate_measured_tree_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc",
+  "candidate_head_metadata_only": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "candidate_profile": "minicpmo_4_5_cpu_reference_trt_mps.yaml",
+  "concurrency": [
+    16,
+    32
+  ],
+  "requests": 320,
+  "discard_runs": 1,
+  "measured_repeats": 1,
+  "pool": "first320 eval, already used",
+  "sequence": "fresh latest main, cleanup, fresh selected candidate on the same reservation",
+  "limits": "Single ordered repeat, not a new statistical quality holdout or ABBA certification; unchanged sampling/scorers/thresholds."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/latest-main-mps-attribution.json b/evidence/minicpmo45-l20x-20261021/plan/latest-main-mps-attribution.json
new file mode 100644
index 000000000..b43fd68bd
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/latest-main-mps-attribution.json
@@ -0,0 +1,20 @@
+{
+  "frozen_at_utc": "2026-10-21T04:33:14.503627+00:00",
+  "purpose": "Disentangle the already available MPS switch from the new CPU-reference backend after upstream #9178 enabled Torch CUDA speaker extraction. This is a one-plane attribution control, not another selected candidate or untouched quality holdout.",
+  "baseline_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "profile_changes": {
+    "cuda_mps": true
+  },
+  "speaker_backend": "upstream Torch default",
+  "device": "same physical GPU as final sequential main/candidate confirmation, queued after it releases",
+  "concurrency": [
+    16,
+    32
+  ],
+  "requests": 320,
+  "discard_runs": 1,
+  "measured_repeats": 1,
+  "pool": "same first320 eval rows",
+  "quality": "Descriptive native scoring of the same two saved run1 cohorts; no all-concurrency noninferiority claim.",
+  "stop": "Complete this fixed control; retain all outcomes without retuning or changing margins."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/holdout-error-attribution.json b/evidence/minicpmo45-l20x-20261021/results/holdout-error-attribution.json
new file mode 100644
index 000000000..c09c66206
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/holdout-error-attribution.json
@@ -0,0 +1,155 @@
+{
+  "scope": "Post-failure attribution only. All prompts remain in the frozen decision. No clipped WER, outlier deletion or threshold change.",
+  "cells": {
+    "1": {
+      "net_extra_errors": 1,
+      "largest_increases": [
+        {
+          "id": "common_voice_en_19717736-common_voice_en_19717739",
+          "error_delta": 1,
+          "baseline_errors": 0,
+          "candidate_errors": 1,
+          "reference_words": 3,
+          "baseline_duration_s": 2.12,
+          "candidate_duration_s": 2.12
+        },
+        {
+          "id": "common_voice_en_103675-common_voice_en_103677",
+          "error_delta": 0,
+          "baseline_errors": 0,
+          "candidate_errors": 0,
+          "reference_words": 8,
+          "baseline_duration_s": 2.8,
+          "candidate_duration_s": 2.8
+        },
+        {
+          "id": "common_voice_en_1205005-common_voice_en_1205008",
+          "error_delta": 0,
+          "baseline_errors": 0,
+          "candidate_errors": 0,
+          "reference_words": 7,
+          "baseline_duration_s": 2.96,
+          "candidate_duration_s": 2.96
+        },
+        {
+          "id": "common_voice_en_123125-common_voice_en_123126",
+          "error_delta": 0,
+          "baseline_errors": 2,
+          "candidate_errors": 2,
+          "reference_words": 14,
+          "baseline_duration_s": 5.44,
+          "candidate_duration_s": 5.44
+        },
+        {
+          "id": "common_voice_en_1416089-common_voice_en_1416093",
+          "error_delta": 0,
+          "baseline_errors": 0,
+          "candidate_errors": 0,
+          "reference_words": 13,
+          "baseline_duration_s": 4.56,
+          "candidate_duration_s": 4.56
+        }
+      ]
+    },
+    "16": {
+      "net_extra_errors": 14,
+      "largest_increases": [
+        {
+          "id": "common_voice_en_20006910-common_voice_en_20006912",
+          "error_delta": 8,
+          "baseline_errors": 24,
+          "candidate_errors": 32,
+          "reference_words": 9,
+          "baseline_duration_s": 18.6,
+          "candidate_duration_s": 29.0
+        },
+        {
+          "id": "common_voice_en_18105426-common_voice_en_18105428",
+          "error_delta": 4,
+          "baseline_errors": 0,
+          "candidate_errors": 4,
+          "reference_words": 4,
+          "baseline_duration_s": 2.32,
+          "candidate_duration_s": 3.6
+        },
+        {
+          "id": "common_voice_en_19049396-common_voice_en_19049393",
+          "error_delta": 2,
+          "baseline_errors": 0,
+          "candidate_errors": 2,
+          "reference_words": 15,
+          "baseline_duration_s": 5.04,
+          "candidate_duration_s": 5.12
+        },
+        {
+          "id": "common_voice_en_18200641-common_voice_en_18200765",
+          "error_delta": 1,
+          "baseline_errors": 0,
+          "candidate_errors": 1,
+          "reference_words": 15,
+          "baseline_duration_s": 6.68,
+          "candidate_duration_s": 6.72
+        },
+        {
+          "id": "common_voice_en_19979514-common_voice_en_19979517",
+          "error_delta": 1,
+          "baseline_errors": 0,
+          "candidate_errors": 1,
+          "reference_words": 9,
+          "baseline_duration_s": 4.12,
+          "candidate_duration_s": 3.32
+        }
+      ]
+    },
+    "32": {
+      "net_extra_errors": 49,
+      "largest_increases": [
+        {
+          "id": "common_voice_en_20006910-common_voice_en_20006912",
+          "error_delta": 57,
+          "baseline_errors": 38,
+          "candidate_errors": 95,
+          "reference_words": 9,
+          "baseline_duration_s": 30.32,
+          "candidate_duration_s": 18.6
+        },
+        {
+          "id": "common_voice_en_18200641-common_voice_en_18200765",
+          "error_delta": 1,
+          "baseline_errors": 0,
+          "candidate_errors": 1,
+          "reference_words": 15,
+          "baseline_duration_s": 6.64,
+          "candidate_duration_s": 6.72
+        },
+        {
+          "id": "common_voice_en_19695366-common_voice_en_19695364",
+          "error_delta": 1,
+          "baseline_errors": 1,
+          "candidate_errors": 2,
+          "reference_words": 14,
+          "baseline_duration_s": 6.4,
+          "candidate_duration_s": 7.0
+        },
+        {
+          "id": "common_voice_en_103675-common_voice_en_103677",
+          "error_delta": 0,
+          "baseline_errors": 0,
+          "candidate_errors": 0,
+          "reference_words": 8,
+          "baseline_duration_s": 2.8,
+          "candidate_duration_s": 2.52
+        },
+        {
+          "id": "common_voice_en_1205005-common_voice_en_1205008",
+          "error_delta": 0,
+          "baseline_errors": 0,
+          "candidate_errors": 0,
+          "reference_words": 7,
+          "baseline_duration_s": 3.44,
+          "candidate_duration_s": 3.24
+        }
+      ]
+    }
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/holdout-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/holdout-quality.json.gz
new file mode 100644
index 0000000000000000000000000000000000000000..807210a7aad2a7c23cba13ccd8944620210d2b08
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diff --git a/evidence/minicpmo45-l20x-20261021/results/noninferiority-holdout.json b/evidence/minicpmo45-l20x-20261021/results/noninferiority-holdout.json
new file mode 100644
index 000000000..2ed0a385b
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/noninferiority-holdout.json
@@ -0,0 +1,78 @@
+{
+  "scope": "Unused holdout noninferiority; original strict gate unchanged",
+  "cells": {
+    "1": {
+      "n": 320,
+      "metrics": {
+        "wer_percentage_points": {
+          "degradation": 0.028910089621277807,
+          "upper_one_sided_95": 0.08705745792222867,
+          "margin": 0.2,
+          "verdict": "PASS"
+        },
+        "sim_x100_drop": {
+          "degradation": -0.07919421195983886,
+          "upper_one_sided_95": -0.019602164924144752,
+          "margin": 0.5,
+          "verdict": "PASS"
+        },
+        "utmos_drop": {
+          "degradation": 0.0007672093808650971,
+          "upper_one_sided_95": 0.006295618638396261,
+          "margin": 0.05,
+          "verdict": "PASS"
+        }
+      },
+      "verdict": "PASS"
+    },
+    "16": {
+      "n": 320,
+      "metrics": {
+        "wer_percentage_points": {
+          "degradation": 0.40474125469788963,
+          "upper_one_sided_95": 0.904330580240175,
+          "margin": 0.2,
+          "verdict": "FAIL"
+        },
+        "sim_x100_drop": {
+          "degradation": -0.19301602840423585,
+          "upper_one_sided_95": 0.20127480596303937,
+          "margin": 0.5,
+          "verdict": "PASS"
+        },
+        "utmos_drop": {
+          "degradation": 0.0027266964316368103,
+          "upper_one_sided_95": 0.020062825754284856,
+          "margin": 0.05,
+          "verdict": "PASS"
+        }
+      },
+      "verdict": "FAIL"
+    },
+    "32": {
+      "n": 320,
+      "metrics": {
+        "wer_percentage_points": {
+          "degradation": 1.4165943914426136,
+          "upper_one_sided_95": 4.729768472601041,
+          "margin": 0.2,
+          "verdict": "FAIL"
+        },
+        "sim_x100_drop": {
+          "degradation": 0.09458468854427338,
+          "upper_one_sided_95": 0.4999546980857848,
+          "margin": 0.5,
+          "verdict": "PASS"
+        },
+        "utmos_drop": {
+          "degradation": 0.024590854346752167,
+          "upper_one_sided_95": 0.042992207407951344,
+          "margin": 0.05,
+          "verdict": "PASS"
+        }
+      },
+      "verdict": "FAIL"
+    }
+  },
+  "verdict": "FAIL"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/outlier-asr-repeat.json b/evidence/minicpmo45-l20x-20261021/results/outlier-asr-repeat.json
new file mode 100644
index 000000000..b55f78739
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/outlier-asr-repeat.json
@@ -0,0 +1,102 @@
+{
+  "scope": "Diagnostic only; three serial submissions of the same saved WAV to the same ASR endpoint and settings. Other scoring traffic may overlap. Does not exclude the prompt or change any frozen gate.",
+  "request_id": "common_voice_en_20006910-common_voice_en_20006912",
+  "rows": [
+    {
+      "role": "main",
+      "concurrency": 1,
+      "wav_sha256": "fc6daab6f625d96d6d26a1fc19c9dd85440d14e42d96dedca421211a577987f3",
+      "same_as_original": [
+        true,
+        true,
+        true
+      ],
+      "transcript_sha256": [
+        "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e",
+        "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e",
+        "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e"
+      ],
+      "original_transcript_sha256": "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e"
+    },
+    {
+      "role": "main",
+      "concurrency": 16,
+      "wav_sha256": "861b2b4c4a827868ec14837c7261ff472e30a6f4aa8dffbec485f529ed0b00fb",
+      "same_as_original": [
+        true,
+        true,
+        true
+      ],
+      "transcript_sha256": [
+        "e0164dab8cb03bf2e7f89462f619e7f689cbc5954e77ff71e4c1be0cea7ae8c3",
+        "e0164dab8cb03bf2e7f89462f619e7f689cbc5954e77ff71e4c1be0cea7ae8c3",
+        "e0164dab8cb03bf2e7f89462f619e7f689cbc5954e77ff71e4c1be0cea7ae8c3"
+      ],
+      "original_transcript_sha256": "e0164dab8cb03bf2e7f89462f619e7f689cbc5954e77ff71e4c1be0cea7ae8c3"
+    },
+    {
+      "role": "main",
+      "concurrency": 32,
+      "wav_sha256": "caae5c5280e665ef7776f4e298e6095de81c7694015e9e8a41daa9bb611db104",
+      "same_as_original": [
+        false,
+        false,
+        false
+      ],
+      "transcript_sha256": [
+        "081fce3a377edad61afee248b1a21683d0e3f0b1b88538271cb1bffd2ef5f6b0",
+        "081fce3a377edad61afee248b1a21683d0e3f0b1b88538271cb1bffd2ef5f6b0",
+        "081fce3a377edad61afee248b1a21683d0e3f0b1b88538271cb1bffd2ef5f6b0"
+      ],
+      "original_transcript_sha256": "0206bfec94b8cbbf77da61e2ae26258b12aa2a981d3389e3a15a6fd10d1e7d19"
+    },
+    {
+      "role": "candidate",
+      "concurrency": 1,
+      "wav_sha256": "edb85a1765bdee8f61adb0c43dc0974147e5bb372865951e624790d019ebb5e4",
+      "same_as_original": [
+        true,
+        true,
+        true
+      ],
+      "transcript_sha256": [
+        "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e",
+        "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e",
+        "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e"
+      ],
+      "original_transcript_sha256": "2aafda2ab3e02b901cd94f54f5d84dcb18a4f11f17d79b26a69a22d41fd3f09e"
+    },
+    {
+      "role": "candidate",
+      "concurrency": 16,
+      "wav_sha256": "d5c42114da79aab1ff8fca3d4f5e6faab2c9aa80e967de435fd08d573393fbaf",
+      "same_as_original": [
+        true,
+        true,
+        true
+      ],
+      "transcript_sha256": [
+        "43130beca75e9f476d45734a171d0c925874e1a7807cad0a65ca9adb6f05fb7d",
+        "43130beca75e9f476d45734a171d0c925874e1a7807cad0a65ca9adb6f05fb7d",
+        "43130beca75e9f476d45734a171d0c925874e1a7807cad0a65ca9adb6f05fb7d"
+      ],
+      "original_transcript_sha256": "43130beca75e9f476d45734a171d0c925874e1a7807cad0a65ca9adb6f05fb7d"
+    },
+    {
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+      "concurrency": 32,
+      "wav_sha256": "e36238588f51d0fbf9b6885743e684ee6350cf31b60abc43538a0dcaa42c7e17",
+      "same_as_original": [
+        true,
+        true,
+        true
+      ],
+      "transcript_sha256": [
+        "c9980509541b13e9689a2fc522e066158582b7741542ce634a5e3ae7b2a62045",
+        "c9980509541b13e9689a2fc522e066158582b7741542ce634a5e3ae7b2a62045",
+        "c9980509541b13e9689a2fc522e066158582b7741542ce634a5e3ae7b2a62045"
+      ],
+      "original_transcript_sha256": "c9980509541b13e9689a2fc522e066158582b7741542ce634a5e3ae7b2a62045"
+    }
+  ]
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/status.json b/evidence/minicpmo45-l20x-20261021/results/status.json
index 120b1e0ee..3d44455da 100644
--- a/evidence/minicpmo45-l20x-20261021/results/status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/status.json
@@ -1,5 +1,5 @@
 {
-  "verdict": "INCONCLUSIVE",
+  "verdict": "FAIL",
   "baseline": "Completed two engines at six concurrency levels, three measured 320-request repeats each; zero failed measured requests.",
   "candidate_revision": "f2462435d79f0243ced93a02f3b8d6cd9c41511b",
   "candidate_microbench": "PASS within frozen embedding gate; CPU-compatible FP32 TensorRT",
@@ -8,7 +8,6 @@
   },
   "optimization_submitted": true,
   "pending": [
-    "original unused-holdout noninferiority",
     "updated-main and adapted-candidate repeated service comparison",
     "adapted-candidate quality regression against updated main"
   ],
@@ -18,5 +17,9 @@
   "original_strict_speaker_verdict": "FAIL",
   "knowledge_pull_request": "https://github.com/InferMatrixLab/InferRSI/pull/51",
   "final_candidate_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc",
-  "updated_baseline_revision": "15bce34586"
+  "updated_baseline_revision": "15bce34586",
+  "historical_noninferiority_verdict": "FAIL",
+  "historical_noninferiority_reason": "C16 and C32 WER degradation upper bounds exceed the frozen +0.20 percentage-point margin; all prompts retained.",
+  "scope": "Historical CPU-reference quality requirement failed; updated-main integration is separately pending.",
+  "final_pull_request_head": "172395ef6ea072c531a89dc18ab868ff2f9ada12"
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-holdout-candidate.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-holdout-candidate.json.gz
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HcmV?d00001

diff --git a/evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py b/evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py
new file mode 100644
index 000000000..97ffb0581
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py
@@ -0,0 +1,81 @@
+"""Plot saved aggregate metrics; ranges are observed repeats, not confidence intervals."""
+
+import argparse
+import json
+from pathlib import Path
+
+import matplotlib
+
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--baselines", type=Path, required=True)
+    parser.add_argument("--integrated", type=Path, required=True)
+    parser.add_argument("--out", type=Path, required=True)
+    args = parser.parse_args()
+    baseline = json.loads(args.baselines.read_text())["rows"]
+    series = [
+        ("vLLM main aa3fd1d9", [row for row in baseline if row["engine"] == "vllm"], "#335c9d"),
+        (
+            "SGLang dbd923cd (terminal audio)",
+            [row for row in baseline if row["engine"] == "sglang"],
+            "#d98222",
+        ),
+        ("vLLM main 15bce345", json.loads(args.integrated.read_text())["baseline"], "#308664"),
+        (
+            "vLLM CPU-reference TRT + MPS 227a43e8",
+            json.loads(args.integrated.read_text())["candidate"],
+            "#8c5aa8",
+        ),
+    ]
+    panels = [
+        ("throughput_frames_s_mean", "Throughput (audio frames/s)"),
+        ("ttfa_p50_ms_pooled", "TTFA p50 (ms)"),
+        ("ttfa_p95_ms_pooled", "TTFA p95 (ms)"),
+        ("rtf_mean", "RTF (mean)"),
+    ]
+    fig, axes = plt.subplots(2, 2, figsize=(12, 7))
+    for ax, (key, title) in zip(axes.flat, panels):
+        for label, rows, color in series:
+            rows = sorted(rows, key=lambda row: row["concurrency"])
+            assert len(rows) == 6, f"Incomplete series: {label}"
+            x = [row["concurrency"] for row in rows]
+            ax.plot(x, [row[key] for row in rows], marker="o", color=color, label=label)
+            if key == "throughput_frames_s_mean":
+                ax.fill_between(
+                    x,
+                    [min(row["throughput_frames_s_runs"]) for row in rows],
+                    [max(row["throughput_frames_s_runs"]) for row in rows],
+                    color=color,
+                    alpha=0.12,
+                )
+        ax.set_xscale("log", base=2)
+        ax.set_xticks([1, 2, 4, 8, 16, 32], labels=[1, 2, 4, 8, 16, 32])
+        ax.set_xlabel("Concurrency")
+        ax.set_title(title)
+        ax.grid(alpha=0.2)
+    handles, labels = axes[0, 0].get_legend_handles_labels()
+    fig.legend(handles, labels, loc="lower center", ncol=2, bbox_to_anchor=(0.5, 0.04), fontsize=9)
+    fig.suptitle("MiniCPM-o 4.5 · one L20X · Seed-TTS English · steady state")
+    fig.text(
+        0.5,
+        0.015,
+        "25 audio frames/s; 3 × 320 measured requests/cell. "
+        "SGLang TTFA is terminal-waveform latency. Quality verdicts are separate.",
+        ha="center",
+        fontsize=8,
+    )
+    fig.tight_layout(rect=(0, 0.12, 1, 0.95))
+    args.out.parent.mkdir(parents=True, exist_ok=True)
+    fig.savefig(args.out.with_suffix(".png"), dpi=160)
+    svg = args.out.with_suffix(".svg")
+    fig.savefig(svg)
+    svg.write_text("\n".join(line.rstrip() for line in svg.read_text().splitlines()) + "\n")
+    plt.close(fig)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/rescore_saved_wav.py b/evidence/minicpmo45-l20x-20261021/validator/rescore_saved_wav.py
new file mode 100644
index 000000000..0d9a5f69c
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/rescore_saved_wav.py
@@ -0,0 +1,53 @@
+"""Repeat native Qwen3 ASR requests; requires local, unredacted scorer output."""
+
+import argparse
+import hashlib
+import json
+from pathlib import Path
+
+import requests
+
+
+def main():
+    p = argparse.ArgumentParser(description=__doc__)
+    p.add_argument("--wav", type=Path, required=True)
+    p.add_argument("--original-quality", type=Path, required=True)
+    p.add_argument("--request-id", required=True)
+    p.add_argument("--asr-port", type=int, default=29181)
+    p.add_argument("--model", default="Qwen/Qwen3-ASR-1.7B")
+    p.add_argument("--repeats", type=int, default=3)
+    p.add_argument("--out", type=Path, required=True)
+    a = p.parse_args()
+    original = json.loads(a.original_quality.read_text())["rows"][a.request_id]["wer"]["hyp_text"]
+    hashes, equal = [], []
+    for _ in range(a.repeats):
+        with a.wav.open("rb") as stream:
+            response = requests.post(
+                f"http://127.0.0.1:{a.asr_port}/v1/audio/transcriptions",
+                data={"model": a.model, "language": "en", "response_format": "json"},
+                files={"file": (a.wav.name, stream, "audio/wav")},
+                timeout=300,
+                proxies={"http": None, "https": None},
+            )
+        response.raise_for_status()
+        text = response.json()["text"]
+        hashes.append(hashlib.sha256(text.encode()).hexdigest())
+        equal.append(text == original)
+    a.out.write_text(
+        json.dumps(
+            {
+                "scope": "Diagnostic only; does not replace frozen scores or remove prompts",
+                "request_id": a.request_id,
+                "wav_sha256": hashlib.sha256(a.wav.read_bytes()).hexdigest(),
+                "original_transcript_sha256": hashlib.sha256(original.encode()).hexdigest(),
+                "same_as_original": equal,
+                "transcript_sha256": hashes,
+            },
+            indent=2,
+        )
+        + "\n"
+    )
+
+
+if __name__ == "__main__":
+    main()

From e1f16384360ae11adca5c02249d859f7930421cc Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 12:54:49 +0800
Subject: [PATCH 10/40] Report adapted speaker throughput and failed quality
 regression

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   39 +-
 .../final-control-allocation-addendum.json    |   12 +
 .../plan/runtime-observations.json            |   16 +-
 .../results/final-concurrency-comparison.png  |  Bin 0 -> 226268 bytes
 .../results/final-concurrency-comparison.svg  | 3016 +++++++++++++++++
 .../results/integrated-comparison.json        |  418 +++
 .../results/integrated-quality.json.gz        |  Bin 0 -> 148010 bytes
 .../results/status.json                       |   12 +-
 .../results/vllm-integrated-candidate.json.gz |  Bin 0 -> 1089905 bytes
 .../results/vllm-latest-main.json.gz          |  Bin 0 -> 1094355 bytes
 .../validator/export_final_controls.py        |   80 +
 .../validator/final_controls.py               |  135 +
 12 files changed, 3719 insertions(+), 9 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/final-control-allocation-addendum.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/final-concurrency-comparison.png
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/final-concurrency-comparison.svg
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/integrated-comparison.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/integrated-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-integrated-candidate.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-latest-main.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/export_final_controls.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/final_controls.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 64fdbc4f2..23db125a2 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -2,7 +2,7 @@
 
 Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
 
-**Original strict quality verdict: FAIL** for the completed speaker-only candidate. The separately authorized noninferiority evaluation on previously unused prompts also **FAILS** on C16/C32 WER. Updated-main integration is assessed separately; neither new comparison changes those verdicts. Component PASS does not establish service PASS.
+**Original strict quality verdict: FAIL** for the completed speaker-only candidate. The separately authorized noninferiority evaluation on previously unused prompts also **FAILS** on C16/C32 WER. The adapted revision also FAILS its separately scoped regression against updated main (C16 WER, C32 WER/SIM). No later comparison changes the earlier verdicts. Component PASS does not establish service PASS.
 
 ## Scope and controls
 
@@ -181,7 +181,7 @@ listening study. A failed upper-bound gate does not by itself prove perceptual
 inferiority.
 
 Host CPUs and the filesystem are shared with other jobs; GPU reservations are
-exclusive, but CPU affinity is not isolated. The host has two Intel Xeon
+cooperative and cannot prevent unreserved processes; CPU affinity is not isolated. The host has two Intel Xeon
 Platinum 8480C sockets, 112 physical cores / 224 hardware threads. Results are
 scoped observations on this host, not hardware-independent performance claims.
 
@@ -223,3 +223,38 @@ The frozen historical candidate fails the authorized quality bounds. All 320 pro
 | 32 | 1.4166 / 4.7298 | 0.0946 / 0.5000 | 0.0246 / 0.0430 | FAIL |
 
 At C32, a single prompt contributes 57 additional errors against a net total increase of 49. Both baseline and candidate already transcribe poorly on that prompt; the candidate C32 ASR result reproduces exactly on three resubmissions of its saved WAV. Baseline C32 resubmissions agree with each other but differ from its original ASR text by one whitespace token. These diagnostics do not delete the prompt, clip its WER, replace frozen scores, or establish a causal model defect. See `results/holdout-error-attribution.json` and `results/outlier-asr-repeat.json`.
+
+## Final adapted revision versus updated main
+
+Baseline `15bce34586` and candidate tree `227a43e8` completed all six cells, three measured repeats of 320 requests per cell, with zero measured request failures. PR head `172395ef` has the identical Git tree; its extra commit only refreshed CI. Both high-concurrency performance gates pass, but the combined service/quality verdict is **FAIL**.
+
+| Engine / profile | C | Frames/s | TTFA p50 ms | TTFA p95 ms | RTF mean |
+|---|---:|---:|---:|---:|---:|
+| Updated main | 1 | 191.4 | 312.5 | 349.7 | 0.133 |
+| Updated main | 2 | 306.8 | 396.5 | 503.1 | 0.165 |
+| Updated main | 4 | 464.2 | 617.0 | 729.8 | 0.224 |
+| Updated main | 8 | 614.8 | 957.6 | 1156.1 | 0.337 |
+| Updated main | 16 | 696.4 | 1288.5 | 1889.4 | 0.587 |
+| Updated main | 32 | 753.9 | 1904.7 | 2681.9 | 1.073 |
+| CPU-reference TRT + MPS | 1 | 193.0 | 301.4 | 342.1 | 0.131 |
+| CPU-reference TRT + MPS | 2 | 337.2 | 341.7 | 413.5 | 0.150 |
+| CPU-reference TRT + MPS | 4 | 535.6 | 457.4 | 580.1 | 0.191 |
+| CPU-reference TRT + MPS | 8 | 720.2 | 685.0 | 932.5 | 0.286 |
+| CPU-reference TRT + MPS | 16 | 838.9 | 996.6 | 1624.8 | 0.487 |
+| CPU-reference TRT + MPS | 32 | 945.4 | 1490.0 | 2211.1 | 0.855 |
+
+Observed high-concurrency throughput gains versus updated main are **20.5% at C16 and 25.4% at C32**. Every candidate repeat exceeds every baseline repeat in both cells. These are combined CPU-reference TRT plus MPS observations, not isolated TensorRT attribution.
+
+Quality uses the already-seen first cohort. The same predeclared margins and paired-bootstrap function apply, but this is an integration regression rather than another independent holdout. Table entries are degradation / one-sided 95% upper bound.
+
+| C | WER pp (margin 0.20) | SIM ×100 drop (margin 0.50) | UTMOS drop (margin 0.05) | Verdict |
+|---|---:|---:|---:|---|
+| 1 | 0.0000 / 0.0577 | -0.0042 / 0.0947 | 0.0121 / 0.0213 | PASS |
+| 16 | 0.4549 / 0.8451 | -0.4792 / -0.0491 | 0.0016 / 0.0181 | FAIL |
+| 32 | 0.1422 / 0.2847 | 0.3191 / 0.6818 | 0.0152 / 0.0311 | FAIL |
+
+C16 WER fails. At C32, WER and SIM point estimates are inside their margins, but their upper confidence bounds fail; this does not establish population or perceptual inferiority. No prompts or original scores are excluded. The earlier untouched-cohort FAIL remains unchanged.
+
+![Final concurrency comparison](results/final-concurrency-comparison.png)
+
+Observed throughput ranges are repeat ranges, not confidence intervals. SGLang TTFA measures terminal-waveform delivery. Native precision and scheduling differ; neither the figure nor the throughput gains establish speech-quality equivalence or a global optimum.
diff --git a/evidence/minicpmo45-l20x-20261021/plan/final-control-allocation-addendum.json b/evidence/minicpmo45-l20x-20261021/plan/final-control-allocation-addendum.json
new file mode 100644
index 000000000..b11a84c07
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/final-control-allocation-addendum.json
@@ -0,0 +1,12 @@
+{
+  "recorded_at_utc": "2026-10-21T04:40:48.314133+00:00",
+  "initial_attempt": "Main startup failed before any measured requests: a noncampaign unreserved GPU process appeared on the reserved card; available KV cache was 2.09 GiB versus 5.62 GiB needed for unchanged max_model_len. Other job left untouched.",
+  "change": "Cancel separately queued attribution job on that card. Rerun the previously frozen main, candidate, and Torch+MPS controls sequentially under one reservation on another verified-free L20X.",
+  "invariants": "No model, sampling, memory-budget, concurrency, cohort, repeat-count or quality-gate changes. Preserve failed startup as environment evidence.",
+  "sequence": [
+    "latest main default",
+    "CPU-reference TRT + MPS",
+    "latest main Torch + MPS"
+  ],
+  "outputs": "vllm-final-fresh-{main,candidate,torch_mps}"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json b/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
index cd3aa5f23..713dee5ee 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
@@ -39,9 +39,21 @@
       "device_role": "same GPU D, sequential fresh holdout pair",
       "cuda_mps": true,
       "speaker_backend": "CPU-reference TensorRT IEEE FP32",
-      "state": "Planned next after main completes; confirm against final controller output"
+      "state": "Completed and scored; noninferiority FAIL retained."
+    },
+    "vllm-latest-main": {
+      "cuda_mps": false,
+      "speaker_backend": "Torch CUDA",
+      "device_role": "GPU E, updated-main repeated matrix",
+      "mps_started_private_daemon": false
+    },
+    "vllm-integrated-candidate": {
+      "cuda_mps": true,
+      "speaker_backend": "CPU-reference TensorRT IEEE FP32",
+      "device_role": "GPU F, adapted-candidate repeated matrix",
+      "mps_started_private_daemon": true
     }
   },
   "summary_metadata_warning": "Raw summary mps_policy=off/id_set=eval and blank source/device fields are reference-helper defaults. These runtime observations, source plans and pinned manifests are authoritative. No strict certification is inferred from those default fields.",
-  "host_limitations": "Exclusive GPU reservations, but shared host CPUs and filesystem; other workloads and separate GPU scoring may overlap. No CPU affinity isolation or causal attribution from microbench timing alone."
+  "host_limitations": "GPU reservations were acquired, but the scheduler cannot prevent unreserved jobs. A final-control startup was aborted when an unrelated job occupied its reserved GPU; no measured requests were produced and the control was moved to a free GPU. Host CPUs and filesystem remain shared; no CPU affinity isolation. See final-control-allocation-addendum.json."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/final-concurrency-comparison.png b/evidence/minicpmo45-l20x-20261021/results/final-concurrency-comparison.png
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index 000000000..488c23b2b
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diff --git a/evidence/minicpmo45-l20x-20261021/results/status.json b/evidence/minicpmo45-l20x-20261021/results/status.json
index 3d44455da..0ac6c0d0b 100644
--- a/evidence/minicpmo45-l20x-20261021/results/status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/status.json
@@ -8,18 +8,20 @@
   },
   "optimization_submitted": true,
   "pending": [
-    "updated-main and adapted-candidate repeated service comparison",
-    "adapted-candidate quality regression against updated main"
+    "final same-GPU MPS attribution control"
   ],
   "candidate_pull_request": "https://github.com/vllm-project/vllm-omni/pull/9188",
   "candidate_cpu_tests_passed": 67,
-  "candidate_tuning": "C16/C32 gains observed; held-out repeated service and generated speech quality pending",
+  "candidate_tuning": "Completed historical candidate comparisons; strict and unused-holdout quality gates FAIL.",
   "original_strict_speaker_verdict": "FAIL",
   "knowledge_pull_request": "https://github.com/InferMatrixLab/InferRSI/pull/51",
   "final_candidate_revision": "227a43e898f8b96236f48f16f399431c8ad0ddcc",
   "updated_baseline_revision": "15bce34586",
   "historical_noninferiority_verdict": "FAIL",
   "historical_noninferiority_reason": "C16 and C32 WER degradation upper bounds exceed the frozen +0.20 percentage-point margin; all prompts retained.",
-  "scope": "Historical CPU-reference quality requirement failed; updated-main integration is separately pending.",
-  "final_pull_request_head": "172395ef6ea072c531a89dc18ab868ff2f9ada12"
+  "scope": "Historical unused-holdout and adapted integration quality both FAIL; throughput observations are not combined qualification.",
+  "final_pull_request_head": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "integrated_verdict": "FAIL",
+  "integrated_quality_reason": "C16 WER and C32 WER/SIM upper bounds exceed frozen margins.",
+  "integrated_cpu_tests_passed": 108
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-integrated-candidate.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-integrated-candidate.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/validator/export_final_controls.py b/evidence/minicpmo45-l20x-20261021/validator/export_final_controls.py
new file mode 100644
index 000000000..c607219be
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/export_final_controls.py
@@ -0,0 +1,80 @@
+import argparse
+import gzip
+import importlib.util
+import json
+import subprocess
+import sys
+import time
+from pathlib import Path
+
+parser = argparse.ArgumentParser(
+    description="Export completed same-GPU control metrics and redact ASR transcripts."
+)
+parser.add_argument("--runs", type=Path, required=True)
+parser.add_argument("--evidence", type=Path, required=True)
+args = parser.parse_args()
+r = args.runs
+e = args.evidence
+paths = [
+    r / f"quality/vllm-final-fresh-{role}-c{c}.json"
+    for role in ("main", "candidate", "torch_mps")
+    for c in (16, 32)
+]
+while True:
+    try:
+        docs = [json.loads(p.read_text()) for p in paths]
+        if all(set(d["tasks"]) == {"wer", "sim", "utmos"} and "summary" in d for d in docs):
+            break
+    except (OSError, ValueError):
+        pass
+    time.sleep(3)
+spec = importlib.util.spec_from_file_location("summarize", e / "validator/summarize_results.py")
+m = importlib.util.module_from_spec(spec)
+spec.loader.exec_module(m)
+profiles = {
+    role: m.aggregate(r / f"vllm-final-fresh-{role}") for role in ("main", "candidate", "torch_mps")
+}
+ratios = []
+for c in (16, 32):
+    rates = {
+        role: next(row["throughput_frames_s_mean"] for row in rows if row["concurrency"] == c)
+        for role, rows in profiles.items()
+    }
+    ratios.append(
+        {
+            "concurrency": c,
+            "candidate_over_main": rates["candidate"] / rates["main"],
+            "torch_mps_over_main": rates["torch_mps"] / rates["main"],
+            "candidate_over_torch_mps": rates["candidate"] / rates["torch_mps"],
+        }
+    )
+out = {
+    "scope": (
+        "Sequential same-GPU fresh main, candidate, then Torch plus MPS control; "
+        "one measured repeat at C16/C32 on reused first cohort. "
+        "Descriptive attribution only, not independent quality qualification."
+    ),
+    "profiles": profiles,
+    "ratios": ratios,
+    "quality": {p.stem: d["summary"] for p, d in zip(paths, docs)},
+}
+(e / "results/final-same-gpu-controls.json").write_text(json.dumps(out, indent=2) + "\n")
+for d in docs:
+    for row in d["rows"].values():
+        row["wer"].pop("hyp_text", None)
+(e / "results/final-controls-quality.json.gz").write_bytes(
+    gzip.compress(
+        (json.dumps({p.stem: d for p, d in zip(paths, docs)}, indent=2) + "\n").encode(), mtime=0
+    )
+)
+for role in ("main", "candidate", "torch_mps"):
+    subprocess.run(
+        [
+            sys.executable,
+            str(e / "validator/export_metrics.py"),
+            str(r / f"vllm-final-fresh-{role}"),
+            str(e / f"results/vllm-final-fresh-{role}.json.gz"),
+        ],
+        check=True,
+    )
+print("FINAL CONTROLS ARTIFACTS COMPLETE", flush=True)
diff --git a/evidence/minicpmo45-l20x-20261021/validator/final_controls.py b/evidence/minicpmo45-l20x-20261021/validator/final_controls.py
new file mode 100644
index 000000000..a62d4c6b9
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/final_controls.py
@@ -0,0 +1,135 @@
+"""Reproduce the ordered same-GPU integration controls on the reused first cohort.
+
+Requires Linux process groups and compatible, separately installed environments.
+Raw server logs remain in the selected local output directory.
+"""
+
+import argparse
+import os
+import signal
+import subprocess
+import time
+import urllib.request
+from pathlib import Path
+
+
+def _terminate(signum, frame):
+    raise SystemExit(128 + signum)
+
+
+def main():
+    signal.signal(signal.SIGTERM, _terminate)
+    parser = argparse.ArgumentParser(description=__doc__)
+    for name in (
+        "model",
+        "main-repo",
+        "candidate-repo",
+        "main-python",
+        "candidate-python",
+        "client-python",
+        "peer-repo",
+        "dataset",
+        "candidate-deploy",
+        "torch-mps-deploy",
+        "out",
+    ):
+        parser.add_argument(f"--{name}", type=Path, required=True)
+    parser.add_argument("--base-port", type=int, default=29331)
+    args = parser.parse_args()
+    args.out.mkdir(parents=True, exist_ok=True)
+    specs = [
+        (
+            "main",
+            args.main_repo,
+            args.main_python,
+            args.main_repo / "vllm_omni/deploy/minicpmo_4_5_turn.yaml",
+        ),
+        ("candidate", args.candidate_repo, args.candidate_python, args.candidate_deploy),
+        ("torch_mps", args.main_repo, args.main_python, args.torch_mps_deploy),
+    ]
+    for index, (role, repo, python, deploy) in enumerate(specs):
+        port = args.base_port + 10 * index
+        env = os.environ | {"PYTHONPATH": str(repo.resolve()), "PYTHONUNBUFFERED": "1"}
+        command = [
+            str(python),
+            "-m",
+            "vllm_omni.entrypoints.cli.main",
+            "serve",
+            str(args.model),
+            "--omni",
+            "--served-model-name",
+            "openbmb/MiniCPM-o-4_5",
+            "--host",
+            "127.0.0.1",
+            "--port",
+            str(port),
+            "--deploy-config",
+            str(deploy),
+            "--trust-remote-code",
+            "--init-timeout",
+            "1800",
+            "--stage-init-timeout",
+            "1800",
+        ]
+        with (args.out / f"{role}-server.log").open("w") as server_log:
+            server = subprocess.Popen(
+                command,
+                env=env,
+                stdout=server_log,
+                stderr=subprocess.STDOUT,
+                start_new_session=True,
+            )
+            try:
+                deadline = time.monotonic() + 1800
+                while True:
+                    if server.poll() is not None:
+                        raise RuntimeError(f"{role} server exited before readiness")
+                    if time.monotonic() > deadline:
+                        raise TimeoutError(f"{role} startup exceeded 1800 seconds")
+                    try:
+                        with urllib.request.urlopen(f"http://127.0.0.1:{port}/health", timeout=2):
+                            break
+                    except (OSError, TimeoutError):
+                        time.sleep(3)
+                client_env = os.environ | {
+                    "PYTHONPATH": str(args.peer_repo.resolve()),
+                    "SEED_TTS_ROOT": str(args.dataset.resolve()),
+                }
+                output = args.out / f"vllm-final-fresh-{role}"
+                with (args.out / f"{role}-benchmark.log").open("w") as benchmark_log:
+                    subprocess.run(
+                        [
+                            str(args.client_python),
+                            str(Path(__file__).with_name("run_baseline.py")),
+                            "--adapter",
+                            "vllm-omni",
+                            "--url",
+                            f"http://127.0.0.1:{port}",
+                            "--out",
+                            str(output),
+                            "--requests",
+                            "320",
+                            "--repeats",
+                            "1",
+                            "--concurrency",
+                            "16",
+                            "32",
+                        ],
+                        env=client_env,
+                        stdout=benchmark_log,
+                        stderr=subprocess.STDOUT,
+                        check=True,
+                    )
+                (output / "complete").write_text("All requested runs saved successfully.\n")
+            finally:
+                if server.poll() is None:
+                    os.killpg(server.pid, signal.SIGTERM)
+                    try:
+                        server.wait(timeout=120)
+                    except subprocess.TimeoutExpired:
+                        os.killpg(server.pid, signal.SIGKILL)
+                        server.wait()
+
+
+if __name__ == "__main__":
+    main()

From f51615d324018298ed93b3b57112eb509553f910 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 13:19:25 +0800
Subject: [PATCH 11/40] Complete same-GPU MPS attribution and preserve failed
 acceptance

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   32 +-
 .../plan/runtime-observations.json            |   21 +
 .../results/concurrency-metrics.csv           |   25 +
 .../results/final-concurrency-comparison.png  |  Bin 226268 -> 226952 bytes
 .../results/final-concurrency-comparison.svg  | 1251 +++++++++--------
 .../results/final-control-environment.json    |   11 +
 .../results/final-controls-quality.json.gz    |  Bin 0 -> 147914 bytes
 .../results/final-same-gpu-controls.json      |  201 +++
 .../results/status.json                       |    8 +-
 .../vllm-final-fresh-candidate.json.gz        |  Bin 0 -> 189041 bytes
 .../results/vllm-final-fresh-main.json.gz     |  Bin 0 -> 191358 bytes
 .../vllm-final-fresh-torch_mps.json.gz        |  Bin 0 -> 189766 bytes
 .../validator/plot_final_results.py           |   11 +-
 .../validator/vllm-pr-checks.json             |   77 +
 14 files changed, 1036 insertions(+), 601 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/concurrency-metrics.csv
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/final-control-environment.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/final-controls-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/final-same-gpu-controls.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-final-fresh-candidate.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-final-fresh-main.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/vllm-final-fresh-torch_mps.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/vllm-pr-checks.json

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 23db125a2..cb794a545 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -2,7 +2,7 @@
 
 Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
 
-**Original strict quality verdict: FAIL** for the completed speaker-only candidate. The separately authorized noninferiority evaluation on previously unused prompts also **FAILS** on C16/C32 WER. The adapted revision also FAILS its separately scoped regression against updated main (C16 WER, C32 WER/SIM). No later comparison changes the earlier verdicts. Component PASS does not establish service PASS.
+**Original strict quality verdict: FAIL** for both completed historical speaker-only and speaker+MPS candidates. The separately authorized noninferiority evaluation on previously unused prompts also **FAILS** on C16/C32 WER. The adapted revision also FAILS its separately scoped regression against updated main (C16 WER, C32 WER/SIM). No later comparison changes the earlier verdicts. Component PASS does not establish service PASS.
 
 ## Scope and controls
 
@@ -15,7 +15,7 @@ Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49)
 - Throughput is 25 × delivered audio seconds / measured wall time; it is an audio-frame equivalent, not video fps. The table averages three run throughputs. TTFA percentiles pool 960 requests; RTF is the mean per-request last-audio latency divided by generated duration.
 - vLLM streams audio chunks. SGLang returns a terminal waveform, so its TTFA is effectively completion latency. Do not interpret the two TTFA columns as equivalent streaming capability.
 
-The native main configurations also differ: SGLang Code2Wav uses float16, compiled DiT/HiFT, eight reference workers and a 32-entry prompt cache; this vLLM baseline uses its default FP32 CFM path and serial CPU reference preparation. These are native-engine comparisons, not an isolated backend comparison with identical numerical kernels and scheduling.
+The native main configurations also differ: SGLang Code2Wav uses float16, compiled DiT/HiFT, eight reference workers and a 32-entry prompt cache; the initial vLLM snapshot uses its default FP32 CFM path and serial CPU reference preparation. Updated main uses Torch CUDA speaker extraction. These are native-engine comparisons, not an isolated backend comparison with identical numerical kernels and scheduling.
 
 ## Initial main snapshots (before CUDA Torch became the vLLM default)
 
@@ -220,7 +220,7 @@ The frozen historical candidate fails the authorized quality bounds. All 320 pro
 |---|---:|---:|---:|---|
 | 1 | 0.0289 / 0.0871 | -0.0792 / -0.0196 | 0.0008 / 0.0063 | PASS |
 | 16 | 0.4047 / 0.9043 | -0.1930 / 0.2013 | 0.0027 / 0.0201 | FAIL |
-| 32 | 1.4166 / 4.7298 | 0.0946 / 0.5000 | 0.0246 / 0.0430 | FAIL |
+| 32 | 1.4166 / 4.7298 | 0.0946 / 0.49995 | 0.0246 / 0.0430 | FAIL |
 
 At C32, a single prompt contributes 57 additional errors against a net total increase of 49. Both baseline and candidate already transcribe poorly on that prompt; the candidate C32 ASR result reproduces exactly on three resubmissions of its saved WAV. Baseline C32 resubmissions agree with each other but differ from its original ASR text by one whitespace token. These diagnostics do not delete the prompt, clip its WER, replace frozen scores, or establish a causal model defect. See `results/holdout-error-attribution.json` and `results/outlier-asr-repeat.json`.
 
@@ -258,3 +258,29 @@ C16 WER fails. At C32, WER and SIM point estimates are inside their margins, but
 ![Final concurrency comparison](results/final-concurrency-comparison.png)
 
 Observed throughput ranges are repeat ranges, not confidence intervals. SGLang TTFA measures terminal-waveform delivery. Native precision and scheduling differ; neither the figure nor the throughput gains establish speech-quality equivalence or a global optimum.
+
+Machine-readable metrics for all four pinned engine/profile snapshots: [concurrency-metrics.csv](results/concurrency-metrics.csv).
+
+## Final same-GPU attribution controls
+
+Fresh services ran sequentially on the same reserved L20X: updated main, CPU-reference TRT + MPS, then unchanged updated main with only MPS enabled. Each C16/C32 cell has one discarded and one measured 320-request run. These reused-cohort, single ordered repeats are descriptive controls, not independent speech-quality qualification or an ABBA study.
+
+| C | Main frames/s | CPU-ref TRT + MPS frames/s | Torch + MPS frames/s | CPU-ref / Torch+MPS |
+|---|---:|---:|---:|---:|
+| 16 | 693.1 | 815.6 | 783.3 | 1.041× |
+| 32 | 766.1 | 929.4 | 864.3 | 1.075× |
+
+Quality means below describe these control WAVs. They do not replace either frozen validation result. WER is corpus WER (%); SIM is ×100.
+
+| Profile | C | WER % | SIM ×100 | UTMOS |
+|---|---:|---:|---:|---:|
+| main | 16 | 1.2795 | 49.7516 | 4.1919 |
+| main | 32 | 1.3079 | 49.8408 | 4.2048 |
+| candidate | 16 | 1.3648 | 49.8820 | 4.1921 |
+| candidate | 32 | 1.1658 | 49.8404 | 4.1951 |
+| torch_mps | 16 | 1.2795 | 49.8582 | 4.1846 |
+| torch_mps | 32 | 1.2795 | 49.6752 | 4.2002 |
+
+Full TTFA/RTF, run metadata and per-request hashes are in `results/final-same-gpu-controls.json` and `results/vllm-final-fresh-*.json.gz`. Reproduce with `validator/final_controls.py --help`, score saved run1 WAVs using the existing scorer, then use `validator/export_final_controls.py --runs ... --evidence ...`. The MPS-only overlay sets `base_config: minicpmo_4_5_turn.yaml` and `cuda_mps: true`; all model-specific defaults remain inherited.
+
+A previous control startup failed before measurement when an unreserved unrelated process occupied its reserved GPU. That job was left untouched; the full three-profile sequence moved to a free GPU without changing memory limits, prompts or gates. Cooperative reservations are not a guarantee of host-wide isolation. See `plan/final-control-allocation-addendum.json` and `results/final-control-environment.json`.
diff --git a/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json b/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
index 713dee5ee..953723699 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/runtime-observations.json
@@ -52,6 +52,27 @@
       "speaker_backend": "CPU-reference TensorRT IEEE FP32",
       "device_role": "GPU F, adapted-candidate repeated matrix",
       "mps_started_private_daemon": true
+    },
+    "vllm-final-fresh-main": {
+      "device_role": "Same physical GPU G, sequential final controls",
+      "cuda_mps": false,
+      "speaker_backend": "Torch CUDA",
+      "state": "Completed and scored",
+      "mps_started_private_daemon": false
+    },
+    "vllm-final-fresh-candidate": {
+      "device_role": "Same physical GPU G, sequential final controls",
+      "cuda_mps": true,
+      "speaker_backend": "CPU-reference TensorRT IEEE FP32",
+      "state": "Completed and scored",
+      "mps_started_private_daemon": true
+    },
+    "vllm-final-fresh-torch_mps": {
+      "device_role": "Same physical GPU G, sequential final controls",
+      "cuda_mps": true,
+      "speaker_backend": "Torch CUDA",
+      "state": "Completed and scored",
+      "mps_started_private_daemon": true
     }
   },
   "summary_metadata_warning": "Raw summary mps_policy=off/id_set=eval and blank source/device fields are reference-helper defaults. These runtime observations, source plans and pinned manifests are authoritative. No strict certification is inferred from those default fields.",
diff --git a/evidence/minicpmo45-l20x-20261021/results/concurrency-metrics.csv b/evidence/minicpmo45-l20x-20261021/results/concurrency-metrics.csv
new file mode 100644
index 000000000..b8f6114a1
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/concurrency-metrics.csv
@@ -0,0 +1,25 @@
+engine,revision,profile,concurrency,throughput_frames_s_mean,ttfa_p50_ms_pooled,ttfa_p95_ms_pooled,rtf_mean,ttfa_delivery,repeats,requests_per_repeat,n_failed
+vllm-omni,aa3fd1d9,initial-main-native,1,192.6309728972112,307.4587588198483,343.0558750871569,0.13163823357797064,streaming,3,320,0
+vllm-omni,aa3fd1d9,initial-main-native,2,295.48597389019307,410.91528814285994,534.6035631839186,0.1720971816832971,streaming,3,320,0
+vllm-omni,aa3fd1d9,initial-main-native,4,394.0476581440165,881.6496999934316,1000.247368076816,0.2666428173622068,streaming,3,320,0
+vllm-omni,aa3fd1d9,initial-main-native,8,488.4001363373871,1375.2594594843686,1602.6222183834761,0.42630675701070436,streaming,3,320,0
+vllm-omni,aa3fd1d9,initial-main-native,16,513.2861988294537,1702.651811297983,2727.534947451204,0.7967777842709449,streaming,3,320,0
+vllm-omni,aa3fd1d9,initial-main-native,32,540.2205300552778,2752.2785966284573,4732.173519395292,1.5019947916199494,streaming,3,320,0
+sglang-omni,dbd923cd,main-native,1,291.33565256989596,371.0423116572201,461.8933257646858,0.0888416606367711,terminal-waveform,3,320,0
+sglang-omni,dbd923cd,main-native,2,476.64068307533654,451.30864251405,578.6992390174418,0.10891612284894604,terminal-waveform,3,320,0
+sglang-omni,dbd923cd,main-native,4,713.7879426625113,599.6185531839728,799.9201192986219,0.145134672745195,terminal-waveform,3,320,0
+sglang-omni,dbd923cd,main-native,8,1043.2055569310974,835.1065027527511,1042.5908281002194,0.1980206295767324,terminal-waveform,3,320,0
+sglang-omni,dbd923cd,main-native,16,1558.5134910014297,1111.986730247736,1411.4549641031772,0.2638718498759094,terminal-waveform,3,320,0
+sglang-omni,dbd923cd,main-native,32,1918.4671911997168,1763.5161047801375,2479.3635668233037,0.4245844838355303,terminal-waveform,3,320,0
+vllm-omni,15bce345,updated-main-native,1,191.367144902749,312.5393916852772,349.7427012305707,0.13252322770531944,streaming,3,320,0
+vllm-omni,15bce345,updated-main-native,2,306.78983013914655,396.4510438963771,503.11871785670513,0.16549976121924462,streaming,3,320,0
+vllm-omni,15bce345,updated-main-native,4,464.22769720048234,616.9718676246703,729.8253195825963,0.2239539695139891,streaming,3,320,0
+vllm-omni,15bce345,updated-main-native,8,614.8286489298924,957.6272070407867,1156.0852929018438,0.3368092002811372,streaming,3,320,0
+vllm-omni,15bce345,updated-main-native,16,696.350580408136,1288.4640241973102,1889.4245164003223,0.5873455186144915,streaming,3,320,0
+vllm-omni,15bce345,updated-main-native,32,753.8763345861681,1904.7096958383918,2681.9357595406454,1.0729952954013566,streaming,3,320,0
+vllm-omni,227a43e8,cpu-reference-trt-mps,1,192.97842522575482,301.35434260591865,342.12581319734454,0.13139107357442603,streaming,3,320,0
+vllm-omni,227a43e8,cpu-reference-trt-mps,2,337.1825655595755,341.7191384360194,413.4840169921517,0.150303386934262,streaming,3,320,0
+vllm-omni,227a43e8,cpu-reference-trt-mps,4,535.6476434027298,457.4177353642881,580.1486061420292,0.1906587911053855,streaming,3,320,0
+vllm-omni,227a43e8,cpu-reference-trt-mps,8,720.2286819431107,685.01648446545,932.495519844815,0.28603748282330366,streaming,3,320,0
+vllm-omni,227a43e8,cpu-reference-trt-mps,16,838.8693462958437,996.6035825200379,1624.8473662883043,0.4870123417037282,streaming,3,320,0
+vllm-omni,227a43e8,cpu-reference-trt-mps,32,945.353258444246,1490.0012705475092,2211.071643512696,0.8547534222214155,streaming,3,320,0
diff --git a/evidence/minicpmo45-l20x-20261021/results/final-concurrency-comparison.png b/evidence/minicpmo45-l20x-20261021/results/final-concurrency-comparison.png
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diff --git a/evidence/minicpmo45-l20x-20261021/results/final-control-environment.json b/evidence/minicpmo45-l20x-20261021/results/final-control-environment.json
new file mode 100644
index 000000000..393ee720d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/final-control-environment.json
@@ -0,0 +1,11 @@
+{
+  "scope": "Partial monitoring from the recorded first sample until final control completion, nominally every ten seconds. Not continuous isolation certification; no retroactive coverage claim.",
+  "first_sample_utc": "2026-10-21T04:42:07.433555+00:00",
+  "last_sample_utc": "2026-10-21T05:17:46.082027+00:00",
+  "samples": 204,
+  "process_observations_during_own_runs": 842,
+  "unmatched_process_observations": [],
+  "identification": "Match known server stage PIDs from private startup logs or inspect only PYTHONPATH in process/ancestor environments. Initial direct process environments did not identify spawned workers; known startup PIDs resolve these observations. Public report omits PIDs, GPU UUIDs and private paths.",
+  "excluded": "Processes appearing on cards after our completion markers are other allocations and are excluded.",
+  "failed_previous_startup": "Unreserved unrelated process occupied the first control card; startup failed before measured requests. Other job left untouched and full controls moved to a free card."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/final-controls-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/final-controls-quality.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/final-same-gpu-controls.json b/evidence/minicpmo45-l20x-20261021/results/final-same-gpu-controls.json
new file mode 100644
index 000000000..97e280dc4
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/final-same-gpu-controls.json
@@ -0,0 +1,201 @@
+{
+  "scope": "Sequential same-GPU fresh main, candidate, then Torch plus MPS control; one measured repeat at C16/C32 on reused first cohort. Descriptive attribution only, not independent quality qualification.",
+  "profiles": {
+    "main": [
+      {
+        "concurrency": 16,
+        "requests_per_repeat": [
+          320
+        ],
+        "repeats": 1,
+        "n_failed": 0,
+        "throughput_frames_s_mean": 693.122777529298,
+        "throughput_frames_s_runs": [
+          693.122777529298
+        ],
+        "ttfa_p50_ms_pooled": 1222.8329624049366,
+        "ttfa_p95_ms_pooled": 1830.9920092113325,
+        "rtf_mean": 0.5864436744876869,
+        "mean_audio_seconds": 4.40225
+      },
+      {
+        "concurrency": 32,
+        "requests_per_repeat": [
+          320
+        ],
+        "repeats": 1,
+        "n_failed": 0,
+        "throughput_frames_s_mean": 766.0570457634595,
+        "throughput_frames_s_runs": [
+          766.0570457634595
+        ],
+        "ttfa_p50_ms_pooled": 1938.0342639051378,
+        "ttfa_p95_ms_pooled": 3036.510010901839,
+        "rtf_mean": 1.0589867972770615,
+        "mean_audio_seconds": 4.4375
+      }
+    ],
+    "candidate": [
+      {
+        "concurrency": 16,
+        "requests_per_repeat": [
+          320
+        ],
+        "repeats": 1,
+        "n_failed": 0,
+        "throughput_frames_s_mean": 815.615922962288,
+        "throughput_frames_s_runs": [
+          815.615922962288
+        ],
+        "ttfa_p50_ms_pooled": 938.601640984416,
+        "ttfa_p95_ms_pooled": 1537.8939061891294,
+        "rtf_mean": 0.4991944261220827,
+        "mean_audio_seconds": 4.419875
+      },
+      {
+        "concurrency": 32,
+        "requests_per_repeat": [
+          320
+        ],
+        "repeats": 1,
+        "n_failed": 0,
+        "throughput_frames_s_mean": 929.3535763965319,
+        "throughput_frames_s_runs": [
+          929.3535763965319
+        ],
+        "ttfa_p50_ms_pooled": 1481.580258347094,
+        "ttfa_p95_ms_pooled": 2024.6404147241265,
+        "rtf_mean": 0.8702834316202954,
+        "mean_audio_seconds": 4.407625
+      }
+    ],
+    "torch_mps": [
+      {
+        "concurrency": 16,
+        "requests_per_repeat": [
+          320
+        ],
+        "repeats": 1,
+        "n_failed": 0,
+        "throughput_frames_s_mean": 783.3153752341492,
+        "throughput_frames_s_runs": [
+          783.3153752341492
+        ],
+        "ttfa_p50_ms_pooled": 1038.1224108859897,
+        "ttfa_p95_ms_pooled": 1736.27570993267,
+        "rtf_mean": 0.5193365145043993,
+        "mean_audio_seconds": 4.41325
+      },
+      {
+        "concurrency": 32,
+        "requests_per_repeat": [
+          320
+        ],
+        "repeats": 1,
+        "n_failed": 0,
+        "throughput_frames_s_mean": 864.2885789235269,
+        "throughput_frames_s_runs": [
+          864.2885789235269
+        ],
+        "ttfa_p50_ms_pooled": 1675.16261478886,
+        "ttfa_p95_ms_pooled": 2336.628743633631,
+        "rtf_mean": 0.938098809980805,
+        "mean_audio_seconds": 4.411
+      }
+    ]
+  },
+  "ratios": [
+    {
+      "concurrency": 16,
+      "candidate_over_main": 1.176726475314559,
+      "torch_mps_over_main": 1.1301249946313283,
+      "candidate_over_torch_mps": 1.041235687118338
+    },
+    {
+      "concurrency": 32,
+      "candidate_over_main": 1.2131649745096067,
+      "torch_mps_over_main": 1.1282300498420048,
+      "candidate_over_torch_mps": 1.075281565740512
+    }
+  ],
+  "quality": {
+    "vllm-final-fresh-main-c16": {
+      "n": 320,
+      "sim": 49.7515808224678,
+      "utmos": 4.191942715644837,
+      "wer": 0.01279499573500142,
+      "wer_counts": {
+        "substitutions": 33,
+        "deletions": 4,
+        "insertions": 8,
+        "hits": 3480
+      },
+      "wer_mean": 0.014247696747696747
+    },
+    "vllm-final-fresh-main-c32": {
+      "n": 320,
+      "sim": 49.840751212835315,
+      "utmos": 4.204756230860949,
+      "wer": 0.013079328973557009,
+      "wer_counts": {
+        "substitutions": 34,
+        "deletions": 5,
+        "insertions": 7,
+        "hits": 3478
+      },
+      "wer_mean": 0.014504696692196692
+    },
+    "vllm-final-fresh-candidate-c16": {
+      "n": 320,
+      "sim": 49.881991145014766,
+      "utmos": 4.1921438664197925,
+      "wer": 0.013647995450668183,
+      "wer_counts": {
+        "substitutions": 36,
+        "deletions": 4,
+        "insertions": 8,
+        "hits": 3477
+      },
+      "wer_mean": 0.015044087856587857
+    },
+    "vllm-final-fresh-candidate-c32": {
+      "n": 320,
+      "sim": 49.84041916131973,
+      "utmos": 4.195094320178032,
+      "wer": 0.011657662780779073,
+      "wer_counts": {
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+        "deletions": 5,
+        "insertions": 3,
+        "hits": 3479
+      },
+      "wer_mean": 0.01164623570873571
+    },
+    "vllm-final-fresh-torch_mps-c16": {
+      "n": 320,
+      "sim": 49.858167740702626,
+      "utmos": 4.184595277905464,
+      "wer": 0.01279499573500142,
+      "wer_counts": {
+        "substitutions": 34,
+        "deletions": 4,
+        "insertions": 7,
+        "hits": 3479
+      },
+      "wer_mean": 0.013952367077367078
+    },
+    "vllm-final-fresh-torch_mps-c32": {
+      "n": 320,
+      "sim": 49.67515196800232,
+      "utmos": 4.200169984251261,
+      "wer": 0.01279499573500142,
+      "wer_counts": {
+        "substitutions": 36,
+        "deletions": 5,
+        "insertions": 4,
+        "hits": 3476
+      },
+      "wer_mean": 0.012858842546342546
+    }
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/status.json b/evidence/minicpmo45-l20x-20261021/results/status.json
index 0ac6c0d0b..d99a61938 100644
--- a/evidence/minicpmo45-l20x-20261021/results/status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/status.json
@@ -7,9 +7,7 @@
     "passed": 67
   },
   "optimization_submitted": true,
-  "pending": [
-    "final same-GPU MPS attribution control"
-  ],
+  "pending": [],
   "candidate_pull_request": "https://github.com/vllm-project/vllm-omni/pull/9188",
   "candidate_cpu_tests_passed": 67,
   "candidate_tuning": "Completed historical candidate comparisons; strict and unused-holdout quality gates FAIL.",
@@ -23,5 +21,7 @@
   "final_pull_request_head": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
   "integrated_verdict": "FAIL",
   "integrated_quality_reason": "C16 WER and C32 WER/SIM upper bounds exceed frozen margins.",
-  "integrated_cpu_tests_passed": 108
+  "integrated_cpu_tests_passed": 108,
+  "final_controls": "Completed three ordered same-GPU profiles at C16/C32, one measured repeat each; descriptive attribution only.",
+  "user_objective": "Not achieved: no candidate qualified as throughput-optimal with the frozen speech-quality bounds."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/vllm-final-fresh-candidate.json.gz b/evidence/minicpmo45-l20x-20261021/results/vllm-final-fresh-candidate.json.gz
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new file mode 100644
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HcmV?d00001

diff --git a/evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py b/evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py
index 97ffb0581..3fd986088 100644
--- a/evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py
+++ b/evidence/minicpmo45-l20x-20261021/validator/plot_final_results.py
@@ -60,6 +60,15 @@ def main():
     handles, labels = axes[0, 0].get_legend_handles_labels()
     fig.legend(handles, labels, loc="lower center", ncol=2, bbox_to_anchor=(0.5, 0.04), fontsize=9)
     fig.suptitle("MiniCPM-o 4.5 · one L20X · Seed-TTS English · steady state")
+    verdict = json.loads(args.integrated.read_text())["verdict"]
+    fig.text(
+        0.5,
+        0.94,
+        f"Combined service / quality verdict: {verdict}",
+        ha="center",
+        color="#9e2828" if verdict != "PASS" else "#308664",
+        fontsize=10,
+    )
     fig.text(
         0.5,
         0.015,
@@ -68,7 +77,7 @@ def main():
         ha="center",
         fontsize=8,
     )
-    fig.tight_layout(rect=(0, 0.12, 1, 0.95))
+    fig.tight_layout(rect=(0, 0.12, 1, 0.90))
     args.out.parent.mkdir(parents=True, exist_ok=True)
     fig.savefig(args.out.with_suffix(".png"), dpi=160)
     svg = args.out.with_suffix(".svg")
diff --git a/evidence/minicpmo45-l20x-20261021/validator/vllm-pr-checks.json b/evidence/minicpmo45-l20x-20261021/validator/vllm-pr-checks.json
new file mode 100644
index 000000000..8b377d199
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/vllm-pr-checks.json
@@ -0,0 +1,77 @@
+{
+  "baseRefOid": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "headRefOid": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "isDraft": true,
+  "mergeable": "MERGEABLE",
+  "number": 9188,
+  "statusCheckRollup": [
+    {
+      "__typename": "CheckRun",
+      "completedAt": "2026-10-21T04:26:04Z",
+      "conclusion": "SUCCESS",
+      "detailsUrl": "https://github.com/vllm-project/vllm-omni/actions/runs/39543945829/job/119037756273",
+      "name": "build (3.11)",
+      "startedAt": "2026-10-21T04:25:24Z",
+      "status": "COMPLETED",
+      "workflowName": "Build Wheel"
+    },
+    {
+      "__typename": "CheckRun",
+      "completedAt": "2026-10-21T04:31:13Z",
+      "conclusion": "SUCCESS",
+      "detailsUrl": "https://github.com/vllm-project/vllm-omni/actions/runs/39543945807/job/119037755544",
+      "name": "Analyze",
+      "startedAt": "2026-10-21T04:25:24Z",
+      "status": "COMPLETED",
+      "workflowName": "CodeQL Advanced"
+    },
+    {
+      "__typename": "CheckRun",
+      "completedAt": "2026-10-21T04:26:25Z",
+      "conclusion": "SUCCESS",
+      "detailsUrl": "https://github.com/vllm-project/vllm-omni/actions/runs/39543945799/job/119037755815",
+      "name": "pre-commit",
+      "startedAt": "2026-10-21T04:25:24Z",
+      "status": "COMPLETED",
+      "workflowName": "pre-commit"
+    },
+    {
+      "__typename": "CheckRun",
+      "completedAt": "2026-10-21T04:26:13Z",
+      "conclusion": "SUCCESS",
+      "detailsUrl": "https://github.com/vllm-project/vllm-omni/actions/runs/39543945829/job/119037756118",
+      "name": "build (3.12)",
+      "startedAt": "2026-10-21T04:25:24Z",
+      "status": "COMPLETED",
+      "workflowName": "Build Wheel"
+    },
+    {
+      "__typename": "CheckRun",
+      "completedAt": "2026-10-21T04:31:06Z",
+      "conclusion": "SUCCESS",
+      "detailsUrl": "https://github.com/vllm-project/vllm-omni/runs/119039385295",
+      "name": "CodeQL",
+      "startedAt": "2026-10-21T04:31:04Z",
+      "status": "COMPLETED",
+      "workflowName": ""
+    },
+    {
+      "__typename": "CheckRun",
+      "completedAt": "2026-10-21T04:25:20Z",
+      "conclusion": "SUCCESS",
+      "detailsUrl": "https://probot.github.io/apps/dco/",
+      "name": "DCO",
+      "startedAt": "2026-10-21T04:25:19Z",
+      "status": "COMPLETED",
+      "workflowName": ""
+    },
+    {
+      "__typename": "StatusContext",
+      "context": "docs/readthedocs.org:vllm-omni",
+      "startedAt": "2026-10-21T04:48:01Z",
+      "state": "SUCCESS",
+      "targetUrl": "https://vllm--9188.org.readthedocs.build/projects/vllm-omni/en/9188/"
+    }
+  ],
+  "url": "https://github.com/vllm-project/vllm-omni/pull/9188"
+}

From 95b2146f8103a0b70d6df02328ad5293dfb7abb9 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:09:19 +0800
Subject: [PATCH 12/40] Freeze peer throughput target and audited untouched
 quality cohort

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2.json                     | 290 ++++++++++++++++++
 1 file changed, 290 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2.json
new file mode 100644
index 000000000..f61be6ea8
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2.json
@@ -0,0 +1,290 @@
+{
+  "frozen_at_utc": "2026-10-21T06:09:19.431010+00:00",
+  "goal": "Exceed the single-GPU peer engine at both C16 and C32 while preserving previously authorized speech quality margins.",
+  "peer_revision": "a4f4778f312791c2d190b48e521141887ed160c8",
+  "peer_profile": "track_s_fast_r11",
+  "peer_quality_note": "Fast published profile has unresolved own quality gates; throughput target only.",
+  "vllm_start_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "quality_reference_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "model_revision": "503e754207c94da6bb26850b4469f367c9ea3582",
+  "screening": "Use only original first64 tuning prompts; reused evaluation cohorts are descriptive regression only.",
+  "performance_protocol": "Same L20X, canonical prompts, audio-frame equivalent throughput. Initial peer reproduction: all six C, 320 requests, discard plus3 repeats, persistent server; final candidate and peer receive identical repeated comparison.",
+  "quality_holdout_ids": [
+    "common_voice_en_19770519-common_voice_en_19770516",
+    "common_voice_en_34321814-common_voice_en_34321812",
+    "common_voice_en_36068063-common_voice_en_36068064",
+    "common_voice_en_647713-common_voice_en_647712",
+    "common_voice_en_25186585-common_voice_en_25186583",
+    "common_voice_en_21658335-common_voice_en_21658337",
+    "common_voice_en_17369851-common_voice_en_17369849",
+    "common_voice_en_493740-common_voice_en_493738",
+    "common_voice_en_173534-common_voice_en_173540",
+    "common_voice_en_591530-common_voice_en_591529",
+    "common_voice_en_19748004-common_voice_en_19748007",
+    "common_voice_en_23700044-common_voice_en_23700045",
+    "common_voice_en_20030172-common_voice_en_20030174",
+    "common_voice_en_19726989-common_voice_en_19726990",
+    "common_voice_en_32683120-common_voice_en_32683121",
+    "common_voice_en_26933529-common_voice_en_26933532",
+    "common_voice_en_21314759-common_voice_en_21314758",
+    "common_voice_en_19043111-common_voice_en_19043109",
+    "common_voice_en_487077-common_voice_en_487079",
+    "common_voice_en_589496-common_voice_en_589494",
+    "common_voice_en_19843546-common_voice_en_19843549",
+    "common_voice_en_25710838-common_voice_en_25710836",
+    "common_voice_en_25745884-common_voice_en_25745889",
+    "common_voice_en_18672480-common_voice_en_18672484",
+    "common_voice_en_20068182-common_voice_en_20068195",
+    "common_voice_en_17288057-common_voice_en_17288059",
+    "common_voice_en_18012457-common_voice_en_18012447",
+    "common_voice_en_23316948-common_voice_en_23316944",
+    "common_voice_en_26554168-common_voice_en_26554171",
+    "common_voice_en_20235009-common_voice_en_20235010",
+    "common_voice_en_21129372-common_voice_en_21129375",
+    "common_voice_en_667155-common_voice_en_667154",
+    "common_voice_en_19294198-common_voice_en_19294200",
+    "common_voice_en_24681934-common_voice_en_24681937",
+    "common_voice_en_19176854-common_voice_en_19176856",
+    "common_voice_en_20791578-common_voice_en_20791579",
+    "common_voice_en_19972684-common_voice_en_19972807",
+    "common_voice_en_21619912-common_voice_en_21619910",
+    "common_voice_en_18557077-common_voice_en_18557074",
+    "common_voice_en_25204047-common_voice_en_25204043",
+    "common_voice_en_30665077-common_voice_en_30665079",
+    "common_voice_en_1205005-common_voice_en_1205007",
+    "common_voice_en_18313326-common_voice_en_18313324",
+    "common_voice_en_18229682-common_voice_en_18229695",
+    "common_voice_en_20535791-common_voice_en_20535795",
+    "common_voice_en_682528-common_voice_en_682530",
+    "common_voice_en_24989570-common_voice_en_24989571",
+    "common_voice_en_18998723-common_voice_en_18998722",
+    "common_voice_en_19690002-common_voice_en_19690003",
+    "common_voice_en_17275818-common_voice_en_17275817",
+    "common_voice_en_125386-common_voice_en_125389",
+    "common_voice_en_25568854-common_voice_en_25568855",
+    "common_voice_en_25271639-common_voice_en_25271640",
+    "common_voice_en_19767978-common_voice_en_19767980",
+    "common_voice_en_19083094-common_voice_en_19083091",
+    "common_voice_en_673471-common_voice_en_673472",
+    "common_voice_en_28827679-common_voice_en_28827709",
+    "common_voice_en_573135-common_voice_en_573138",
+    "common_voice_en_182275-common_voice_en_182276",
+    "common_voice_en_19748971-common_voice_en_19748974",
+    "common_voice_en_33604595-common_voice_en_33604556",
+    "common_voice_en_19641039-common_voice_en_19641038",
+    "common_voice_en_24814747-common_voice_en_24814749",
+    "common_voice_en_28917649-common_voice_en_28917648",
+    "common_voice_en_32641373-common_voice_en_32641375",
+    "common_voice_en_19669708-common_voice_en_19669702",
+    "common_voice_en_25428174-common_voice_en_25428180",
+    "common_voice_en_652024-common_voice_en_652023",
+    "common_voice_en_20289354-common_voice_en_20289353",
+    "common_voice_en_24009789-common_voice_en_24009790",
+    "common_voice_en_25347734-common_voice_en_25347736",
+    "common_voice_en_23729047-common_voice_en_23729051",
+    "common_voice_en_19981298-common_voice_en_19981297",
+    "common_voice_en_21762342-common_voice_en_21762343",
+    "common_voice_en_23733663-common_voice_en_23733664",
+    "common_voice_en_17277080-common_voice_en_17277082",
+    "common_voice_en_20812017-common_voice_en_20812020",
+    "common_voice_en_23718813-common_voice_en_23718814",
+    "common_voice_en_17851231-common_voice_en_17851256",
+    "common_voice_en_37238105-common_voice_en_37238104",
+    "common_voice_en_21059484-common_voice_en_21059406",
+    "common_voice_en_23640041-common_voice_en_23640043",
+    "common_voice_en_20273907-common_voice_en_20273911",
+    "common_voice_en_18554437-common_voice_en_18554439",
+    "common_voice_en_24988318-common_voice_en_24988361",
+    "common_voice_en_20888046-common_voice_en_20888051",
+    "common_voice_en_20089981-common_voice_en_20090015",
+    "common_voice_en_570619-common_voice_en_570622",
+    "common_voice_en_24567654-common_voice_en_24567661",
+    "common_voice_en_19793104-common_voice_en_19793103",
+    "common_voice_en_19049396-common_voice_en_19049395",
+    "common_voice_en_18994734-common_voice_en_18994738",
+    "common_voice_en_20317297-common_voice_en_20317300",
+    "common_voice_en_17375252-common_voice_en_17375256",
+    "common_voice_en_37133940-common_voice_en_37134010",
+    "common_voice_en_502839-common_voice_en_502843",
+    "common_voice_en_23381412-common_voice_en_23381414",
+    "common_voice_en_19916471-common_voice_en_19916474",
+    "common_voice_en_19767707-common_voice_en_19767710",
+    "common_voice_en_17347410-common_voice_en_17347409",
+    "common_voice_en_648428-common_voice_en_648429",
+    "common_voice_en_25186585-common_voice_en_25186586",
+    "common_voice_en_19730681-common_voice_en_19730680",
+    "common_voice_en_27935469-common_voice_en_27935466",
+    "common_voice_en_24423943-common_voice_en_24423945",
+    "common_voice_en_20304148-common_voice_en_20304149",
+    "common_voice_en_22793454-common_voice_en_22793458",
+    "common_voice_en_2586258-common_voice_en_2586259",
+    "common_voice_en_23733663-common_voice_en_23733666",
+    "common_voice_en_17519982-common_voice_en_17519985",
+    "common_voice_en_33322125-common_voice_en_33322126",
+    "common_voice_en_36516974-common_voice_en_36516976",
+    "common_voice_en_25896925-common_voice_en_26641098",
+    "common_voice_en_18902273-common_voice_en_18902274",
+    "common_voice_en_30735432-common_voice_en_30735433",
+    "common_voice_en_19622969-common_voice_en_19622970",
+    "common_voice_en_29345455-common_voice_en_29345456",
+    "common_voice_en_21555942-common_voice_en_21555944",
+    "common_voice_en_20806032-common_voice_en_20806033",
+    "common_voice_en_25694807-common_voice_en_25694816",
+    "common_voice_en_21139160-common_voice_en_21139162",
+    "common_voice_en_628642-common_voice_en_628644",
+    "common_voice_en_550301-common_voice_en_550303",
+    "common_voice_en_537760-common_voice_en_537763",
+    "common_voice_en_20938865-common_voice_en_20938866",
+    "common_voice_en_22810002-common_voice_en_22810003",
+    "common_voice_en_23998981-common_voice_en_23998980",
+    "common_voice_en_29890305-common_voice_en_29890301",
+    "common_voice_en_615162-common_voice_en_615158",
+    "common_voice_en_17986345-common_voice_en_17986347",
+    "common_voice_en_566283-common_voice_en_566281",
+    "common_voice_en_23374825-common_voice_en_23374821",
+    "common_voice_en_26554168-common_voice_en_26554170",
+    "common_voice_en_21653057-common_voice_en_21653087",
+    "common_voice_en_18889688-common_voice_en_18889687",
+    "common_voice_en_23650405-common_voice_en_23650404",
+    "common_voice_en_27434681-common_voice_en_27434683",
+    "common_voice_en_17738848-common_voice_en_17744571",
+    "common_voice_en_22972881-common_voice_en_22972879",
+    "common_voice_en_20791751-common_voice_en_20791752",
+    "common_voice_en_23305810-common_voice_en_23305815",
+    "common_voice_en_27404277-common_voice_en_27404276",
+    "common_voice_en_20342901-common_voice_en_20342897",
+    "common_voice_en_31005683-common_voice_en_31005688",
+    "common_voice_en_33907-common_voice_en_33908",
+    "common_voice_en_22728555-common_voice_en_22728554",
+    "common_voice_en_32298822-common_voice_en_32298846",
+    "common_voice_en_24989570-common_voice_en_24989573",
+    "common_voice_en_20236234-common_voice_en_20236236",
+    "common_voice_en_20080005-common_voice_en_20080006",
+    "common_voice_en_2586258-common_voice_en_2586260",
+    "common_voice_en_19727183-common_voice_en_19727184",
+    "common_voice_en_25662916-common_voice_en_25662913",
+    "common_voice_en_565900-common_voice_en_565902",
+    "common_voice_en_575287-common_voice_en_575288",
+    "common_voice_en_96260-common_voice_en_96263",
+    "common_voice_en_13900-common_voice_en_13901",
+    "common_voice_en_35042682-common_voice_en_35042750",
+    "common_voice_en_571544-common_voice_en_571546",
+    "common_voice_en_20907200-common_voice_en_20907217",
+    "common_voice_en_27733062-common_voice_en_27733063",
+    "common_voice_en_19284142-common_voice_en_19284143",
+    "common_voice_en_21319256-common_voice_en_21319257",
+    "common_voice_en_19726989-common_voice_en_19726988",
+    "common_voice_en_21370640-common_voice_en_21370642",
+    "common_voice_en_509177-common_voice_en_509176",
+    "common_voice_en_19770519-common_voice_en_19770517",
+    "common_voice_en_17271507-common_voice_en_17271509",
+    "common_voice_en_15265-common_voice_en_15266",
+    "common_voice_en_205647-common_voice_en_205649",
+    "common_voice_en_25319086-common_voice_en_25319087",
+    "common_voice_en_18828571-common_voice_en_18828573",
+    "common_voice_en_33322125-common_voice_en_33322130",
+    "common_voice_en_489724-common_voice_en_489726",
+    "common_voice_en_20304708-common_voice_en_20304710",
+    "common_voice_en_30619661-common_voice_en_30619659",
+    "common_voice_en_35299046-common_voice_en_35299043",
+    "common_voice_en_25748530-common_voice_en_25748532",
+    "common_voice_en_17277080-common_voice_en_17277083",
+    "common_voice_en_18681919-common_voice_en_18681920",
+    "common_voice_en_21877403-common_voice_en_21877404",
+    "common_voice_en_19284142-common_voice_en_19284144",
+    "common_voice_en_17263780-common_voice_en_17263782",
+    "common_voice_en_566283-common_voice_en_566282",
+    "common_voice_en_19449066-common_voice_en_19449075",
+    "common_voice_en_24518104-common_voice_en_24518111",
+    "common_voice_en_590785-common_voice_en_590791",
+    "common_voice_en_26933529-common_voice_en_26933531",
+    "common_voice_en_21499767-common_voice_en_21499786",
+    "common_voice_en_32697372-common_voice_en_32697449",
+    "common_voice_en_31776611-common_voice_en_31776613",
+    "common_voice_en_19401124-common_voice_en_19401125",
+    "common_voice_en_24423943-common_voice_en_24423942",
+    "common_voice_en_19854924-common_voice_en_19854923",
+    "common_voice_en_18962809-common_voice_en_18962813",
+    "common_voice_en_31499885-common_voice_en_31499889",
+    "common_voice_en_2072999-common_voice_en_2073000",
+    "common_voice_en_29890305-common_voice_en_29890302",
+    "common_voice_en_23699312-common_voice_en_23699314",
+    "common_voice_en_20041534-common_voice_en_20041536",
+    "common_voice_en_93674-common_voice_en_93675",
+    "common_voice_en_17389984-common_voice_en_17389988",
+    "common_voice_en_19527999-common_voice_en_19528000",
+    "common_voice_en_17429166-common_voice_en_17429168",
+    "common_voice_en_18057869-common_voice_en_18057867",
+    "common_voice_en_26952530-common_voice_en_26952588",
+    "common_voice_en_19739025-common_voice_en_19739027",
+    "common_voice_en_23728823-common_voice_en_23728826",
+    "common_voice_en_23316948-common_voice_en_23316945",
+    "common_voice_en_21777264-common_voice_en_21777262",
+    "common_voice_en_33563095-common_voice_en_33563097",
+    "common_voice_en_31497532-common_voice_en_31497530",
+    "common_voice_en_19619855-common_voice_en_19619858",
+    "common_voice_en_493276-common_voice_en_493277",
+    "common_voice_en_17920116-common_voice_en_17920112",
+    "common_voice_en_586741-common_voice_en_586742",
+    "common_voice_en_19944630-common_voice_en_19944631",
+    "common_voice_en_19934187-common_voice_en_19934317",
+    "common_voice_en_20177004-common_voice_en_20177058",
+    "common_voice_en_19698719-common_voice_en_19698718",
+    "common_voice_en_21184954-common_voice_en_21184958",
+    "common_voice_en_19669708-common_voice_en_19669704",
+    "common_voice_en_20289354-common_voice_en_20289351",
+    "common_voice_en_24567654-common_voice_en_24567652",
+    "common_voice_en_19124597-common_voice_en_19124596",
+    "common_voice_en_23726733-common_voice_en_23726734",
+    "common_voice_en_63703-common_voice_en_63702",
+    "common_voice_en_570615-common_voice_en_570616",
+    "common_voice_en_25821292-common_voice_en_25821294",
+    "common_voice_en_209233-common_voice_en_209236",
+    "common_voice_en_23618179-common_voice_en_23618177",
+    "common_voice_en_19869780-common_voice_en_19869779",
+    "common_voice_en_20190570-common_voice_en_20190568",
+    "common_voice_en_19083094-common_voice_en_19083093",
+    "common_voice_en_485101-common_voice_en_485099",
+    "common_voice_en_22575787-common_voice_en_22575789",
+    "common_voice_en_23804758-common_voice_en_23804761",
+    "common_voice_en_15265-common_voice_en_15268",
+    "common_voice_en_36516974-common_voice_en_36516979",
+    "common_voice_en_21106663-common_voice_en_21106664",
+    "common_voice_en_18781918-common_voice_en_18781919",
+    "common_voice_en_31892400-common_voice_en_31892402",
+    "common_voice_en_20640019-common_voice_en_20640018",
+    "common_voice_en_28316626-common_voice_en_28316630",
+    "common_voice_en_15735839-common_voice_en_15735837",
+    "common_voice_en_19744568-common_voice_en_19744566",
+    "common_voice_en_17879420-common_voice_en_17879438",
+    "common_voice_en_32697372-common_voice_en_32697370",
+    "common_voice_en_19789569-common_voice_en_19789567",
+    "common_voice_en_2072999-common_voice_en_2324746",
+    "common_voice_en_20297680-common_voice_en_20297682",
+    "common_voice_en_21851999-common_voice_en_21851998",
+    "common_voice_en_20583510-common_voice_en_20583509",
+    "common_voice_en_19741922-common_voice_en_19741926",
+    "common_voice_en_37262846-common_voice_en_37262842",
+    "common_voice_en_20042516-common_voice_en_20042515"
+  ],
+  "quality_holdout_n": 256,
+  "quality_id_hash": "6bf3adb8509075c074a9955a68ff34674211542c2a079855b3676d1bbdc40be7",
+  "holdout_audit": "Original tuning indices128:384 unused in saved generation runs and stage profiling. Proposed indices64:384 failed the coverage assertion and were never frozen or generated in this round.",
+  "quality_concurrency": [
+    1,
+    16,
+    32
+  ],
+  "margins": {
+    "wer_percentage_points": 0.2,
+    "sim_x100_drop": 0.5,
+    "utmos_drop": 0.05
+  },
+  "quality_statistic": "Paired prompt bootstrap, one-sided95 upper degradation bound,20000 draws seed20261022; all nine bounds must pass. Holdout generated only after candidate selection.",
+  "prior_verdicts": "All prior strict and noninferiority FAIL results remain unchanged.",
+  "hypotheses": [
+    "Profile Token2Wav flow/HiFT precision and launch costs against peer",
+    "Batch graphs and scheduling with resident state",
+    "Talker multi-step scheduling if measured stage breakdown supports it"
+  ]
+}

From 149ec73e3435f6159159b6535595ab2bc1b5b5e5 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:20:50 +0800
Subject: [PATCH 13/40] Freeze FP16 and stage-capacity screening hypotheses

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-capacity32.json          | 14 ++++++++++++
 .../peer-round2-environment-addendum.json     |  8 +++++++
 .../plan/peer-round2-fp16-resident.json       | 22 +++++++++++++++++++
 .../plan/peer-round2-fp16-screen.json         |  8 +++++++
 4 files changed, 52 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-capacity32.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-environment-addendum.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-resident.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-screen.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-capacity32.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-capacity32.json
new file mode 100644
index 000000000..f34700216
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-capacity32.json
@@ -0,0 +1,14 @@
+{
+  "frozen_at_utc": "2026-10-21T06:17:42.002236+00:00",
+  "hypothesis": "Align all three stage capacities with C32 to remove a possible active-sequence cap; keep FP32 flow, Torch speaker, MPS and sampling unchanged.",
+  "changes": {
+    "stage_max_num_seqs": [
+      32,
+      32,
+      32
+    ],
+    "talker_kv_cache_bytes": 8589934592
+  },
+  "kv_reason": "Stage1 32*4096 maximum context needs twice the original 4GiB capacity; avoid relying on unsupported physical-preemption replay.",
+  "screen": "Original first64 tuning prompts, C16/C32, discard plus1 measured repeat; compare against native Torch+MPS screen, not independent quality qualification."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-environment-addendum.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-environment-addendum.json
new file mode 100644
index 000000000..2af644dbc
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-environment-addendum.json
@@ -0,0 +1,8 @@
+{
+  "recorded_at_utc": "2026-10-21T06:19:15.937522+00:00",
+  "initial_startup": "Failed before service readiness because torchaudio.load requires TorchCodec, absent from pinned engine.lock.",
+  "change": "Install torchcodec0.14.0+cu130 without dependency upgrades. All locked package versions, engine source, model and config retained.",
+  "validation": "Official HT_ref_audio.wav loads as mono96256samples at16000Hz.",
+  "source": "https://github.com/meta-pytorch/torchcodec",
+  "sample_or_gate_changes": false
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-resident.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-resident.json
new file mode 100644
index 000000000..8ca03523e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-resident.json
@@ -0,0 +1,22 @@
+{
+  "frozen_at_utc": "2026-10-21T06:15:04.226959+00:00",
+  "hypothesis": "Enable existing fused DiT and resident attention caches for CUDA FP16 flow rather than the current ragged fallback; preserve default FP32 and NPU gating.",
+  "changes": [
+    "Accept matching FP16 Q/K/V in tiled attention",
+    "Accumulate softmax and outputs in FP32 but cast probabilities to V dtype for FP16 Tensor Core dot",
+    "Allow CUDA fused path when compute and stored attention cache are both FP16"
+  ],
+  "kernel_gate": "Compare against PyTorch MATH SDPA computed in FP32 and rounded to input dtype, atol0.002 rtol0.002; cover masks including fully masked query rows, noncontiguous pooled K/V and repeated/permuted pool rows. FP32 regression unchanged.",
+  "service_gate": "No performance/quality qualification from numerical kernels. Retain frozen round2 speech bounds and peer throughput target.",
+  "source_revision": "86732dde68fcfc90455e2db663c85f6e4fbc375d",
+  "pre_service_checks": {
+    "attention_gpu": 26,
+    "dit_regression": 6,
+    "changed_file_precommit": "PASS after fixing optional-mask type narrowing"
+  },
+  "first_service_screen": {
+    "profile": "fp16-fused-mps",
+    "cfm_slot_pool": false,
+    "scope": "First isolate restored FP16 fused body under existing default arena caching. New kernel also supports optional resident pool; turning that on is a separate later screen."
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-screen.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-screen.json
new file mode 100644
index 000000000..cc26b564f
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-screen.json
@@ -0,0 +1,8 @@
+{
+  "frozen_at_utc": "2026-10-21T06:11:02.764641+00:00",
+  "hypothesis": "FP16 flow may reduce the dominant Code2Wav compute time while preserving acceptable generated speech quality. Compare against otherwise identical Torch-speaker+MPS, not the failed CPU-reference speaker candidate.",
+  "changed_variable": "token2wav_float16 false -> true",
+  "scope": "64 original tuning prompts, C1/16/32, one discard and one measured repeat. Warmup/completion validity required before proceeding; no qualification from this screen.",
+  "next_gate": "Inspect numerical/audio health and native speech scorers before promotion; preserve failed outputs.",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12"
+}

From 1aff9ee7a18b8f05307e0cd537dc820a173ec62a Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:34:59 +0800
Subject: [PATCH 14/40] Record capacity screen and freeze FP16 pool trial

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-fp16-pool.json                  | 12 ++++++++++++
 .../plan/peer-round2-profile-exclusion.json          | 11 +++++++++++
 .../results/peer-round2-capacity32-screen.json       | 12 ++++++++++++
 3 files changed, 35 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-pool.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-profile-exclusion.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-capacity32-screen.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-pool.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-pool.json
new file mode 100644
index 000000000..4b2a2cca1
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-fp16-pool.json
@@ -0,0 +1,12 @@
+{
+  "frozen_at_utc": "2026-10-21T06:30:41.036889+00:00",
+  "source_revision": "86732dde68fcfc90455e2db663c85f6e4fbc375d",
+  "hypothesis": "Resident K/V and merged prefix offsets may reduce copying and fragmented audio batches after FP16 fused-body support.",
+  "changes_vs_fp16_fused_screen": {
+    "cfm_slot_pool": true,
+    "cfm_row_offset_merge": true
+  },
+  "unchanged": "micro_batch_size4, stage capacities16, Torch speaker, MPS, sampling and64 tuning prompts",
+  "limitation": "Current pool has micro_batch_size+max(2,micro_batch_size//8)=6 stream slots; measure fallback behavior before enlarging it.",
+  "numerical_evidence": "26 GPU attention cases (including repeated resident rows) and6 DiT regression cases PASS; generated speech gate still required."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-profile-exclusion.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-profile-exclusion.json
new file mode 100644
index 000000000..df13ef917
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-profile-exclusion.json
@@ -0,0 +1,11 @@
+{
+  "recorded_at_utc": "2026-10-21T06:30:41.008686+00:00",
+  "affected_run": "peer-repeated/c1/run1",
+  "event": "Two short py-spy stack snapshots were taken while diagnosing apparent startup delay; artifact timestamps show run0 had already finished, so snapshots overlap measured run1.",
+  "policy": "Retain raw run1 but exclude it from unprofiled C1 aggregates. Runs2/3 and other concurrency cells remain unprofiled. Final confirmation requires fresh unprofiled repeats for both engines.",
+  "snapshots_local_times": [
+    "2026-10-21T14:28:51+08:00",
+    "2026-10-21T14:29:06+08:00"
+  ],
+  "discard_run0_summary_local_time": "2026-10-21T14:28:15+08:00"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-capacity32-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-capacity32-screen.json
new file mode 100644
index 000000000..e5f64fa06
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-capacity32-screen.json
@@ -0,0 +1,12 @@
+{
+  "scope": "64 previously used tuning prompts, single measured repeat; not formal performance qualification.",
+  "baseline": {
+    "16": 739.5967989351692,
+    "32": 848.8140884415932
+  },
+  "capacity32": {
+    "16": 772.1937892034148,
+    "32": 780.2965904392426
+  },
+  "decision": "Do not promote capacity32 alone: C16 improves slightly but C32 decreases. Retain as conditional hypothesis only if a later compute optimization changes the bottleneck."
+}

From b4488671753ee4cba00f2e80a3d63bb8fbb33868 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:36:57 +0800
Subject: [PATCH 15/40] Freeze round-two holdout evaluator and record FP16
 regression

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../peer-round2-native-fp16-screen.json       |  60 +++++++++++
 .../validator/peer_round2_holdout.py          |  62 +++++++++++
 .../validator/peer_round2_noninferiority.py   | 101 ++++++++++++++++++
 3 files changed, 223 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-native-fp16-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_holdout.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_noninferiority.py

diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-fp16-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-fp16-screen.json
new file mode 100644
index 000000000..65b78ab78
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-fp16-screen.json
@@ -0,0 +1,60 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "scope": "64 reused tuning prompts, one measured repeat after discard; not final qualification",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "profiles": {
+    "screen-torch-mps": {
+      "1": {
+        "throughput_frames_s": 192.23217408312624,
+        "ttfa_p50_s": 0.2981584994122386,
+        "ttfa_p95_s": 0.32917039170861245,
+        "rtf_mean": 0.13143682723026684,
+        "n_requests": 64,
+        "n_failed": 0
+      },
+      "16": {
+        "throughput_frames_s": 739.5967989351692,
+        "ttfa_p50_s": 1.0429030349478126,
+        "ttfa_p95_s": 1.9607031137216837,
+        "rtf_mean": 0.5223557244375909,
+        "n_requests": 64,
+        "n_failed": 0
+      },
+      "32": {
+        "throughput_frames_s": 848.8140884415932,
+        "ttfa_p50_s": 1.8589568389579654,
+        "ttfa_p95_s": 3.588924608658999,
+        "rtf_mean": 0.8924367367600894,
+        "n_requests": 64,
+        "n_failed": 0
+      }
+    },
+    "screen-fp16-mps": {
+      "1": {
+        "throughput_frames_s": 177.41427620623176,
+        "ttfa_p50_s": 0.3619168996810913,
+        "ttfa_p95_s": 0.39645095150917764,
+        "rtf_mean": 0.14300575530569176,
+        "n_requests": 64,
+        "n_failed": 0
+      },
+      "16": {
+        "throughput_frames_s": 486.4202406761821,
+        "ttfa_p50_s": 1.40935737779364,
+        "ttfa_p95_s": 2.4148101587314157,
+        "rtf_mean": 0.8004005516329982,
+        "n_requests": 64,
+        "n_failed": 0
+      },
+      "32": {
+        "throughput_frames_s": 518.2758193930315,
+        "ttfa_p50_s": 3.06098780175671,
+        "ttfa_p95_s": 4.743225209414959,
+        "rtf_mean": 1.462588532126349,
+        "n_requests": 64,
+        "n_failed": 0
+      }
+    }
+  },
+  "decision": "Native FP16 alone regresses; continue fused-body and resident-pool hypotheses. Quality scoring pending."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_holdout.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_holdout.py
new file mode 100644
index 000000000..35431f0ed
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_holdout.py
@@ -0,0 +1,62 @@
+import argparse
+import asyncio
+import json
+from pathlib import Path
+
+from bench.adapters import get_adapter
+from bench.client import make_session
+from bench.protocol import closed_loop, evaluate_run, save_run
+from bench.workload import canonical_requests, load_seed_tts_rows, make_id_sets
+
+
+async def main():
+    p = argparse.ArgumentParser()
+    p.add_argument("--adapter", required=True)
+    p.add_argument("--url", required=True)
+    p.add_argument("--out", required=True)
+    p.add_argument("--concurrency", type=int, nargs="+", default=[1, 16, 32])
+    p.add_argument("--requests", type=int, default=256)
+    p.add_argument("--repeats", type=int, default=1)
+    p.add_argument("--plan", type=Path, required=True)
+
+    a = p.parse_args()
+    out = Path(a.out)
+    out.mkdir(parents=True, exist_ok=False)
+    rows = load_seed_tts_rows()
+    sets = make_id_sets(rows)
+    frozen = json.loads(a.plan.read_text())
+    ids = frozen["quality_holdout_ids"]
+    if len(ids) != 256 or len(set(ids)) != 256 or list(sets.tuning_pool[128:384]) != ids:
+        raise ValueError("Holdout IDs differ from the frozen unused cohort")
+    if a.requests != 256 or set(a.concurrency) != {1, 16, 32}:
+        raise ValueError("Quality qualification requires 256 prompts at C1/C16/C32")
+    adapter = get_adapter(a.adapter)
+    # Exploratory steady-state baseline. No restart between cells; explicitly
+    # distinct from the reference campaign's fresh-server certification.
+    plan = (vars(a) | {"plan": str(a.plan)}) | {
+        "cache_policy": "none",
+        "qualification": "exploratory",
+        "ids": sets.to_json(),
+    }
+    (out / "plan.json").write_text(json.dumps(plan, indent=2))
+    async with make_session() as session:
+        for c in a.concurrency:
+            warm = canonical_requests(rows, sets.warmup(c))
+            traces = await closed_loop(session, a.url, adapter, warm, c, timeout_s=180)
+            result = evaluate_run("warmup", c, traces, measured=False)
+            save_run(result, out / f"c{c}" / "warmup")
+            if any(not r.ok for r in result.per_request):
+                raise RuntimeError(f"C{c} warmup failed; inspect saved traces")
+            reqs = canonical_requests(rows, ids)
+            for k in range(a.repeats + 1):
+                traces = await closed_loop(
+                    session, a.url, adapter, reqs, c, timeout_s=180, record_raw=True
+                )
+                result = evaluate_run(f"run{k}", c, traces, measured=k > 0)
+                save_run(result, out / f"c{c}" / f"run{k}")
+                print(json.dumps(result.summary()), flush=True)
+                if any(not r.ok for r in result.per_request):
+                    raise RuntimeError(f"C{c} run{k} failed; inspect saved traces")
+
+
+asyncio.run(main())
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_noninferiority.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_noninferiority.py
new file mode 100644
index 000000000..d5cb3f392
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_noninferiority.py
@@ -0,0 +1,101 @@
+"""Frozen, paired prompt bootstrap for the round-two frozen 256-prompt holdout."""
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+
+
+def evaluate(baseline, candidate, margins, expected_ids):
+    b, c = baseline["rows"], candidate["rows"]
+    if len(expected_ids) != 256 or len(set(expected_ids)) != 256:
+        raise ValueError("Expected exactly 256 unique frozen IDs")
+    if set(b) != set(expected_ids) or set(c) != set(expected_ids):
+        raise ValueError("Scores must exactly match the frozen holdout IDs")
+    if any(set(doc["tasks"]) != {"wer", "sim", "utmos"} for doc in (baseline, candidate)):
+        raise ValueError("Incomplete scorers")
+    ids = sorted(b)
+    rng = np.random.default_rng(20261022)
+    draws = rng.integers(0, len(ids), size=(20000, len(ids)))
+    result = {}
+    for metric in ("wer_percentage_points", "sim_x100_drop", "utmos_drop"):
+        if metric == "wer_percentage_points":
+            values = []
+            for rows in (b, c):
+                errors = np.array(
+                    [
+                        sum(rows[i]["wer"][k] for k in ("substitutions", "deletions", "insertions"))
+                        for i in ids
+                    ]
+                )
+                words = np.array(
+                    [
+                        sum(rows[i]["wer"][k] for k in ("substitutions", "deletions", "hits"))
+                        for i in ids
+                    ]
+                )
+                if np.any(words <= 0):
+                    raise ValueError("Invalid reference count")
+                values.append((errors, words))
+            if not np.array_equal(values[0][1], values[1][1]):
+                raise ValueError("Different reference denominators")
+            point = 100 * (
+                values[1][0].sum() / values[1][1].sum() - values[0][0].sum() / values[0][1].sum()
+            )
+            distribution = 100 * (
+                (values[1][0] - values[0][0])[draws].sum(axis=1) / values[0][1][draws].sum(axis=1)
+            )
+        else:
+            key = "sim" if metric.startswith("sim") else "utmos"
+            delta = np.array([b[i][key] - c[i][key] for i in ids])
+            point = delta.mean()
+            distribution = delta[draws].mean(axis=1)
+        upper = float(np.percentile(distribution, 95))
+        if not np.isfinite(distribution).all() or not np.isfinite(point):
+            raise ValueError("Nonfinite scores")
+        result[metric] = {
+            "degradation": float(point),
+            "upper_one_sided_95": upper,
+            "margin": margins[metric],
+            "verdict": "PASS" if upper <= margins[metric] else "FAIL",
+        }
+    return {
+        "n": len(ids),
+        "metrics": result,
+        "verdict": "PASS" if all(x["verdict"] == "PASS" for x in result.values()) else "FAIL",
+    }
+
+
+def main():
+    p = argparse.ArgumentParser()
+    p.add_argument("--plan", type=Path, required=True)
+    p.add_argument("--quality-dir", type=Path, required=True)
+    p.add_argument("--out", type=Path, required=True)
+    a = p.parse_args()
+    plan = json.loads(a.plan.read_text())
+    report = {"scope": "Unused holdout noninferiority; original strict gate unchanged", "cells": {}}
+    try:
+        for concurrency in plan["quality_concurrency"]:
+            docs = [
+                json.loads(
+                    (a.quality_dir / f"peer-round2-holdout-{role}-c{concurrency}.json").read_text()
+                )
+                for role in ("main", "candidate")
+            ]
+            if any(set(doc["rows"]) != set(plan["quality_holdout_ids"]) for doc in docs):
+                raise ValueError("Outputs do not match frozen unused holdout IDs")
+            report["cells"][str(concurrency)] = evaluate(
+                *docs, plan["margins"], plan["quality_holdout_ids"]
+            )
+        report["verdict"] = (
+            "PASS" if all(x["verdict"] == "PASS" for x in report["cells"].values()) else "FAIL"
+        )
+    except (OSError, ValueError, KeyError) as exc:
+        report.update(verdict="INCONCLUSIVE", reason=str(exc))
+    a.out.write_text(json.dumps(report, indent=2) + "\n")
+    print(json.dumps(report))
+
+
+if __name__ == "__main__":
+    main()

From f3cea5a6b6cce8096f3417dc0f34e311413e33d6 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:39:24 +0800
Subject: [PATCH 16/40] Freeze FP32 batch-width screening hypothesis

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-batch16.json                     | 11 +++++++++++
 1 file changed, 11 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json
new file mode 100644
index 000000000..606512662
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json
@@ -0,0 +1,11 @@
+{
+  "frozen_at_utc": "2026-10-21T06:39:12.499372+00:00",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "Increase Whole-Euler microbatch from4 to16 to reduce serial replay at high concurrency.",
+  "changes": {
+    "micro_batch_size": 16
+  },
+  "unchanged": "FP32 flow, default nonresident cache, Torch speaker, MPS, stage capacities16, canonical64 tuning prompts",
+  "protocol": "C1/C16/C32,64 reused tuning prompts, discard then one measured repeat. Quality screening follows; no holdout consumption.",
+  "decision": "Promote only if service throughput improves; a numerical dtype change is not part of this screen."
+}

From e4cdac35952fbcda3935bd5badce641b7381a2af Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:44:19 +0800
Subject: [PATCH 17/40] Separate stage diagnostics from batch-width timing

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../minicpmo45-l20x-20261021/plan/peer-round2-batch16.json     | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json
index 606512662..4e0b0f8b2 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch16.json
@@ -7,5 +7,6 @@
   },
   "unchanged": "FP32 flow, default nonresident cache, Torch speaker, MPS, stage capacities16, canonical64 tuning prompts",
   "protocol": "C1/C16/C32,64 reused tuning prompts, discard then one measured repeat. Quality screening follows; no holdout consumption.",
-  "decision": "Promote only if service throughput improves; a numerical dtype change is not part of this screen."
+  "decision": "Promote only if service throughput improves; a numerical dtype change is not part of this screen.",
+  "diagnostic_after_screen": "Separate C32 stage-metrics request window on the same first64 tuning IDs, after throughput summaries are saved; excluded from performance aggregates."
 }

From fdd3fd8dc0ff7abf164a235a1e361983d7ec0f12 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:49:24 +0800
Subject: [PATCH 18/40] Record FP16 screening failure and runtime dispatch
 diagnosis

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-dispatch-fix.json        |   8 +
 .../results/peer-round2-fp16-pool-screen.json |  55 ++++++
 .../results/peer-round2-screen-quality.json   | 157 ++++++++++++++++++
 3 files changed, 220 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-fp16-pool-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json
new file mode 100644
index 000000000..296756b20
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json
@@ -0,0 +1,8 @@
+{
+  "frozen_at_utc": "2026-10-21T06:48:06.501149+00:00",
+  "parent_revision": "86732dde68fcfc90455e2db663c85f6e4fbc375d",
+  "hypothesis": "Enable CUDA FP16 at the remaining _ragged_body runtime gate; test the actual service dispatch against the ragged numerical reference.",
+  "validation": "New dispatch test must fail on parent then pass after fix; rerun DiT regressions before service screen.",
+  "service": "Same64 tuning prompts,C1/C16/C32,discard plus one measured repeat; only runtime dispatch changed vs nominal fp16-fused screen.",
+  "quality": "Existing noninferiority margins unchanged; reserved256 remain unused."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-fp16-pool-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-fp16-pool-screen.json
new file mode 100644
index 000000000..24146b195
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-fp16-pool-screen.json
@@ -0,0 +1,55 @@
+{
+  "source_revision": "86732dde68fcfc90455e2db663c85f6e4fbc375d",
+  "verdict": "FAIL",
+  "scope": "Screening throughput regression only; quality qualification pending.",
+  "cells": {
+    "1": {
+      "throughput_frames_s": 190.1563748436996,
+      "ttfa_p50_s": 0.3220428288914263,
+      "ttfa_p95_s": 0.3682864622678607,
+      "rtf_mean": 0.13257556265977197,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "16": {
+      "throughput_frames_s": 503.4867028463122,
+      "ttfa_p50_s": 1.2908506174571812,
+      "ttfa_p95_s": 2.5626851960550994,
+      "rtf_mean": 0.7839277616593806,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "32": {
+      "throughput_frames_s": 562.2434215047659,
+      "ttfa_p50_s": 2.584794282913208,
+      "ttfa_p95_s": 4.256634762324393,
+      "rtf_mean": 1.370429968875393,
+      "n_failed": 0,
+      "n_requests": 64
+    }
+  },
+  "mechanism_correction": "Initialization accepts FP16 but _ragged_body still gates ordinary nonresident fusion on FP32 input. Resident slots use fused code; fallback rows do not. Earlier GPU numerical tests called the fused kernel directly and did not cover this service dispatch.",
+  "nominal_fused_without_pool": {
+    "1": {
+      "throughput_frames_s": 178.93305943833786,
+      "ttfa_p50_s": 0.3553368877619505,
+      "ttfa_p95_s": 0.3926191593986004,
+      "rtf_mean": 0.14193875948468465,
+      "n_failed": 0
+    },
+    "16": {
+      "throughput_frames_s": 485.79583281009093,
+      "ttfa_p50_s": 1.386609590612352,
+      "ttfa_p95_s": 2.3111644179560242,
+      "rtf_mean": 0.8048504978511333,
+      "n_failed": 0
+    },
+    "32": {
+      "throughput_frames_s": 528.1696524060178,
+      "ttfa_p50_s": 2.7802301486954093,
+      "ttfa_p95_s": 4.777805440267548,
+      "rtf_mean": 1.4424365392733642,
+      "n_failed": 0
+    }
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
new file mode 100644
index 000000000..7e64dbfee
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
@@ -0,0 +1,157 @@
+{
+  "scope": "Reused64 tuning prompts; descriptive quality screening, not unused-holdout acceptance.",
+  "verdict": "INCONCLUSIVE",
+  "profiles": {
+    "screen-torch-mps": {
+      "1": {
+        "n": 64,
+        "sim": 50.0388879776001,
+        "utmos": 4.210992179811001,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 695
+        },
+        "wer_mean": 0.02427338286713287
+      },
+      "16": {
+        "n": 64,
+        "sim": 50.04513117671013,
+        "utmos": 4.222677733749151,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 9,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 697
+        },
+        "wer_mean": 0.024652170745920746
+      },
+      "32": {
+        "n": 64,
+        "sim": 51.00280150771141,
+        "utmos": 4.220405284315348,
+        "wer": 0.018387553041018388,
+        "wer_counts": {
+          "substitutions": 9,
+          "deletions": 1,
+          "insertions": 3,
+          "hits": 697
+        },
+        "wer_mean": 0.023331876456876458
+      }
+    },
+    "screen-fp16-mps": {
+      "1": {
+        "n": 64,
+        "sim": 50.12503969669342,
+        "utmos": 4.20760940387845,
+        "wer": 0.018387553041018388,
+        "wer_counts": {
+          "substitutions": 10,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 696
+        },
+        "wer_mean": 0.022971299533799533
+      },
+      "16": {
+        "n": 64,
+        "sim": 50.11029088497162,
+        "utmos": 4.227166544646025,
+        "wer": 0.016973125884016973,
+        "wer_counts": {
+          "substitutions": 7,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 699
+        },
+        "wer_mean": 0.02188774766899767
+      },
+      "32": {
+        "n": 64,
+        "sim": 51.173108011484146,
+        "utmos": 4.223404936492443,
+        "wer": 0.02263083451202263,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 695
+        },
+        "wer_mean": 0.02813774766899767
+      }
+    },
+    "screen-fp16-pool-mps": {
+      "1": {
+        "n": 64,
+        "sim": 50.141796231269836,
+        "utmos": 4.207637004554272,
+        "wer": 0.018387553041018388,
+        "wer_counts": {
+          "substitutions": 10,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 696
+        },
+        "wer_mean": 0.022710882867132867
+      },
+      "16": {
+        "n": 64,
+        "sim": 50.09496396780014,
+        "utmos": 4.203806925565004,
+        "wer": 0.018387553041018388,
+        "wer_counts": {
+          "substitutions": 8,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 698
+        },
+        "wer_mean": 0.02463395979020979
+      },
+      "32": {
+        "n": 64,
+        "sim": 50.29212284088135,
+        "utmos": 4.207753740251064,
+        "wer": 0.016973125884016973,
+        "wer_counts": {
+          "substitutions": 7,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 699
+        },
+        "wer_mean": 0.022029793123543126
+      }
+    },
+    "screen-capacity32-mps": {
+      "16": {
+        "n": 64,
+        "sim": 50.58166968822479,
+        "utmos": 4.228141937404871,
+        "wer": 0.015558698727015558,
+        "wer_counts": {
+          "substitutions": 7,
+          "deletions": 1,
+          "insertions": 3,
+          "hits": 699
+        },
+        "wer_mean": 0.020609338578088575
+      },
+      "32": {
+        "n": 64,
+        "sim": 50.76721328496933,
+        "utmos": 4.218518011271954,
+        "wer": 0.026874115983026876,
+        "wer_counts": {
+          "substitutions": 13,
+          "deletions": 1,
+          "insertions": 5,
+          "hits": 693
+        },
+        "wer_mean": 0.04141899766899767
+      }
+    }
+  }
+}

From 1b2787d340edb7668df3ac9de16757c2de047630 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 14:55:18 +0800
Subject: [PATCH 19/40] Pin runtime dispatch fix and complete peer baseline
 reproduction

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-dispatch-fix.json        |   5 +-
 .../results/peer-round2-baseline.json         | 234 ++++++++++++++++++
 2 files changed, 238 insertions(+), 1 deletion(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json
index 296756b20..3b290f23f 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-dispatch-fix.json
@@ -4,5 +4,8 @@
   "hypothesis": "Enable CUDA FP16 at the remaining _ragged_body runtime gate; test the actual service dispatch against the ragged numerical reference.",
   "validation": "New dispatch test must fail on parent then pass after fix; rerun DiT regressions before service screen.",
   "service": "Same64 tuning prompts,C1/C16/C32,discard plus one measured repeat; only runtime dispatch changed vs nominal fp16-fused screen.",
-  "quality": "Existing noninferiority margins unchanged; reserved256 remain unused."
+  "quality": "Existing noninferiority margins unchanged; reserved256 remain unused.",
+  "candidate_revision": "b6dacdf03756dbedeee8592577798670f5e22329",
+  "dispatch_negative_control": "New FP16 dispatch test fails on parent with the expected fused-path assertion.",
+  "precommit": "PASS"
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json
new file mode 100644
index 000000000..68c250c5b
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json
@@ -0,0 +1,234 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "scope": "Peer throughput target reproduction only; not speech-quality qualified; persistent server,320 prompts per repeat",
+  "source_revision": "a4f4778f312791c2d190b48e521141887ed160c8",
+  "profile": "track_s_fast_r11",
+  "exclude": "C1 run1 had two profiler snapshots; retained raw but excluded from aggregate",
+  "cells": {
+    "1": {
+      "measured_repeats": 2,
+      "mean": {
+        "throughput_frames_s": 399.1797938836057,
+        "ttfa_p50_s": 0.12561487639322877,
+        "ttfa_p95_s": 0.1310733950464055,
+        "rtf_mean": 0.06318489771332836
+      },
+      "failed_requests": 0,
+      "runs": [
+        {
+          "label": "run2",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 399.2518485918816,
+          "ttfa_p50_s": 0.12569232797250152,
+          "ttfa_p95_s": 0.13126140055246652,
+          "rtf_mean": 0.06316638823637923
+        },
+        {
+          "label": "run3",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 399.10773917532987,
+          "ttfa_p50_s": 0.12553742481395602,
+          "ttfa_p95_s": 0.13088538954034448,
+          "rtf_mean": 0.0632034071902775
+        }
+      ]
+    },
+    "2": {
+      "measured_repeats": 3,
+      "mean": {
+        "throughput_frames_s": 522.7815224118706,
+        "ttfa_p50_s": 0.19030275009572506,
+        "ttfa_p95_s": 0.2238410594097028,
+        "rtf_mean": 0.09719417906213433
+      },
+      "failed_requests": 0,
+      "runs": [
+        {
+          "label": "run1",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 524.2833407727487,
+          "ttfa_p50_s": 0.18930724542587996,
+          "ttfa_p95_s": 0.22458223472349345,
+          "rtf_mean": 0.09695828350119165
+        },
+        {
+          "label": "run2",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 524.4681610124577,
+          "ttfa_p50_s": 0.19021307351067662,
+          "ttfa_p95_s": 0.2246854744385928,
+          "rtf_mean": 0.09690288978284167
+        },
+        {
+          "label": "run3",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 519.5930654504054,
+          "ttfa_p50_s": 0.1913879313506186,
+          "ttfa_p95_s": 0.2222554690670222,
+          "rtf_mean": 0.09772136390236967
+        }
+      ]
+    },
+    "4": {
+      "measured_repeats": 3,
+      "mean": {
+        "throughput_frames_s": 756.8998217583901,
+        "ttfa_p50_s": 0.2664259920517604,
+        "ttfa_p95_s": 0.3047216606171181,
+        "rtf_mean": 0.13440840311578064
+      },
+      "failed_requests": 0,
+      "runs": [
+        {
+          "label": "run1",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 749.0288351609349,
+          "ttfa_p50_s": 0.26875559985637665,
+          "ttfa_p95_s": 0.302722130715847,
+          "rtf_mean": 0.13583986041899343
+        },
+        {
+          "label": "run2",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 761.3569619872535,
+          "ttfa_p50_s": 0.2647039033472538,
+          "ttfa_p95_s": 0.3066069653723389,
+          "rtf_mean": 0.13362078289833318
+        },
+        {
+          "label": "run3",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 760.313668126982,
+          "ttfa_p50_s": 0.2658184729516506,
+          "ttfa_p95_s": 0.30483588576316833,
+          "rtf_mean": 0.13376456603001535
+        }
+      ]
+    },
+    "8": {
+      "measured_repeats": 3,
+      "mean": {
+        "throughput_frames_s": 1126.452351587127,
+        "ttfa_p50_s": 0.3528090729378164,
+        "ttfa_p95_s": 0.4185279951586077,
+        "rtf_mean": 0.18023458369240614
+      },
+      "failed_requests": 0,
+      "runs": [
+        {
+          "label": "run1",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 1115.562478968023,
+          "ttfa_p50_s": 0.356242248788476,
+          "ttfa_p95_s": 0.41473029032349584,
+          "rtf_mean": 0.18213786003808577
+        },
+        {
+          "label": "run2",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 1135.3223175041437,
+          "ttfa_p50_s": 0.3512508487328887,
+          "ttfa_p95_s": 0.41143202586099503,
+          "rtf_mean": 0.17897701723012444
+        },
+        {
+          "label": "run3",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 1128.4722582892143,
+          "ttfa_p50_s": 0.35093412129208446,
+          "ttfa_p95_s": 0.42942166929133235,
+          "rtf_mean": 0.1795888738090082
+        }
+      ]
+    },
+    "16": {
+      "measured_repeats": 3,
+      "mean": {
+        "throughput_frames_s": 1698.4111949113371,
+        "ttfa_p50_s": 0.47094419024263817,
+        "ttfa_p95_s": 0.5544122065107029,
+        "rtf_mean": 0.2378654682241167
+      },
+      "failed_requests": 0,
+      "runs": [
+        {
+          "label": "run1",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 1708.5152452274522,
+          "ttfa_p50_s": 0.47399294190108776,
+          "ttfa_p95_s": 0.53595609087497,
+          "rtf_mean": 0.23592496180502312
+        },
+        {
+          "label": "run2",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 1699.6169441707327,
+          "ttfa_p50_s": 0.47324231220409274,
+          "ttfa_p95_s": 0.5986196104902778,
+          "rtf_mean": 0.23759453543058448
+        },
+        {
+          "label": "run3",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 1687.1013953358265,
+          "ttfa_p50_s": 0.46559731662273407,
+          "ttfa_p95_s": 0.528660918166861,
+          "rtf_mean": 0.24007690743674245
+        }
+      ]
+    },
+    "32": {
+      "measured_repeats": 3,
+      "mean": {
+        "throughput_frames_s": 2532.2272544324,
+        "ttfa_p50_s": 0.652823238633573,
+        "ttfa_p95_s": 0.7605699910782279,
+        "rtf_mean": 0.31420577419157525
+      },
+      "failed_requests": 0,
+      "runs": [
+        {
+          "label": "run1",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 2488.152112536773,
+          "ttfa_p50_s": 0.6573648029007018,
+          "ttfa_p95_s": 0.764265651535243,
+          "rtf_mean": 0.3156646026543056
+        },
+        {
+          "label": "run2",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 2558.585374352388,
+          "ttfa_p50_s": 0.6418805029243231,
+          "ttfa_p95_s": 0.7572030443698168,
+          "rtf_mean": 0.31311212467731775
+        },
+        {
+          "label": "run3",
+          "n_requests": 320,
+          "n_failed": 0,
+          "throughput_frames_s": 2549.9442764080386,
+          "ttfa_p50_s": 0.6592244100756943,
+          "ttfa_p95_s": 0.7602412773296238,
+          "rtf_mean": 0.31384059524310237
+        }
+      ]
+    }
+  }
+}

From e1e5b2324585bebb870bba065eaa9b43b3ae1a95 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 15:03:11 +0800
Subject: [PATCH 20/40] Freeze HiFT precision screen after numerical gate
 passes

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-hift-tf32.json           |  23 ++
 .../results/peer-round2-batch16-screen.json   |  43 +++
 .../results/peer-round2-hift-numerical.json   | 295 ++++++++++++++++++
 3 files changed, 361 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-hift-tf32.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-batch16-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-hift-numerical.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-hift-tf32.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-hift-tf32.json
new file mode 100644
index 000000000..d9955218a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-hift-tf32.json
@@ -0,0 +1,23 @@
+{
+  "frozen_at_utc": "2026-10-21T06:59:06.014919+00:00",
+  "parent_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "Scoped cuDNN/matmul TF32 in HiFT upsampling and source/residual blocks may reduce the remaining Code2Wav cost; source generation and decoder input/output convolutions retain their caller precision.",
+  "inspiration": {
+    "repository": "InferMatrixLab/minicpm-o-4.5-single-gpu-engine",
+    "revision": "a4f4778f312791c2d190b48e521141887ed160c8",
+    "path": "engine/models/token2wav.py"
+  },
+  "operator_gate": {
+    "waveform_relative_l2_max": 0.01,
+    "source": "exactly equal under matched seeded noise",
+    "scope": "First16 original tuning prompts, widths16/50/56 mel frames (48 real-speech windows), official HiFT weights; cache_source empty. Streaming service quality still required."
+  },
+  "service": "Only HiFT precision toggle changes against Torch+MPS default; FP32 flow and batch4 retained.64 reused tuning prompts,C1/C16/C32,discard+one repeat.",
+  "quality": "Prior authorized WER/SIM/UTMOS noninferiority margins remain unchanged; no holdout generation during screening.",
+  "candidate_revision": "460b64d7727585516be3b3c992cf0154b82f2cf9",
+  "pre_service_validation": {
+    "cpu_regressions": 35,
+    "precommit": "PASS",
+    "numerical_report": "../results/peer-round2-hift-numerical.json"
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-batch16-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-batch16-screen.json
new file mode 100644
index 000000000..4b27ce6df
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-batch16-screen.json
@@ -0,0 +1,43 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "scope": "64 reused tuning prompts, one measured repeat; throughput improvement is exploratory, not final qualification",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "cells": {
+    "1": {
+      "throughput_frames_s": 195.06704675552575,
+      "ttfa_p50_s": 0.29740623012185097,
+      "ttfa_p95_s": 0.3303545414470136,
+      "rtf_mean": 0.12942367030367663,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "16": {
+      "throughput_frames_s": 760.1710863988206,
+      "ttfa_p50_s": 1.1695650070905685,
+      "ttfa_p95_s": 1.7888787986710668,
+      "rtf_mean": 0.5135984359048855,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "32": {
+      "throughput_frames_s": 895.0384019394737,
+      "ttfa_p50_s": 1.8793323999270797,
+      "ttfa_p95_s": 3.3891150186769647,
+      "rtf_mean": 0.8585077294911585,
+      "n_failed": 0,
+      "n_requests": 64
+    }
+  },
+  "separate_diagnostic_mean": {
+    "thinker_ttft_ms": 113.00430819392204,
+    "thinker_gen_ms": 173.65941777825356,
+    "thinker_tpot_ms": 7.928317298807252,
+    "talker_first_output_ms": 813.5854601860046,
+    "talker_gen_ms": 1647.305954247713,
+    "code2wav_first_output_ms": 1954.1207887232304,
+    "code2wav_gen_ms": 3570.487316697836,
+    "audio_s": 4.386875,
+    "client_ttfa_s": 1.9877856113744201
+  },
+  "diagnostic_note": "Stage times overlap and include pipeline waiting; they are not isolated kernel durations. Diagnostic run is excluded from throughput aggregates."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-hift-numerical.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-hift-numerical.json
new file mode 100644
index 000000000..b61d59237
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-hift-numerical.json
@@ -0,0 +1,295 @@
+{
+  "scope": "48 real-speech windows, official HiFT weights, matched random source, empty source cache",
+  "rows": [
+    {
+      "prompt_index": 0,
+      "mel_frames": 16,
+      "relative_l2": 0.0008113376097753644,
+      "max_absolute": 0.0004437156021595001
+    },
+    {
+      "prompt_index": 0,
+      "mel_frames": 50,
+      "relative_l2": 0.0011442406103014946,
+      "max_absolute": 0.0025216341018676758
+    },
+    {
+      "prompt_index": 0,
+      "mel_frames": 56,
+      "relative_l2": 0.0010879153851419687,
+      "max_absolute": 0.0016235560178756714
+    },
+    {
+      "prompt_index": 1,
+      "mel_frames": 16,
+      "relative_l2": 0.0021792028564959764,
+      "max_absolute": 0.0016084164381027222
+    },
+    {
+      "prompt_index": 1,
+      "mel_frames": 50,
+      "relative_l2": 0.002298159757629037,
+      "max_absolute": 0.0024608969688415527
+    },
+    {
+      "prompt_index": 1,
+      "mel_frames": 56,
+      "relative_l2": 0.0024292415473610163,
+      "max_absolute": 0.002527087926864624
+    },
+    {
+      "prompt_index": 2,
+      "mel_frames": 16,
+      "relative_l2": 0.0010045409435406327,
+      "max_absolute": 0.0005430467426776886
+    },
+    {
+      "prompt_index": 2,
+      "mel_frames": 50,
+      "relative_l2": 0.001180937746539712,
+      "max_absolute": 0.0009092986583709717
+    },
+    {
+      "prompt_index": 2,
+      "mel_frames": 56,
+      "relative_l2": 0.001119120861403644,
+      "max_absolute": 0.0004909541457891464
+    },
+    {
+      "prompt_index": 3,
+      "mel_frames": 16,
+      "relative_l2": 0.0035826447419822216,
+      "max_absolute": 0.000896744430065155
+    },
+    {
+      "prompt_index": 3,
+      "mel_frames": 50,
+      "relative_l2": 0.0010414671851322055,
+      "max_absolute": 0.0009139478206634521
+    },
+    {
+      "prompt_index": 3,
+      "mel_frames": 56,
+      "relative_l2": 0.0010618228698149323,
+      "max_absolute": 0.0007871948182582855
+    },
+    {
+      "prompt_index": 4,
+      "mel_frames": 16,
+      "relative_l2": 0.001088021555915475,
+      "max_absolute": 0.00032518524676561356
+    },
+    {
+      "prompt_index": 4,
+      "mel_frames": 50,
+      "relative_l2": 0.0017403592355549335,
+      "max_absolute": 0.000593826174736023
+    },
+    {
+      "prompt_index": 4,
+      "mel_frames": 56,
+      "relative_l2": 0.001635711989365518,
+      "max_absolute": 0.000517725944519043
+    },
+    {
+      "prompt_index": 5,
+      "mel_frames": 16,
+      "relative_l2": 0.0011510433396324515,
+      "max_absolute": 0.001260802149772644
+    },
+    {
+      "prompt_index": 5,
+      "mel_frames": 50,
+      "relative_l2": 0.001204229425638914,
+      "max_absolute": 0.0023920591920614243
+    },
+    {
+      "prompt_index": 5,
+      "mel_frames": 56,
+      "relative_l2": 0.0009771991753950715,
+      "max_absolute": 0.0014205724000930786
+    },
+    {
+      "prompt_index": 6,
+      "mel_frames": 16,
+      "relative_l2": 0.0013771762605756521,
+      "max_absolute": 0.0024019908159971237
+    },
+    {
+      "prompt_index": 6,
+      "mel_frames": 50,
+      "relative_l2": 0.0009965780191123486,
+      "max_absolute": 0.0018949955701828003
+    },
+    {
+      "prompt_index": 6,
+      "mel_frames": 56,
+      "relative_l2": 0.0009843343868851662,
+      "max_absolute": 0.001656949520111084
+    },
+    {
+      "prompt_index": 7,
+      "mel_frames": 16,
+      "relative_l2": 0.000657650176435709,
+      "max_absolute": 0.00011003203690052032
+    },
+    {
+      "prompt_index": 7,
+      "mel_frames": 50,
+      "relative_l2": 0.0009541446925140917,
+      "max_absolute": 0.00022687017917633057
+    },
+    {
+      "prompt_index": 7,
+      "mel_frames": 56,
+      "relative_l2": 0.001217199838720262,
+      "max_absolute": 0.00029101036489009857
+    },
+    {
+      "prompt_index": 8,
+      "mel_frames": 16,
+      "relative_l2": 0.0007832854171283543,
+      "max_absolute": 0.0015461891889572144
+    },
+    {
+      "prompt_index": 8,
+      "mel_frames": 50,
+      "relative_l2": 0.0008881968096829951,
+      "max_absolute": 0.0012156665325164795
+    },
+    {
+      "prompt_index": 8,
+      "mel_frames": 56,
+      "relative_l2": 0.0008910720935091376,
+      "max_absolute": 0.0014916658401489258
+    },
+    {
+      "prompt_index": 9,
+      "mel_frames": 16,
+      "relative_l2": 0.0006050372612662613,
+      "max_absolute": 3.995746374130249e-05
+    },
+    {
+      "prompt_index": 9,
+      "mel_frames": 50,
+      "relative_l2": 0.001603313721716404,
+      "max_absolute": 0.000198455061763525
+    },
+    {
+      "prompt_index": 9,
+      "mel_frames": 56,
+      "relative_l2": 0.001551946857944131,
+      "max_absolute": 0.00018638372421264648
+    },
+    {
+      "prompt_index": 10,
+      "mel_frames": 16,
+      "relative_l2": 0.0012708842987194657,
+      "max_absolute": 0.0014857649803161621
+    },
+    {
+      "prompt_index": 10,
+      "mel_frames": 50,
+      "relative_l2": 0.0008183811441995203,
+      "max_absolute": 0.001084446907043457
+    },
+    {
+      "prompt_index": 10,
+      "mel_frames": 56,
+      "relative_l2": 0.0008653689874336123,
+      "max_absolute": 0.0010782256722450256
+    },
+    {
+      "prompt_index": 11,
+      "mel_frames": 16,
+      "relative_l2": 0.0005591415683738887,
+      "max_absolute": 0.0008673667907714844
+    },
+    {
+      "prompt_index": 11,
+      "mel_frames": 50,
+      "relative_l2": 0.0009310100576840341,
+      "max_absolute": 0.002278566360473633
+    },
+    {
+      "prompt_index": 11,
+      "mel_frames": 56,
+      "relative_l2": 0.0008310782141052186,
+      "max_absolute": 0.002262204885482788
+    },
+    {
+      "prompt_index": 12,
+      "mel_frames": 16,
+      "relative_l2": 0.001380826928652823,
+      "max_absolute": 0.00042304396629333496
+    },
+    {
+      "prompt_index": 12,
+      "mel_frames": 50,
+      "relative_l2": 0.001221650978550315,
+      "max_absolute": 0.0009464435279369354
+    },
+    {
+      "prompt_index": 12,
+      "mel_frames": 56,
+      "relative_l2": 0.0015076216077432036,
+      "max_absolute": 0.001266680657863617
+    },
+    {
+      "prompt_index": 13,
+      "mel_frames": 16,
+      "relative_l2": 0.000722019758541137,
+      "max_absolute": 9.979307651519775e-05
+    },
+    {
+      "prompt_index": 13,
+      "mel_frames": 50,
+      "relative_l2": 0.0008337386534549296,
+      "max_absolute": 0.00029075145721435547
+    },
+    {
+      "prompt_index": 13,
+      "mel_frames": 56,
+      "relative_l2": 0.0008197708521038294,
+      "max_absolute": 0.0003403499722480774
+    },
+    {
+      "prompt_index": 14,
+      "mel_frames": 16,
+      "relative_l2": 0.001000631833449006,
+      "max_absolute": 0.0008913278579711914
+    },
+    {
+      "prompt_index": 14,
+      "mel_frames": 50,
+      "relative_l2": 0.0008372064330615103,
+      "max_absolute": 0.0011583566665649414
+    },
+    {
+      "prompt_index": 14,
+      "mel_frames": 56,
+      "relative_l2": 0.000848564610350877,
+      "max_absolute": 0.0012233182787895203
+    },
+    {
+      "prompt_index": 15,
+      "mel_frames": 16,
+      "relative_l2": 0.0005785642424598336,
+      "max_absolute": 5.952268838882446e-05
+    },
+    {
+      "prompt_index": 15,
+      "mel_frames": 50,
+      "relative_l2": 0.0007628710009157658,
+      "max_absolute": 8.230097591876984e-05
+    },
+    {
+      "prompt_index": 15,
+      "mel_frames": 56,
+      "relative_l2": 0.0007612149347551167,
+      "max_absolute": 9.068637154996395e-05
+    }
+  ],
+  "max_relative_l2": 0.0035826447419822216,
+  "verdict": "PASS"
+}

From d0ce216e4efc577ac45ef1713a8e10b377b97e92 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 15:05:34 +0800
Subject: [PATCH 21/40] Record corrected FP16 dispatch result and freeze
 residency trial

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-resident16.json          | 13 ++++++++
 .../results/peer-round2-dispatch-screen.json  | 32 +++++++++++++++++++
 2 files changed, 45 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-resident16.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-dispatch-screen.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-resident16.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-resident16.json
new file mode 100644
index 000000000..3978b8460
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-resident16.json
@@ -0,0 +1,13 @@
+{
+  "frozen_at_utc": "2026-10-21T07:03:43.700560+00:00",
+  "source_revision": "b6dacdf03756dbedeee8592577798670f5e22329",
+  "hypothesis": "With actual FP16 fusion enabled, a16-row microbatch gives18 resident slots, enough for stage capacity16; test whether fewer replays and cache copies outperform the6-slot trial.",
+  "changes_vs_dispatch_only": {
+    "micro_batch_size": 16,
+    "cfm_slot_pool": true,
+    "cfm_row_offset_merge": true
+  },
+  "limitations": "This is a combined batching/residency screen; do not attribute gain to any one toggle without an ablation.",
+  "protocol": "64 reused tuning prompts,C1/C16/C32,discard+one repeat; same sampling, Torch speaker, MPS, FP16 flow; HiFT remains IEEE FP32.",
+  "validation": "26 attention tests and6 DiT tests passed, including actual FP16 dispatch; speech quality screening remains required."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-dispatch-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-dispatch-screen.json
new file mode 100644
index 000000000..f5be32816
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-dispatch-screen.json
@@ -0,0 +1,32 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "scope": "64 reused tuning prompts, one measured repeat, no final performance or quality qualification",
+  "source_revision": "b6dacdf03756dbedeee8592577798670f5e22329",
+  "cells": {
+    "1": {
+      "throughput_frames_s": 192.78916450611223,
+      "ttfa_p50_s": 0.29299376625567675,
+      "ttfa_p95_s": 0.32444422915577886,
+      "rtf_mean": 0.1311724539505048,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "16": {
+      "throughput_frames_s": 825.9532673478732,
+      "ttfa_p50_s": 1.216235188767314,
+      "ttfa_p95_s": 1.8333380463533104,
+      "rtf_mean": 0.4847945349624937,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "32": {
+      "throughput_frames_s": 857.742972869709,
+      "ttfa_p50_s": 1.8151386007666588,
+      "ttfa_p95_s": 3.2356737752910703,
+      "rtf_mean": 0.8832207689635144,
+      "n_failed": 0,
+      "n_requests": 64
+    }
+  },
+  "validation": "New dispatch assertion fails on parent; fixed implementation passes6 DiT tests and all changed-file precommit checks."
+}

From 22e624481b70c6b4ba50051d257129b90f84e7f0 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 15:08:44 +0800
Subject: [PATCH 22/40] Preserve dispatch and batch-width quality screening

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../results/peer-round2-screen-quality.json   | 82 +++++++++++++++++++
 1 file changed, 82 insertions(+)

diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
index 7e64dbfee..89795b591 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
@@ -152,6 +152,88 @@
         },
         "wer_mean": 0.04141899766899767
       }
+    },
+    "screen-fp16-dispatch-mps": {
+      "1": {
+        "n": 64,
+        "sim": 49.97908663749695,
+        "utmos": 4.197729919105768,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 695
+        },
+        "wer_mean": 0.02427338286713287
+      },
+      "16": {
+        "n": 64,
+        "sim": 49.56127646565437,
+        "utmos": 4.205279611051083,
+        "wer": 0.02263083451202263,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 695
+        },
+        "wer_mean": 0.02896088286713287
+      },
+      "32": {
+        "n": 64,
+        "sim": 50.271223694086075,
+        "utmos": 4.208677411079407,
+        "wer": 0.016973125884016973,
+        "wer_counts": {
+          "substitutions": 10,
+          "deletions": 1,
+          "insertions": 1,
+          "hits": 696
+        },
+        "wer_mean": 0.021248543123543125
+      }
+    },
+    "screen-fp32-batch16-mps": {
+      "1": {
+        "n": 64,
+        "sim": 50.03927397727966,
+        "utmos": 4.211021088063717,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 695
+        },
+        "wer_mean": 0.02427338286713287
+      },
+      "16": {
+        "n": 64,
+        "sim": 50.54042565822601,
+        "utmos": 4.200230292975903,
+        "wer": 0.016973125884016973,
+        "wer_counts": {
+          "substitutions": 9,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 697
+        },
+        "wer_mean": 0.02150895979020979
+      },
+      "32": {
+        "n": 64,
+        "sim": 51.42967754602432,
+        "utmos": 4.217132780700922,
+        "wer": 0.014144271570014143,
+        "wer_counts": {
+          "substitutions": 7,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 699
+        },
+        "wer_mean": 0.017342293123543125
+      }
     }
   }
 }

From 75335127f1405197f298b7061074d4ca1c22f9a8 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 15:22:01 +0800
Subject: [PATCH 23/40] Preserve HiFT, residency and prompt-setup screening
 evidence

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-batch-setup.json         | 16 +++++
 ...eer-round2-screen-fp16-resident16-mps.json | 31 +++++++++
 .../peer-round2-screen-hift-tf32-mps.json     | 69 +++++++++++++++++++
 .../results/peer-round2-setup-numerical.json  | 47 +++++++++++++
 4 files changed, 163 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch-setup.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-fp16-resident16-mps.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-hift-tf32-mps.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-numerical.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch-setup.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch-setup.json
new file mode 100644
index 000000000..e76a80e00
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-batch-setup.json
@@ -0,0 +1,16 @@
+{
+  "frozen_at_utc": "2026-10-21T07:14:41.615568+00:00",
+  "parent_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "Current vLLM prepares each distinct reference voice with a separate prompt CFM Euler solve. Batch same-length prompt solves while keeping each flow encoder call unchanged; avoid variable-length padding in first implementation.",
+  "inspiration": {
+    "repository": "InferMatrixLab/minicpm-o-4.5-single-gpu-engine",
+    "revision": "a4f4778f312791c2d190b48e521141887ed160c8",
+    "path": "engine/runtime/token2wav_batch.py:setup_many"
+  },
+  "scope": "Opt-in cfm_batch_prompt_setup; default off. Preserve per-prompt features, cached-state ownership, CFG row ordering, and existing non-CUDA behavior.",
+  "operator_gate": "Same reference encoder outputs; prompt estimator cache relative L2<=0.01 against independent solves; paired continuation audio relative L2<=0.01 on reused tuning prompts; exact cache/row ownership checks. Failure excludes promotion without changing gates.",
+  "service": "Only batch prompt setup changes vs Torch+MPS baseline, default FP32 Flow and HiFT, microbatch4;64 reused tuning prompts at C1/C16/C32.",
+  "quality": "Existing speech noninferiority gates unchanged; reserved holdout untouched.",
+  "candidate_revision": "d255857c1d1441ba77362da6d4cb628fa5dc47a8",
+  "numerical_protocol_detail": "Four first eligible references >=6 seconds from original first64 tuning IDs, truncated to6 seconds; matching seeded HiFT noise for each baseline/candidate continuation; first28 reference speech tokens as continuation input. Initial unseeded probe was stopped before model load completed, with no numerical results."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-fp16-resident16-mps.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-fp16-resident16-mps.json
new file mode 100644
index 000000000..72a878b18
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-fp16-resident16-mps.json
@@ -0,0 +1,31 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "scope": "64 reused tuning prompts, one measured repeat; no final qualification",
+  "cells": {
+    "1": {
+      "throughput_frames_s": 195.48027283991107,
+      "ttfa_p50_s": 0.2955296402797103,
+      "ttfa_p95_s": 0.3218923930544406,
+      "rtf_mean": 0.12941430037961194,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "16": {
+      "throughput_frames_s": 848.2127450045919,
+      "ttfa_p50_s": 1.326912050601095,
+      "ttfa_p95_s": 2.136800453346223,
+      "rtf_mean": 0.47656773709281225,
+      "n_failed": 0,
+      "n_requests": 64
+    },
+    "32": {
+      "throughput_frames_s": 878.0731802061676,
+      "ttfa_p50_s": 1.898135322611779,
+      "ttfa_p95_s": 4.139536390127614,
+      "rtf_mean": 0.8721677482871804,
+      "n_failed": 0,
+      "n_requests": 64
+    }
+  },
+  "decision": "C32 increases modestly versus dispatch-only but remains far below the peer target on its separate320-prompt workload. Do not claim a statistically confirmed gain or a matched peer win."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-hift-tf32-mps.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-hift-tf32-mps.json
new file mode 100644
index 000000000..16fa7d3c2
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-hift-tf32-mps.json
@@ -0,0 +1,69 @@
+{
+  "verdict": "FAIL",
+  "scope": "64 reused tuning prompts, one measured repeat; fails throughput promotion against FP32 baseline; not final speech-quality acceptance",
+  "cells": {
+    "1": {
+      "throughput_frames_s": 183.18654208534716,
+      "ttfa_p50_s": 0.3086627828888595,
+      "ttfa_p95_s": 0.33932453761808573,
+      "rtf_mean": 0.13766234621063053,
+      "n_failed": 0,
+      "n_requests": 64,
+      "quality": {
+        "n": 64,
+        "sim": 50.039308071136475,
+        "utmos": 4.21100053191185,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 695
+        },
+        "wer_mean": 0.02427338286713287
+      }
+    },
+    "16": {
+      "throughput_frames_s": 737.2577751213121,
+      "ttfa_p50_s": 1.1451171077787876,
+      "ttfa_p95_s": 1.9528556275181472,
+      "rtf_mean": 0.530965402599596,
+      "n_failed": 0,
+      "n_requests": 64,
+      "quality": {
+        "n": 64,
+        "sim": 49.897953778505325,
+        "utmos": 4.1876552030444145,
+        "wer": 0.028288543140028287,
+        "wer_counts": {
+          "substitutions": 13,
+          "deletions": 1,
+          "insertions": 6,
+          "hits": 693
+        },
+        "wer_mean": 0.04366258741258741
+      }
+    },
+    "32": {
+      "throughput_frames_s": 845.3368890156694,
+      "ttfa_p50_s": 1.8919171816669405,
+      "ttfa_p95_s": 3.509336013905704,
+      "rtf_mean": 0.8919556375545152,
+      "n_failed": 0,
+      "n_requests": 64,
+      "quality": {
+        "n": 64,
+        "sim": 50.72682964801788,
+        "utmos": 4.213015131652355,
+        "wer": 0.018387553041018388,
+        "wer_counts": {
+          "substitutions": 8,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 698
+        },
+        "wer_mean": 0.023189831002331
+      }
+    }
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-numerical.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-numerical.json
new file mode 100644
index 000000000..9535a14f4
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-numerical.json
@@ -0,0 +1,47 @@
+{
+  "scope": "Four distinct six-second references from the first64 reused tuning IDs; individual encoders, shared FP32 prompt solve, paired continuation on reference speech tokens",
+  "rows": [
+    {
+      "prompt_index": 0,
+      "errors": {
+        "conformer_cnn_cache": 0.0,
+        "conformer_att_cache": 0.0,
+        "estimator_cnn_cache": 0.0003847459447570145,
+        "estimator_att_cache": 0.0004364989581517875,
+        "continuation_audio": 0.6314619183540344
+      }
+    },
+    {
+      "prompt_index": 1,
+      "errors": {
+        "conformer_cnn_cache": 0.0,
+        "conformer_att_cache": 0.0,
+        "estimator_cnn_cache": 0.0005224508349783719,
+        "estimator_att_cache": 0.0004373687843326479,
+        "continuation_audio": 0.5722200870513916
+      }
+    },
+    {
+      "prompt_index": 2,
+      "errors": {
+        "conformer_cnn_cache": 0.0,
+        "conformer_att_cache": 0.0,
+        "estimator_cnn_cache": 0.00037057462031953037,
+        "estimator_att_cache": 0.00042073868098668754,
+        "continuation_audio": 0.22678354382514954
+      }
+    },
+    {
+      "prompt_index": 3,
+      "errors": {
+        "conformer_cnn_cache": 0.0,
+        "conformer_att_cache": 0.0,
+        "estimator_cnn_cache": 0.00044068691204302013,
+        "estimator_att_cache": 0.0004504274984356016,
+        "continuation_audio": 0.0161434393376112
+      }
+    }
+  ],
+  "verdict": "FAIL",
+  "decision": "Do not promote or run a service performance qualification under this hypothesis: paired continuation waveform relative L2 exceeds frozen0.01 gate even though prompt-cache errors are small."
+}

From 98d13e4d654b47b471bf8f693370da3ada6167e6 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 15:30:16 +0800
Subject: [PATCH 24/40] Freeze graph-coverage screens from independent stage
 profiler

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../plan/peer-round2-graph-coverage.json      |  17 +
 .../plan/peer-round2-stage2-profile.json      |  15 +
 .../results/peer-round2-stage2-profile.json   | 442 ++++++++++++++++++
 3 files changed, 474 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-graph-coverage.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-profile.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-stage2-profile.json

diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-graph-coverage.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-graph-coverage.json
new file mode 100644
index 000000000..077717f8d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-graph-coverage.json
@@ -0,0 +1,17 @@
+{
+  "frozen_at_utc": "2026-10-21T07:27:38.275671+00:00",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "evidence": "FP32 batch16 startup captures30 Whole-Euler graphs against cap32. _entry refuses unseen keys once full. Service logs show eager HiFT tails at batch2 and variable widths. Diagnostic trace has57535 ordinary kernel launches plus13662 extended launches, with294847 device kernels overall; profiler overhead excludes timing from service claims.",
+  "screens": {
+    "cfm128-batch16": {
+      "change": "cfm_max_graphs32->128",
+      "hypothesis": "Avoid eager fallbacks after precapture consumes nearly all graph slots"
+    },
+    "hift-exact-batch16": {
+      "change": "hift_graph_exact_batch_sizes[1]->[1,2,4]",
+      "hypothesis": "Capture common multirow tail shapes without changing their padding or precision"
+    }
+  },
+  "unchanged": "FP32 flow, default FP32 HiFT, Torch speaker,MPS,microbatch16, capacities16, canonical sampling",
+  "protocol": "Each fresh service:64 reused tuning prompts,C1/C16/C32,discard+one repeat; score saved outputs; no reserved holdout use."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-profile.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-profile.json
new file mode 100644
index 000000000..74216110a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-profile.json
@@ -0,0 +1,15 @@
+{
+  "recorded_at_utc": "2026-10-21T07:23:51.518941+00:00",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "profile": "Torch speaker, MPS, FP32 Flow, IEEE FP32 HiFT, micro_batch_size16",
+  "protocol": "Dedicated fresh service with stage2 torch profiler; warm64 reused tuning prompts atC32, then profile first32 reused tuning prompts atC32. No holdout data.",
+  "profiler": {
+    "activities": [
+      "CPU",
+      "CUDA"
+    ],
+    "with_stack": false,
+    "record_shapes": false
+  },
+  "exclusion": "All requests in this diagnostic service are excluded from performance aggregates. Only sanitized operator timing summaries may be published; raw traces stay local."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-stage2-profile.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-stage2-profile.json
new file mode 100644
index 000000000..1731da683
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-stage2-profile.json
@@ -0,0 +1,442 @@
+{
+  "scope": "Diagnostic only; instrumentation overhead means these durations are not service performance numbers",
+  "categories": {
+    "": 62,
+    "cpu_op": 381781,
+    "user_annotation": 744,
+    "overhead": 1961,
+    "cuda_runtime": 115922,
+    "ac2g": 421247,
+    "gpu_memcpy": 2582,
+    "kernel": 294847,
+    "cuda_driver": 3113,
+    "gpu_memset": 4783,
+    "gpu_user_annotation": 18,
+    "Trace": 1
+  },
+  "operators": {
+    "kernel": [
+      {
+        "name": "_attention",
+        "sum_ms": 244.13863599999974,
+        "count": 8800
+      },
+      {
+        "name": "void at::native::elementwise_kernel<128, 2, at::native::gpu_kernel_impl_nocast<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}>(at::TensorIteratorBase&, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1} const&)::{lambda(int)#1}>(int, at::native::gpu_kernel_impl_nocast<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}>(at::TensorIteratorBase&, at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&)::{lambda()#3}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1} const&)::{lambda(int)#1})",
+        "sum_ms": 242.23646099999624,
+        "count": 46527
+      },
+      {
+        "name": "sm90_xmma_gemm_f32f32_tf32f32_f32_tn_n_tilesize64x64x32_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
+        "sum_ms": 204.25373199999885,
+        "count": 21531
+      },
+      {
+        "name": "sm90_xmma_gemm_f32f32_tf32f32_f32_tn_n_tilesize64x128x32_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
+        "sum_ms": 180.93917500000046,
+        "count": 15940
+      },
+      {
+        "name": "sm90_xmma_gemm_f32f32_tf32f32_f32_tn_n_tilesize128x128x32_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
+        "sum_ms": 154.05077400000016,
+        "count": 10890
+      },
+      {
+        "name": "_residual_layer_norm_kernel",
+        "sum_ms": 114.76959600000151,
+        "count": 35750
+      },
+      {
+        "name": "void at::native::_scatter_gather_elementwise_kernel<128, 8, at::native::_cuda_scatter_gather_internal_kernel<false, at::native::OpaqueType<4>, long>::operator()<at::native::TensorAssign>(at::TensorIterator&, long, long, long, at::native::TensorAssign const&)::{lambda(int)#1}>(int, at::native::_cuda_scatter_gather_internal_kernel<false, at::native::OpaqueType<4>, long>::operator()<at::native::TensorAssign>(at::TensorIterator&, long, long, long, at::native::TensorAssign const&)::{lambda(int)#1})",
+        "sum_ms": 107.19988800000006,
+        "count": 17600
+      },
+      {
+        "name": "sm90_xmma_gemm_f32f32_tf32f32_f32_tn_n_tilesize128x64x32_warpgroupsize1x1x1_execute_segment_k_off_kernel__5x_cublas",
+        "sum_ms": 95.2863610000002,
+        "count": 7992
+      },
+      {
+        "name": "void at::native::elementwise_kernel<128, 2, at::native::gpu_kernel_impl_nocast<at::native::CUDAFunctor_add<float> >(at::TensorIteratorBase&, at::native::CUDAFunctor_add<float> const&)::{lambda(int)#1}>(int, at::native::gpu_kernel_impl_nocast<at::native::CUDAFunctor_add<float> >(at::TensorIteratorBase&, at::native::CUDAFunctor_add<float> const&)::{lambda(int)#1})",
+        "sum_ms": 46.97159800000025,
+        "count": 17044
+      },
+      {
+        "name": "void cutlass::Kernel2<cutlass_80_tensorop_s1688gemm_64x64_32x6_tn_align4>(cutlass_80_tensorop_s1688gemm_64x64_32x6_tn_align4::Params)",
+        "sum_ms": 41.10041699999984,
+        "count": 6043
+      },
+      {
+        "name": "sm80_xmma_fprop_implicit_gemm_tf32f32_tf32f32_f32_nhwckrsc_nchw_tilesize64x32x64_stage5_warpsize2x2x1_g1_tensor16x8x8_alignc4_execute_kernel__5x_cudnn",
+        "sum_ms": 38.39741099999995,
+        "count": 4115
+      },
+      {
+        "name": "void cublasLt::epilogue::impl::globalKernel<8, 32, float, float, float, true, false, 4>(int, int, long, float*, cublasLtEpilogue_t, int, float*, long, void*, long, long, long, float*, long, int*)",
+        "sum_ms": 35.20801800000028,
+        "count": 7840
+      },
+      {
+        "name": "void cudnn::engines_precompiled::nchwToNhwcKernel<float, float, float, false, true, (cudnnKernelDataType_t)2>(cudnn::engines_precompiled::nchw2nhwc_params_t<float>, float const*, float*)",
+        "sum_ms": 33.02018899999988,
+        "count": 9791
+      },
+      {
+        "name": "sm80_xmma_gemm_f32f32_tf32f32_f32_nn_n_tilesize32x32x64_stage3_warpsize2x2x1_tensor16x8x8_aligna4_alignc4_execute_kernel__5x_cublas",
+        "sum_ms": 31.83016199999996,
+        "count": 5366
+      },
+      {
+        "name": "_qkv_head_layer_norm_kernel",
+        "sum_ms": 30.969115999999993,
+        "count": 8800
+      },
+      {
+        "name": "_kernel",
+        "sum_ms": 21.258748,
+        "count": 3528
+      },
+      {
+        "name": "void at::native::(anonymous namespace)::avg_pool2d_out_cuda_frame<float, float>(int, float const*, long, long, long, long, int, int, int, int, int, int, int, float*, int, bool, bool)",
+        "sum_ms": 17.561681999999955,
+        "count": 1664
+      },
+      {
+        "name": "void at::native::(anonymous namespace)::weight_norm_fwd_first_dim_kernel<float, float>(float*, float*, float const*, float const*, int)",
+        "sum_ms": 13.72631499999999,
+        "count": 4018
+      },
+      {
+        "name": "void at::native::vectorized_elementwise_kernel<4, at::native::CUDAFunctor_add<float>, std::array<char*, 3ul> >(int, at::native::CUDAFunctor_add<float>, std::array<char*, 3ul>)",
+        "sum_ms": 13.123063000000036,
+        "count": 5629
+      },
+      {
+        "name": "void cudnn::engines_precompiled::nchwToNhwcKernel<float, float, float, false, true, (cudnnKernelDataType_t)0>(cudnn::engines_precompiled::nchw2nhwc_params_t<float>, float const*, float*)",
+        "sum_ms": 10.723984000000014,
+        "count": 2908
+      },
+      {
+        "name": "sm90_xmma_fprop_implicit_gemm_f32f32_tf32f32_f32_nhwckrsc_nhwc_tilesize128x64x32_warpgroupsize1x1x1_g1_execute_segment_k_off_kernel__5x_cudnn",
+        "sum_ms": 10.186836999999993,
+        "count": 475
+      },
+      {
+        "name": "void at::native::(anonymous namespace)::vectorized_layer_norm_kernel<float, float, false>(int, float, float const*, float const*, float const*, float*, float*, float*)",
+        "sum_ms": 9.991383000000049,
+        "count": 2822
+      },
+      {
+        "name": "void at::native::(anonymous namespace)::CatArrayBatchedCopy<at::native::(anonymous namespace)::OpaqueType<4u>, unsigned int, 4, 64, 64>(at::native::(anonymous namespace)::OpaqueType<4u>*, at::native::(anonymous namespace)::CatArrInputTensorMetadata<at::native::(anonymous namespace)::OpaqueType<4u>, unsigned int, 64, 64>, at::native::(anonymous namespace)::TensorSizeStride<unsigned int, 4u>, int, unsigned int)",
+        "sum_ms": 9.77546600000003,
+        "count": 2184
+      },
+      {
+        "name": "sm80_xmma_fprop_implicit_gemm_tf32f32_tf32f32_f32_nhwckrsc_nchw_tilesize128x128x16_stage4_warpsize2x2x1_g1_tensor16x8x8_alignc4_execute_kernel__5x_cudnn",
+        "sum_ms": 9.718611,
+        "count": 144
+      },
+      {
+        "name": "void at::native::vectorized_elementwise_kernel<4, at::native::(anonymous namespace)::launch_clamp_scalar(at::TensorIteratorBase&, c10::Scalar, c10::Scalar, at::native::detail::ClampLimits)::{lambda()#1}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, std::array<char*, 2ul> >(int, at::native::(anonymous namespace)::launch_clamp_scalar(at::TensorIteratorBase&, c10::Scalar, c10::Scalar, at::native::detail::ClampLimits)::{lambda()#1}::operator()() const::{lambda()#7}::operator()() const::{lambda(float)#1}, std::array<char*, 2ul>)",
+        "sum_ms": 8.959122000000082,
+        "count": 5793
+      },
+      {
+        "name": "void cudnn::engines_precompiled::nhwcToNchwKernel<float, float, float, true, false, (cudnnKernelDataType_t)0>(cudnn::engines_precompiled::nhwc2nchw_params_t<float>, float const*, float*)",
+        "sum_ms": 8.841637999999994,
+        "count": 1817
+      },
+      {
+        "name": "sm90_xmma_fprop_implicit_gemm_f32f32_tf32f32_f32_nhwckrsc_nhwc_tilesize64x128x32_warpgroupsize1x1x1_g1_execute_segment_k_off_kernel__5x_cudnn",
+        "sum_ms": 7.053679999999996,
+        "count": 300
+      },
+      {
+        "name": "void cutlass__5x_cudnn::Kernel<cutlass_tensorop_s1688fprop_optimized_tf32_256x64_16x4_nhwc_align4>(cutlass_tensorop_s1688fprop_optimized_tf32_256x64_16x4_nhwc_align4::Params)",
+        "sum_ms": 6.418611000000001,
+        "count": 285
+      },
+      {
+        "name": "void cublasLt::splitKreduce_kernel<32, 16, int, float, float, float, float, false, float, float, float, true, true, false, false>(cublasLt::cublasSplitKParams<float>, float const*, float const*, float*, float*, float const*, float const*, float const*, float const*, float*, void*, long, float*, int*, float*, float*, float const*, float const*, float const*, float const*, float const*)",
+        "sum_ms": 5.344822999999943,
+        "count": 2207
+      },
+      {
+        "name": "void at::native::reduce_kernel<512, 1, at::native::ReduceOp<float, at::native::MeanOps<float, float, float, float>, unsigned int, float, 4, 4> >(at::native::ReduceOp<float, at::native::MeanOps<float, float, float, float>, unsigned int, float, 4, 4>)",
+        "sum_ms": 5.329350000000004,
+        "count": 1696
+      }
+    ],
+    "cpu_op": [
+      {
+        "name": "aten::convolution",
+        "sum_ms": 536.6346880000017,
+        "count": 7762
+      },
+      {
+        "name": "aten::_convolution",
+        "sum_ms": 527.3416669999998,
+        "count": 7762
+      },
+      {
+        "name": "aten::conv1d",
+        "sum_ms": 519.3273900000015,
+        "count": 7375
+      },
+      {
+        "name": "aten::cudnn_convolution",
+        "sum_ms": 307.68386100000015,
+        "count": 7535
+      },
+      {
+        "name": "aten::copy_",
+        "sum_ms": 285.2470229999987,
+        "count": 9652
+      },
+      {
+        "name": "aten::linear",
+        "sum_ms": 218.4615940000006,
+        "count": 5976
+      },
+      {
+        "name": "aten::matmul",
+        "sum_ms": 170.73924499999987,
+        "count": 3162
+      },
+      {
+        "name": "aten::addmm",
+        "sum_ms": 149.95982500000017,
+        "count": 5152
+      },
+      {
+        "name": "aten::cat",
+        "sum_ms": 139.72446699999978,
+        "count": 5449
+      },
+      {
+        "name": "aten::stft",
+        "sum_ms": 138.20667800000004,
+        "count": 130
+      },
+      {
+        "name": "aten::to",
+        "sum_ms": 134.2705790000002,
+        "count": 7144
+      },
+      {
+        "name": "aten::_to_copy",
+        "sum_ms": 130.53042200000004,
+        "count": 1598
+      },
+      {
+        "name": "aten::abs",
+        "sum_ms": 98.17480799999994,
+        "count": 196
+      },
+      {
+        "name": "aten::bmm",
+        "sum_ms": 96.76906500000004,
+        "count": 2306
+      },
+      {
+        "name": "aten::clone",
+        "sum_ms": 92.85149500000026,
+        "count": 5720
+      },
+      {
+        "name": "aten::fill_",
+        "sum_ms": 91.89172200000003,
+        "count": 2716
+      },
+      {
+        "name": "aten::add",
+        "sum_ms": 90.10374600000007,
+        "count": 6708
+      },
+      {
+        "name": "aten::zeros",
+        "sum_ms": 84.76750099999992,
+        "count": 1487
+      },
+      {
+        "name": "aten::sum",
+        "sum_ms": 79.99230499999996,
+        "count": 160
+      },
+      {
+        "name": "aten::zero_",
+        "sum_ms": 79.55899100000002,
+        "count": 1910
+      },
+      {
+        "name": "aten::thnn_conv2d",
+        "sum_ms": 70.451383,
+        "count": 32
+      },
+      {
+        "name": "aten::_slow_conv2d_forward",
+        "sum_ms": 70.310911,
+        "count": 32
+      },
+      {
+        "name": "aten::mul",
+        "sum_ms": 70.06700899999981,
+        "count": 4924
+      },
+      {
+        "name": "aten::_fft_r2c",
+        "sum_ms": 66.81287800000001,
+        "count": 97
+      },
+      {
+        "name": "aten::empty",
+        "sum_ms": 66.71136300000006,
+        "count": 21098
+      },
+      {
+        "name": "aten::batch_norm",
+        "sum_ms": 62.38747899999993,
+        "count": 1792
+      },
+      {
+        "name": "aten::_batch_norm_impl_index",
+        "sum_ms": 59.809836000000004,
+        "count": 1792
+      },
+      {
+        "name": "aten::reshape",
+        "sum_ms": 59.511856,
+        "count": 13854
+      },
+      {
+        "name": "aten::layer_norm",
+        "sum_ms": 57.99266099999991,
+        "count": 1833
+      },
+      {
+        "name": "aten::add_",
+        "sum_ms": 56.35728300000004,
+        "count": 6234
+      }
+    ],
+    "cuda_runtime": [
+      {
+        "name": "cudaGraphLaunch",
+        "sum_ms": 572.497359,
+        "count": 146
+      },
+      {
+        "name": "cudaLaunchKernel",
+        "sum_ms": 446.4360449999973,
+        "count": 57535
+      },
+      {
+        "name": "cudaStreamSynchronize",
+        "sum_ms": 108.40922599999999,
+        "count": 288
+      },
+      {
+        "name": "cudaLaunchKernelExC",
+        "sum_ms": 74.27129099999988,
+        "count": 13662
+      },
+      {
+        "name": "cudaMemcpyAsync",
+        "sum_ms": 35.70676899999998,
+        "count": 2580
+      },
+      {
+        "name": "cudaFuncGetAttributes",
+        "sum_ms": 29.38321400000002,
+        "count": 9567
+      },
+      {
+        "name": "cudaEventSynchronize",
+        "sum_ms": 21.039809999999996,
+        "count": 761
+      },
+      {
+        "name": "cudaEventQuery",
+        "sum_ms": 5.66229500000002,
+        "count": 9071
+      },
+      {
+        "name": "cudaMemsetAsync",
+        "sum_ms": 4.188126000000002,
+        "count": 802
+      },
+      {
+        "name": "cudaEventRecordWithFlags",
+        "sum_ms": 3.078887,
+        "count": 981
+      },
+      {
+        "name": "cudaDeviceGetAttribute",
+        "sum_ms": 1.4040729999999992,
+        "count": 2999
+      },
+      {
+        "name": "cudaStreamIsCapturing",
+        "sum_ms": 1.222360999999999,
+        "count": 1720
+      },
+      {
+        "name": "cudaPeekAtLastError",
+        "sum_ms": 0.9207620000000094,
+        "count": 8846
+      },
+      {
+        "name": "cudaGetErrorString",
+        "sum_ms": 0.8281920000000031,
+        "count": 6584
+      },
+      {
+        "name": "cudaMalloc",
+        "sum_ms": 0.607542,
+        "count": 1
+      },
+      {
+        "name": "cudaFuncSetAttribute",
+        "sum_ms": 0.382831,
+        "count": 192
+      },
+      {
+        "name": "cudaHostAlloc",
+        "sum_ms": 0.234002,
+        "count": 3
+      },
+      {
+        "name": "cudaDeviceSynchronize",
+        "sum_ms": 0.216564,
+        "count": 1
+      },
+      {
+        "name": "cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags",
+        "sum_ms": 0.17831399999999997,
+        "count": 10
+      },
+      {
+        "name": "cudaPointerGetAttributes",
+        "sum_ms": 0.11837800000000001,
+        "count": 102
+      },
+      {
+        "name": "cudaStreamWaitEvent",
+        "sum_ms": 0.054216999999999994,
+        "count": 17
+      },
+      {
+        "name": "cudaEventRecord",
+        "sum_ms": 0.04503800000000001,
+        "count": 48
+      },
+      {
+        "name": "cudaStreamGetCaptureInfo",
+        "sum_ms": 0.0035410000000000003,
+        "count": 6
+      }
+    ]
+  },
+  "kernel_sum_s": 1.879141402,
+  "kernel_span_s": 4.661852760986328
+}

From dcf5478a817435dbe8a51fda6ed4a722ce05a2d1 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 15:31:40 +0800
Subject: [PATCH 25/40] Archive reproducible exploratory implementation patches

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../peer-round2-batch-prompt-setup.patch      | 171 ++++++++++++++
 .../patch/peer-round2-fp16-dispatch.patch     | 208 ++++++++++++++++++
 .../patch/peer-round2-hift-tf32.patch         | 146 ++++++++++++
 .../patch/peer-round2-manifest.json           |  21 ++
 4 files changed, 546 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-batch-prompt-setup.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-fp16-dispatch.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-hift-tf32.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json

diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-batch-prompt-setup.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-batch-prompt-setup.patch
new file mode 100644
index 000000000..0b993d0ea
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-batch-prompt-setup.patch
@@ -0,0 +1,171 @@
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_prompt_setup_batch.py b/tests/model_executor/models/minicpmo_4_5/test_prompt_setup_batch.py
+new file mode 100644
+index 0000000000..a9c46a0a05
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_prompt_setup_batch.py
+@@ -0,0 +1,41 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++import pytest
++import torch
++
++from tests.model_executor.models.minicpmo_4_5.test_code2wav_batching import _FakeToken2Wav
++from vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav import BatchedToken2Wav
++
++pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
++
++
++@pytest.mark.parametrize("cache_size", [0, 1, 4])
++def test_prompt_batch_preserves_cfg_rows_duplicates_and_cache_ownership(cache_size):
++    token2wav = _FakeToken2Wav()
++    backend = BatchedToken2Wav(token2wav, setup_cache_size=cache_size)
++    prompts = [backend.prepare_prompt(str(i), f"/fake/{i}.wav") for i in range(3)]
++    for i, prompt in enumerate(prompts):
++        prompt.speech_tokens.add_(i * 10)
++    expected = [backend._create_initial_states(prompt, 1)[0] for prompt in prompts]
++    token2wav.flow.decoder.estimator.cfg_batches.clear()
++    actual = backend.setup_many([prompts[2], prompts[0], prompts[2], prompts[1]])
++    assert actual[0] is actual[2]
++    assert token2wav.flow.decoder.estimator.cfg_batches == [6, 6]
++    for state, reference in zip(actual, [expected[2], expected[0], expected[2], expected[1]], strict=True):
++        for key in reference.flow_cache:
++            torch.testing.assert_close(state.flow_cache[key], reference.flow_cache[key], rtol=0, atol=0)
++    snapshot = actual[1].flow_cache["estimator_att_cache"].clone()
++    actual[0].flow_cache["estimator_att_cache"].add_(1)
++    torch.testing.assert_close(actual[1].flow_cache["estimator_att_cache"], snapshot, rtol=0, atol=0)
++    assert len(backend._setup_cache) <= cache_size
++
++
++def test_prompt_batch_reuses_existing_cached_state():
++    backend = BatchedToken2Wav(_FakeToken2Wav(), setup_cache_size=2)
++    first = backend.prepare_prompt("first", "/fake/first.wav")
++    second = backend.prepare_prompt("second", "/fake/second.wav")
++    cached = backend.setup_batch(first, 1)[0]
++    result = backend.setup_many([first, second, first])
++    assert result[0] is result[2] is cached
++    assert backend.setup_many([]) == []
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+index 3e9c849670..55efe8186d 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+@@ -1793,6 +1793,79 @@ class BatchedToken2Wav(nn.Module):
+             for row in split
+         ]
+ 
++    def _create_initial_states_many(self, features: list[PromptFeatures]) -> list[BatchedToken2WavState]:
++        """Share one Euler solve across equal-length, independently encoded prompts."""
++        if len(features) == 1:
++            return self._create_initial_states(features[0], 1)
++        encoded, speakers, mels, cnn, att = [], [], [], [], []
++        with self._autocast(features[0].speaker_embedding.device):
++            for prompt in features:
++                tokens, speaker, mel = self._repeat_prompt(prompt, 1)
++                lookahead_width = self._pre_lookahead_len()
++                lookahead = tokens.new_full((1, 3 if lookahead_width is None else lookahead_width), _SILENCE_TOKEN)
++                hidden, row_cnn, row_att = self._encode_chunk(
++                    torch.cat((tokens, lookahead), dim=1), last_chunk=False, cnn_cache=None, att_cache=None
++                )
++                encoded.append(hidden)
++                speakers.append(self._project_speakers(speaker))
++                mels.append(mel)
++                cnn.append(row_cnn)
++                att.append(row_att)
++            prompt_mels = torch.cat(mels, dim=0)
++            _, estimator_cnn, estimator_att = self._decode_cfm(
++                torch.cat(encoded, dim=0).transpose(1, 2).contiguous(),
++                torch.cat(speakers, dim=0),
++                prompt_mels.transpose(1, 2).contiguous(),
++                cnn_cache=None,
++                att_cache=None,
++                att_keep=(int(prompt_mels.shape[1]), _CACHE_TRIM_SUFFIX),
++            )
++        rows = self._split_flow_cache(
++            {
++                "conformer_cnn_cache": torch.cat(cnn, dim=0),
++                "conformer_att_cache": torch.cat(att, dim=1),
++                "estimator_cnn_cache": estimator_cnn,
++                "estimator_att_cache": estimator_att,
++            },
++            len(features),
++        )
++        return [
++            BatchedToken2WavState(
++                flow_cache=row,
++                hift_cache={
++                    "mel": prompt_mels.new_zeros((1, int(prompt_mels.shape[2]), 0)),
++                    "source": prompt_mels.new_zeros((1, 1, 0)),
++                    "speech": prompt_mels.new_zeros((1, 0)),
++                },
++            )
++            for row in rows
++        ]
++
++    def setup_many(self, features: list[PromptFeatures]) -> list[BatchedToken2WavState]:
++        """Reuse cached states and batch equal-length misses, preserving caller order."""
++        keys = [self._setup_cache_key(prompt) for prompt in features]
++        states: dict[tuple[tuple[str, str], int], BatchedToken2WavState] = {}
++        missing: dict[tuple[tuple[str, str], int], PromptFeatures] = {}
++        for key, prompt in zip(keys, features, strict=True):
++            if key in self._setup_cache:
++                states[key] = self._setup_cache[key]
++                self._setup_cache.move_to_end(key)
++            else:
++                missing.setdefault(key, prompt)
++        groups: dict[tuple[int, int], list[PromptFeatures]] = {}
++        for prompt in missing.values():
++            shape = (int(prompt.speech_tokens.shape[1]), int(prompt.mels.shape[1]))
++            groups.setdefault(shape, []).append(prompt)
++        for prompts in groups.values():
++            for prompt, state in zip(prompts, self._create_initial_states_many(prompts), strict=True):
++                key = self._setup_cache_key(prompt)
++                states[key] = state
++                if self._setup_cache_size > 0:
++                    self._setup_cache[key] = state
++                    while len(self._setup_cache) > self._setup_cache_size:
++                        self._setup_cache.popitem(last=False)
++        return [states[key] for key in keys]
++
+     def _setup_cache_key(self, features: PromptFeatures) -> tuple[tuple[str, str], int]:
+         bucket_frames = (
+             self._cfm_graph_bucket_frames
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+index 4fdbe44879..5ba424d4eb 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+@@ -505,6 +505,7 @@ class MiniCPMO45Code2Wav(nn.Module):
+         self._prompt_wav_override = extra.get("prompt_wav")
+         self._default_prompt_normalized: tuple[str, str] | None = None
+         self._onset_merge = read_bool_flag(extra, "cfm_onset_merge", False)
++        self._batch_prompt_setup = read_bool_flag(extra, "cfm_batch_prompt_setup", False)
+         self._cross_turn_buckets = read_bool_flag(extra, "cfm_cross_turn_buckets", False)
+         self._row_offset_merge = self._cfm_graph_config["row_offset_merge"]
+         self._precapture_empty_cache = read_bool_flag(extra, "cfm_precapture_empty_cache", False)
+@@ -890,9 +891,15 @@ class MiniCPMO45Code2Wav(nn.Module):
+             features.append(prompts[key])
+             if states[row] is None:
+                 fresh.setdefault(key, []).append(row)
+-        for key, rows in fresh.items():
+-            for row, state in zip(rows, self.backend.setup_batch(prompts[key], len(rows)), strict=True):
+-                states[row] = state
++        if getattr(self, "_batch_prompt_setup", False) and len(fresh) > 1:
++            prepared = self.backend.setup_many([prompts[key] for key in fresh])
++            for rows, state in zip(fresh.values(), prepared, strict=True):
++                for row in rows:
++                    states[row] = state
++        else:
++            for key, rows in fresh.items():
++                for row, state in zip(rows, self.backend.setup_batch(prompts[key], len(rows)), strict=True):
++                    states[row] = state
+         if any(state is None for state in states):
+             raise _batch_error("incomplete_setup")
+         return cast(list[BatchedToken2WavState], states), features[0] if len(prompts) == 1 else features
+@@ -1541,6 +1548,8 @@ class MiniCPMO45Code2Wav(nn.Module):
+         tf32_mode = self._tf32_mode if current_omni_platform.is_cuda() else "off"
+         if tf32_mode != "off":
+             logger.info("MiniCPM-o Code2Wav: ordinary TF32 enabled for CFM DiT GEMMs")
++        if self._batch_prompt_setup and not current_omni_platform.is_cuda():
++            raise ValueError("cfm_batch_prompt_setup requires CUDA")
+         use_float16 = read_bool_flag(extra, "token2wav_float16", False)
+         previous_dtype = torch.get_default_dtype()
+         try:
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-fp16-dispatch.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-fp16-dispatch.patch
new file mode 100644
index 000000000..dabbb8e0c
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-fp16-dispatch.patch
@@ -0,0 +1,208 @@
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+new file mode 100644
+index 0000000000..39c416ddaf
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+@@ -0,0 +1,57 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Tiled attention must preserve masking and pooled-row ownership in FP16."""
++
++import pytest
++import torch
++import torch.nn.functional as F
++from torch.nn.attention import SDPBackend, sdpa_kernel
++
++from tests.helpers.mark import hardware_marks
++from vllm_omni.model_executor.models.minicpmo_4_5.cfm_attention import cfm_attention
++
++pytestmark = [pytest.mark.core_model, *hardware_marks(res={"cuda": "L4"}, num_cards=1)]
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++@pytest.mark.parametrize("pooled", [False, True])
++@pytest.mark.parametrize("masked", [False, True])
++@pytest.mark.parametrize("frames,history", [(1, 17), (23, 65), (50, 513)])
++def test_tiled_attention_matches_math_sdpa(dtype, pooled, masked, frames, history):
++    generator = torch.Generator(device="cuda").manual_seed(43)
++    batch, heads, width = 3, 4, 64
++    q = torch.randn(batch, heads, frames, width, device="cuda", dtype=dtype, generator=generator)
++    # K and V are interleaved in the real resident pool, so both views are strided.
++    storage = torch.randn(
++        7 if pooled else batch, heads, history, 2 * width, device="cuda", dtype=dtype, generator=generator
++    )
++    k, v = storage[..., :width], storage[..., width:]
++    rows = torch.tensor([5, 1, 5], device="cuda") if pooled else None
++    mask = None
++    if masked:
++        mask = torch.rand(batch, frames, history, device="cuda", generator=generator) > 0.3
++        mask[0, 0] = False
++    expected_k = k.index_select(0, rows) if pooled else k
++    expected_v = v.index_select(0, rows) if pooled else v
++    with sdpa_kernel(SDPBackend.MATH):
++        expected = F.scaled_dot_product_attention(
++            q.float(),
++            expected_k.float(),
++            expected_v.float(),
++            attn_mask=mask.unsqueeze(1) if mask is not None else None,
++        ).to(dtype)
++    actual = cfm_attention(q, k, v, mask, rows)
++    torch.testing.assert_close(actual, expected, atol=2e-3, rtol=2e-3)
++    assert torch.isfinite(actual).all()
++    if masked:
++        assert torch.count_nonzero(actual[0, :, 0]) == 0
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++def test_tiled_attention_rejects_mixed_cache_dtype(dtype):
++    q = torch.empty(1, 1, 1, 16, dtype=dtype)
++    cache_dtype = torch.float16 if dtype == torch.float32 else torch.float32
++    k = torch.empty_like(q, dtype=cache_dtype)
++    with pytest.raises(ValueError, match="matching float32 or float16"):
++        cfm_attention(q, k, k)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+index 3cf8bdd941..aad9716331 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+@@ -44,14 +44,17 @@ def _run(body, estimator, *, rows: int, frames: int, cached: int, lengths):
+     channels = estimator.blocks[0].conv.block[1].in_channels
+     attn = estimator.blocks[0].attn
+     device = next(estimator.parameters()).device
+-    estimator_input = torch.randn(rows, 320, frames, device=device)
+-    time_embedding = estimator.t_embedder(torch.rand((), device=device).expand(rows)).unsqueeze(1)
++    dtype = next(estimator.parameters()).dtype
++    estimator_input = torch.randn(rows, 320, frames, device=device, dtype=dtype)
++    time_embedding = estimator.t_embedder(torch.rand((), device=device, dtype=dtype).expand(rows)).unsqueeze(1)
+     mask = torch.rand(rows, frames, cached + frames, device=device) > 0.3
+     mask[..., 0] = True
+-    cnn = [torch.randn(rows, 2 * channels, 2, device=device) for _ in range(depth)]
+-    att = [torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device) for _ in range(depth)]
+-    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device)
+-    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device)
++    cnn = [torch.randn(rows, 2 * channels, 2, device=device, dtype=dtype) for _ in range(depth)]
++    att = [
++        torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device, dtype=dtype) for _ in range(depth)
++    ]
++    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device, dtype=dtype)
++    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device, dtype=dtype)
+     with torch.no_grad():
+         out = body(estimator, estimator_input, time_embedding, mask, cnn, att, cnn_out, att_out, lengths)
+     return out, cnn_out, att_out
+@@ -93,3 +96,34 @@ def test_ragged_body_reuses_modulation_without_recomputing_adaln(monkeypatch, ca
+     actual = _run(precomputed, estimator, rows=4, frames=6, cached=cached, lengths=[6, 4])
+     for want, got in zip(expected, actual, strict=True):
+         torch.testing.assert_close(got, want, rtol=1e-4, atol=2e-5)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_fp16_fused_body_matches_fp16_ragged_body(monkeypatch):
++    estimator = _upstream_dit("cuda").half()
++    driver = BatchedToken2Wav.__new__(BatchedToken2Wav)
++    nn.Module.__init__(driver)
++    driver._ragged_fused_body = True
++    calls = []
++
++    def fused(*args, **kwargs):
++        calls.append(True)
++        return blocks_forward_chunk_fused(*args, **kwargs)
++
++    monkeypatch.setattr(
++        "vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav.blocks_forward_chunk_fused",
++        fused,
++    )
++    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.float16):
++        expected = _run(
++            BatchedToken2Wav._blocks_forward_chunk_ragged,
++            estimator,
++            rows=4,
++            frames=6,
++            cached=5,
++            lengths=[6, 4],
++        )
++        actual = _run(driver._ragged_body, estimator, rows=4, frames=6, cached=5, lengths=[6, 4])
++    assert calls, "FP16 service dispatch must use the fused body"
++    for want, got in zip(expected, actual, strict=True):
++        torch.testing.assert_close(got, want, rtol=2e-3, atol=2e-3)
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+index 3e9c849670..3cc96189fb 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+@@ -494,17 +494,25 @@ class BatchedToken2Wav(nn.Module):
+                 micro_batch_size = int(micro_batch_size_cfg) if micro_batch_size_cfg is not None else 4
+                 enable_whole_euler = bool(cfm_graph_cfg.get("enable_whole_euler", True))
+                 if bool(cfm_graph_cfg.get("fused_body", False)):
+-                    # A reduced-precision attention cache keeps the ragged body,
+-                    # which attends in the activation dtype through upstream.
++                    # A BF16 storage-only cache still uses the ragged body.
++                    # CUDA FP16 flow can keep its matching FP16 cache resident.
+                     # NPU uses the same schedule with AddLayerNorm and packed QKV.
+                     self._ragged_fused_body = (
+                         flow_parameter.device.type in {"cuda", "npu"}
+                         and supports_fused_body(estimator)
+-                        and self._estimator_att_cache_dtype == torch.float32
++                        and (
++                            self._estimator_att_cache_dtype == torch.float32
++                            or (
++                                flow_parameter.device.type == "cuda"
++                                and self._estimator_att_cache_dtype == torch.float16
++                                and self._estimator_att_compute_dtype == torch.float16
++                            )
++                        )
+                     )
+                     if not self._ragged_fused_body:
+                         logger.warning(
+-                            "cfm_fused_body requested but unsupported here (DiT blocks or a non-fp32 attention cache)"
++                            "cfm_fused_body requested but unsupported here "
++                            "(DiT blocks or incompatible attention cache dtype)"
+                         )
+                 # Resident request caches need the fused body and its tiled
+                 # attention, which reads keys/values out of the pool in place.
+@@ -1086,7 +1094,10 @@ class BatchedToken2Wav(nn.Module):
+         ``modulation`` comes from the Whole-Euler arena, for either body.
+         """
+         estimator_input = args[1]
+-        if slots is not None or (self._ragged_fused_body and estimator_input.dtype == torch.float32):
++        fused_dtype = estimator_input.dtype == torch.float32 or (
++            estimator_input.is_cuda and estimator_input.dtype == torch.float16
++        )
++        if slots is not None or (self._ragged_fused_body and fused_dtype):
+             # Slot-pool graphs are only built over the fused body (``slot_pool`` above).
+             if estimator_input.device.type == "npu":
+                 from vllm_omni.platforms.npu.models.minicpmo_fused import (
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+index 3ab3f7f96a..e64fcd2f82 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+@@ -1,6 +1,6 @@
+ # SPDX-License-Identifier: Apache-2.0
+ # SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+-"""Tiled CFM attention: float32 tensors, ordinary TF32 Tensor Core dots."""
++"""Tiled CFM attention with FP32/TF32 or FP16 Tensor Core dots."""
+ 
+ import torch
+ from vllm.triton_utils import tl, triton
+@@ -80,7 +80,7 @@ def _attention(
+             (keys[:, None] < nk) & (ds[None, :] < dim),
+             0,
+         )
+-        accumulator = accumulator * correction[:, None] + tl.dot(prob, values, input_precision="tf32")
++        accumulator = accumulator * correction[:, None] + tl.dot(prob.to(values.dtype), values, input_precision="tf32")
+         maximum = new_max
+     result = accumulator / tl.where(denominator > 0, denominator, 1.0)[:, None]
+     tl.store(
+@@ -98,11 +98,11 @@ def cfm_attention(
+     mask: torch.Tensor | None = None,
+     kv_rows: torch.Tensor | None = None,
+ ) -> torch.Tensor:
+-    """Tiled attention with TF32 dots; optional ``kv_rows`` indexes a pooled K/V cache."""
++    """Tiled attention; optional ``kv_rows`` indexes a pooled K/V cache in place."""
+     b, heads, nq, dim = q.shape
+     nk = k.shape[2]
+-    if q.dtype != torch.float32 or k.dtype != torch.float32 or v.dtype != torch.float32:
+-        raise ValueError("CFM tiled attention requires float32 Q/K/V")
++    if q.dtype not in (torch.float32, torch.float16) or k.dtype != q.dtype or v.dtype != q.dtype:
++        raise ValueError("CFM tiled attention requires matching float32 or float16 Q/K/V")
+     num_stages = 2
+     out = torch.empty((b, nq, heads, dim), device=q.device, dtype=q.dtype)
+     _attention[(b, heads, triton.cdiv(nq, 32))](
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-hift-tf32.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-hift-tf32.patch
new file mode 100644
index 000000000..395f38657
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-hift-tf32.patch
@@ -0,0 +1,146 @@
+diff --git a/tests/model_executor/models/cosyvoice3/test_hift_tf32_policy.py b/tests/model_executor/models/cosyvoice3/test_hift_tf32_policy.py
+new file mode 100644
+index 0000000000..c7c2922157
+--- /dev/null
++++ b/tests/model_executor/models/cosyvoice3/test_hift_tf32_policy.py
+@@ -0,0 +1,31 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++import pytest
++import torch
++
++from vllm_omni.model_executor.models.cosyvoice3.code2wav_core.hifigan import _upsample_tf32
++
++pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
++
++
++@pytest.mark.parametrize("enabled", [False, True])
++@pytest.mark.parametrize("initial", [False, True])
++@pytest.mark.parametrize("raise_error", [False, True])
++def test_upsample_policy_restores_after_call(enabled, initial, raise_error):
++    old = (torch.backends.cudnn.allow_tf32, torch.backends.cuda.matmul.allow_tf32)
++    try:
++        torch.backends.cudnn.allow_tf32 = initial
++        torch.backends.cuda.matmul.allow_tf32 = not initial
++        try:
++            with _upsample_tf32(enabled):
++                assert torch.backends.cudnn.allow_tf32 == (True if enabled else initial)
++                assert torch.backends.cuda.matmul.allow_tf32 == (True if enabled else not initial)
++                if raise_error:
++                    raise RuntimeError("decoder failure")
++        except RuntimeError as exc:
++            assert str(exc) == "decoder failure"
++        assert torch.backends.cudnn.allow_tf32 == initial
++        assert torch.backends.cuda.matmul.allow_tf32 == (not initial)
++    finally:
++        torch.backends.cudnn.allow_tf32, torch.backends.cuda.matmul.allow_tf32 = old
+diff --git a/vllm_omni/model_executor/models/cosyvoice3/code2wav_core/hifigan.py b/vllm_omni/model_executor/models/cosyvoice3/code2wav_core/hifigan.py
+index 293315d620..5dcae8c21b 100644
+--- a/vllm_omni/model_executor/models/cosyvoice3/code2wav_core/hifigan.py
++++ b/vllm_omni/model_executor/models/cosyvoice3/code2wav_core/hifigan.py
+@@ -8,6 +8,7 @@
+ 
+ import math
+ import os
++from contextlib import contextmanager
+ 
+ import numpy as np
+ import torch
+@@ -35,6 +36,23 @@ This code is modified from https://github.com/jik876/hifi-gan
+ """
+ 
+ 
++@contextmanager
++def _upsample_tf32(enabled: bool):
++    """Scope reduced precision to the HiFT upsampling blocks."""
++    if not enabled:
++        yield
++        return
++    previous_cudnn = torch.backends.cudnn.allow_tf32
++    previous_matmul = torch.backends.cuda.matmul.allow_tf32
++    try:
++        torch.backends.cudnn.allow_tf32 = True
++        torch.backends.cuda.matmul.allow_tf32 = True
++        yield
++    finally:
++        torch.backends.cudnn.allow_tf32 = previous_cudnn
++        torch.backends.cuda.matmul.allow_tf32 = previous_matmul
++
++
+ def init_weights(m, mean=0.0, std=0.01):
+     classname = m.__class__.__name__
+     if classname.find("Conv") != -1:
+@@ -589,6 +607,7 @@ class HiFTGenerator(nn.Module):
+     ):
+         super().__init__()
+ 
++        self.upsample_tf32 = False
+         self.out_channels = 1
+         self.nb_harmonics = nb_harmonics
+         self.sampling_rate = sampling_rate
+@@ -838,26 +857,26 @@ class HiFTGenerator(nn.Module):
+         s_stft = torch.cat([s_stft_real, s_stft_imag], dim=1)
+ 
+         x = self.conv_pre(x)
+-        for i in range(self.num_upsamples):
+-            x = F.leaky_relu(x, self.lrelu_slope)
+-            x = self.ups[i](x)
+-
+-            if i == self.num_upsamples - 1:
+-                x = self.reflection_pad(x)
+-
+-            # fusion
+-            si = self.source_downs[i](s_stft)
+-            si = self.source_resblocks[i](si)
+-            x = x + si
+-
+-            xs = None
+-            for j in range(self.num_kernels):
+-                if xs is None:
+-                    xs = self.resblocks[i * self.num_kernels + j](x)
+-                else:
+-                    xs += self.resblocks[i * self.num_kernels + j](x)
+-            x = xs / self.num_kernels
+-
++        with _upsample_tf32(self.upsample_tf32 and x.is_cuda):
++            for i in range(self.num_upsamples):
++                x = F.leaky_relu(x, self.lrelu_slope)
++                x = self.ups[i](x)
++
++                if i == self.num_upsamples - 1:
++                    x = self.reflection_pad(x)
++
++                # fusion
++                si = self.source_downs[i](s_stft)
++                si = self.source_resblocks[i](si)
++                x = x + si
++
++                xs = None
++                for j in range(self.num_kernels):
++                    if xs is None:
++                        xs = self.resblocks[i * self.num_kernels + j](x)
++                    else:
++                        xs += self.resblocks[i * self.num_kernels + j](x)
++                x = xs / self.num_kernels
+         x = F.leaky_relu(x)
+         x = self.conv_post(x)
+         magnitude = torch.exp(x[:, : self.istft_params["n_fft"] // 2 + 1, :])
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+index 4fdbe44879..799f58f57c 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+@@ -1559,6 +1559,13 @@ class MiniCPMO45Code2Wav(nn.Module):
+         finally:
+             torch.set_default_dtype(previous_dtype)
+ 
++        hift_tf32 = read_bool_flag(extra, "hift_upsample_tf32", False)
++        if hift_tf32 and not current_omni_platform.is_cuda():
++            raise ValueError("hift_upsample_tf32 requires CUDA")
++        token2wav.hift.upsample_tf32 = hift_tf32
++        if hift_tf32:
++            logger.info("MiniCPM-o Code2Wav: TF32 enabled for HiFT upsampling blocks")
++
+         trt_stepper = None
+         # Parsed before the platform branches: a typo in a shared stage config
+         # must fail at startup on every platform, not only where the toggle is
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
new file mode 100644
index 000000000..b3e8f2d95
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
@@ -0,0 +1,21 @@
+{
+  "base_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "implementations": {
+    "fp16-dispatch": {
+      "source_revision": "b6dacdf03756dbedeee8592577798670f5e22329",
+      "patch": "peer-round2-fp16-dispatch.patch",
+      "status": "Exploratory implementation; not quality/performance qualified"
+    },
+    "hift-tf32": {
+      "source_revision": "460b64d7727585516be3b3c992cf0154b82f2cf9",
+      "patch": "peer-round2-hift-tf32.patch",
+      "status": "Exploratory implementation; not quality/performance qualified"
+    },
+    "batch-prompt-setup": {
+      "source_revision": "d255857c1d1441ba77362da6d4cb628fa5dc47a8",
+      "patch": "peer-round2-batch-prompt-setup.patch",
+      "status": "Exploratory implementation; not quality/performance qualified"
+    }
+  },
+  "note": "Apply each patch independently to the base. Default behavior remains unchanged unless the corresponding opt-in config is enabled. Do not combine or promote failed candidates as a qualified release."
+}

From 37e654fe2cdd131c0e52c35a0774391cfeadb179 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 15:49:18 +0800
Subject: [PATCH 26/40] Archive request evidence and freeze selective CFM
 precision trial

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |  12 +++
 .../plan/peer-round2-cfm-only-fp16.json       |  17 ++++
 .../peer-round2-baseline-requests.json.gz     | Bin 0 -> 679591 bytes
 .../results/peer-round2-baseline.json         |  55 ++++++++++--
 .../results/peer-round2-screen-artifact.json  |  17 ++++
 ...eer-round2-screen-requests-quality.json.gz | Bin 0 -> 374138 bytes
 .../results/peer-round2-status.json           |  25 ++++++
 .../validator/peer_round2_probe_hift.py       |  84 ++++++++++++++++++
 .../validator/peer_round2_probe_setup.py      |  80 +++++++++++++++++
 9 files changed, 283 insertions(+), 7 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-only-fp16.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline-requests.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_hift.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_setup.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index cb794a545..139a24a00 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -1,5 +1,17 @@
 # MiniCPM-o 4.5: single-L20X throughput study
 
+## Round two: active, INCONCLUSIVE
+
+The requester asked to continue until vLLM-Omni exceeds the source-pinned single-GPU peer at C16 and C32 while retaining the authorized quality margins. This goal is **not achieved**. The earlier failed campaign remains documented below.
+
+- [Frozen continuation plan and unused256-prompt cohort](plan/peer-round2.json), [current status](results/peer-round2-status.json), and [acceptance issue](https://github.com/InferMatrixLab/InferRSI/issues/49).
+- [Peer repeated baseline](results/peer-round2-baseline.json): exploratory mean C16/C32 throughput1698.4/2532.2 frames/s; final candidate confirmation still requires equivalent repeated comparison. The fast peer profile is not the speech-quality reference.
+- [Screening speech quality](results/peer-round2-screen-quality.json), [FP16 dispatch correction](results/peer-round2-dispatch-screen.json), and [FP32 batch-width screen](results/peer-round2-batch16-screen.json). Reused64-prompt screens do not establish final acceptance.
+- [Rejected prompt-setup numerical result](results/peer-round2-setup-numerical.json), [HiFT precision screen](results/peer-round2-screen-hift-tf32-mps.json), and [FP16 residency screen](results/peer-round2-screen-fp16-resident16-mps.json).
+- [Independent operator profile](results/peer-round2-stage2-profile.json) motivates the [active graph-coverage trials](plan/peer-round2-graph-coverage.json). Profiled requests are excluded from performance aggregates.
+- [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
+
+
 Acceptance: [InferRSI #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
 
 **Original strict quality verdict: FAIL** for both completed historical speaker-only and speaker+MPS candidates. The separately authorized noninferiority evaluation on previously unused prompts also **FAILS** on C16/C32 WER. The adapted revision also FAILS its separately scoped regression against updated main (C16 WER, C32 WER/SIM). No later comparison changes the earlier verdicts. Component PASS does not establish service PASS.
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-only-fp16.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-only-fp16.json
new file mode 100644
index 000000000..293b2caaf
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-only-fp16.json
@@ -0,0 +1,17 @@
+{
+  "frozen_at_utc": "2026-10-21T07:44:03.488910+00:00",
+  "parent_revision": "b6dacdf03756dbedeee8592577798670f5e22329",
+  "hypothesis": "The existing global float16 flag also converts the flow encoder and speaker projection. Keep those in FP32 and apply FP16 only to the CFM estimator and its noise/cache path, to test whether encoder precision caused the observed SIM degradation.",
+  "scope": "New opt-in cfm_float16, default off; no changes to model weights on disk, sampling, Euler step count, output length limits, HiFT or speaker extraction.",
+  "operator_checks": "Existing FP16 attention and DiT numerical parity tests; verify encoder parameters and execution stay FP32 while estimator execution/cache is FP16, and disabled defaults remain unchanged.",
+  "quality_screen": "Use the original first64 tuning prompts at C1/C16/C32 and report WER/SIM/UTMOS before promotion. This precision experiment uses the existing frozen speech noninferiority contract; it does not change or retroactively rejudge the failed waveform-parity gate of prompt batching.",
+  "service_screen": "Same Torch+MPS baseline config, microbatch4 and stage capacities16;64 reused tuning prompts,discard+one measured repeat.",
+  "holdout": "256 reserved IDs remain unused until final candidate selection.",
+  "candidate_revision": "4671fdc3736c760f1abd637e30079b3cf65d1fdf",
+  "pre_service_checks": {
+    "gpu_dit_and_precision": 7,
+    "cpu_batching_and_cfm": 222,
+    "changed_file_precommit": "PASS",
+    "gpu_test_environment": "Small numerical tests ran on the campaign-owned ASR reservation, excluded from any service timing."
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline-requests.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline-requests.json.gz
new file mode 100644
index 0000000000000000000000000000000000000000..0e4d73000a3393c2c0a46de509b7057df1d3a4d1
GIT binary patch
literal 679591
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json
index 68c250c5b..2a3c4f0dd 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-baseline.json
@@ -33,7 +33,13 @@
           "ttfa_p95_s": 0.13088538954034448,
           "rtf_mean": 0.0632034071902775
         }
-      ]
+      ],
+      "pooled_requests": {
+        "n": 640,
+        "ttfa_p50_s": 0.1256165779195726,
+        "ttfa_p95_s": 0.13093884550034998,
+        "rtf_mean": 0.06318489771332836
+      }
     },
     "2": {
       "measured_repeats": 3,
@@ -72,7 +78,13 @@
           "ttfa_p95_s": 0.2222554690670222,
           "rtf_mean": 0.09772136390236967
         }
-      ]
+      ],
+      "pooled_requests": {
+        "n": 960,
+        "ttfa_p50_s": 0.19014606857672334,
+        "ttfa_p95_s": 0.22433129511773586,
+        "rtf_mean": 0.09719417906213433
+      }
     },
     "4": {
       "measured_repeats": 3,
@@ -111,7 +123,13 @@
           "ttfa_p95_s": 0.30483588576316833,
           "rtf_mean": 0.13376456603001535
         }
-      ]
+      ],
+      "pooled_requests": {
+        "n": 960,
+        "ttfa_p50_s": 0.2666403064504266,
+        "ttfa_p95_s": 0.3053204839117825,
+        "rtf_mean": 0.13440840311578064
+      }
     },
     "8": {
       "measured_repeats": 3,
@@ -150,7 +168,13 @@
           "ttfa_p95_s": 0.42942166929133235,
           "rtf_mean": 0.1795888738090082
         }
-      ]
+      ],
+      "pooled_requests": {
+        "n": 960,
+        "ttfa_p50_s": 0.35363235231488943,
+        "ttfa_p95_s": 0.4168954434804618,
+        "rtf_mean": 0.18023458369240614
+      }
     },
     "16": {
       "measured_repeats": 3,
@@ -189,7 +213,13 @@
           "ttfa_p95_s": 0.528660918166861,
           "rtf_mean": 0.24007690743674245
         }
-      ]
+      ],
+      "pooled_requests": {
+        "n": 960,
+        "ttfa_p50_s": 0.4708248642273247,
+        "ttfa_p95_s": 0.5505937870591879,
+        "rtf_mean": 0.23786546822411667
+      }
     },
     "32": {
       "measured_repeats": 3,
@@ -228,7 +258,18 @@
           "ttfa_p95_s": 0.7602412773296238,
           "rtf_mean": 0.31384059524310237
         }
-      ]
+      ],
+      "pooled_requests": {
+        "n": 960,
+        "ttfa_p50_s": 0.6524820369668305,
+        "ttfa_p95_s": 0.7602832305710763,
+        "rtf_mean": 0.3142057741915752
+      }
     }
-  }
+  },
+  "request_artifact": {
+    "path": "peer-round2-baseline-requests.json.gz",
+    "sha256": "09a7276f680e46955f11276dbbc32489bd33a596857c2ee428bb99e25e0ae841"
+  },
+  "metric_note": "Throughput mean averages repeat throughputs. pooled_requests gives TTFA percentiles across all retained requests; mean preserves the separately labeled arithmetic mean of per-run percentiles."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
new file mode 100644
index 000000000..d82aeb0cf
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
@@ -0,0 +1,17 @@
+{
+  "scope": "All completed first-round tuning screens; reused data, no final acceptance",
+  "path": "peer-round2-screen-requests-quality.json.gz",
+  "sha256": "bfcae076229b1940285b723bdd2aaebc9c451c60aa5107e553caa103d94e27c5",
+  "profiles": [
+    "screen-torch-mps",
+    "screen-capacity32-mps",
+    "screen-fp16-mps",
+    "screen-fp16-fused-mps",
+    "screen-fp16-pool-mps",
+    "screen-fp16-dispatch-mps",
+    "screen-fp32-batch16-mps",
+    "screen-hift-tf32-mps",
+    "screen-fp16-resident16-mps"
+  ],
+  "privacy": "Audio and ASR hypothesis text are excluded. Audio hashes and error counts remain."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
new file mode 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
new file mode 100644
index 000000000..d8effdff7
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -0,0 +1,25 @@
+{
+  "verdict": "INCONCLUSIVE",
+  "goal": "Exceed peer at C16 andC32 with all frozen speech noninferiority gates passing",
+  "achieved": false,
+  "completed": [
+    "Peer six-concurrency repeated baseline",
+    "FP16 runtime dispatch implementation and screening",
+    "HiFT scoped TF32 implementation and screening",
+    "FP32 microbatch16 screening",
+    "Prompt setup batching implementation and failed numerical gate",
+    "Independent stage2 profiler"
+  ],
+  "active": [
+    "CFM graph capacity128 screening",
+    "HiFT exact batch1/2/4 graph screening"
+  ],
+  "reserved_holdout_used": false,
+  "quality_margins": {
+    "wer_percentage_points": 0.2,
+    "sim_x100_drop": 0.5,
+    "utmos_drop": 0.05
+  },
+  "prior_campaign_verdicts": "unchanged",
+  "acceptance_issue": "https://github.com/InferMatrixLab/InferRSI/issues/49"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_hift.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_hift.py
new file mode 100644
index 000000000..3a9386194
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_hift.py
@@ -0,0 +1,84 @@
+import argparse
+import json
+import math
+from pathlib import Path
+
+import soundfile as sf
+import torch
+from bench.workload import load_seed_tts_rows, make_id_sets
+from scipy.signal import resample_poly
+from vllm_omni.model_executor.models.cosyvoice3.utils import mel_spectrogram
+from vllm_omni.model_executor.models.step_audio2.step_audio2_token2wav import _build_hift
+
+args_parser = argparse.ArgumentParser()
+args_parser.add_argument("--model", type=Path, required=True)
+args_parser.add_argument("--out", type=Path, required=True)
+a = args_parser.parse_args()
+a.out.parent.mkdir(parents=True, exist_ok=True)
+r = a.out.parent
+torch.set_num_threads(4)
+torch.backends.cuda.matmul.allow_tf32 = False
+torch.backends.cudnn.allow_tf32 = False
+model = _build_hift()
+weights = torch.load(a.model / "assets/token2wav/hift.pt", map_location="cpu", weights_only=True)
+model.load_state_dict({k.replace("generator.", ""): v for k, v in weights.items()}, strict=True)
+model = model.cuda().eval()
+rows = load_seed_tts_rows()
+ids = make_id_sets(rows).tuning_pool[:16]
+byid = {x.row_id: x for x in rows}
+results = []
+with torch.inference_mode():
+    for i, ident in enumerate(ids):
+        wav, sr = sf.read(byid[ident].ref_wav_path, dtype="float32")
+        wav = wav.mean(axis=1) if wav.ndim == 2 else wav
+        if sr != 24000:
+            g = math.gcd(sr, 24000)
+            wav = resample_poly(wav, 24000 // g, sr // g).astype("float32")
+        mel = mel_spectrogram(
+            torch.from_numpy(wav).unsqueeze(0),
+            n_fft=1920,
+            num_mels=80,
+            sampling_rate=24000,
+            hop_size=480,
+            win_size=1920,
+            fmin=0,
+            fmax=8000,
+            center=False,
+        ).cuda()
+        assert mel.shape[-1] >= 56
+        for width in [16, 50, 56]:
+            x = mel[..., :width].contiguous()
+            source = torch.empty(1, 1, 0, device="cuda")
+            pair = []
+            for enabled in [False, True]:
+                model.upsample_tf32 = enabled
+                torch.manual_seed(1000 + i)
+                pair.append(tuple(y.clone() for y in model.inference(x, source)))
+                assert (
+                    not torch.backends.cudnn.allow_tf32
+                    and not torch.backends.cuda.matmul.allow_tf32
+                )
+            torch.testing.assert_close(pair[0][1], pair[1][1], rtol=0, atol=0)
+            err = float(
+                torch.linalg.vector_norm(pair[1][0] - pair[0][0])
+                / torch.linalg.vector_norm(pair[0][0]).clamp_min(1e-12)
+            )
+            results.append(
+                {
+                    "prompt_index": i,
+                    "mel_frames": width,
+                    "relative_l2": err,
+                    "max_absolute": float((pair[1][0] - pair[0][0]).abs().max()),
+                }
+            )
+        print(i, max(x["relative_l2"] for x in results[-3:]), flush=True)
+report = {
+    "scope": (
+        "48 real-speech windows, official HiFT weights, matched random source, empty source cache"
+    ),
+    "rows": results,
+    "max_relative_l2": max(x["relative_l2"] for x in results),
+    "verdict": "PASS" if all(x["relative_l2"] <= 0.01 for x in results) else "FAIL",
+}
+a.out.write_text(json.dumps(report, indent=2) + "\n")
+print(report["verdict"], report["max_relative_l2"], flush=True)
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_setup.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_setup.py
new file mode 100644
index 000000000..73607fd47
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_probe_setup.py
@@ -0,0 +1,80 @@
+import argparse
+import json
+import math
+from pathlib import Path
+
+import soundfile as sf
+import torch
+from bench.workload import load_seed_tts_rows, make_id_sets
+from scipy.signal import resample_poly
+from vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav import BatchedToken2Wav
+from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_token2wav import MiniCPMO45Token2wav
+
+args_parser = argparse.ArgumentParser()
+args_parser.add_argument("--model", type=Path, required=True)
+args_parser.add_argument("--out", type=Path, required=True)
+a = args_parser.parse_args()
+a.out.parent.mkdir(parents=True, exist_ok=True)
+r = a.out.parent
+tmp = r / "setup-prompts"
+tmp.mkdir(exist_ok=True)
+torch.set_num_threads(4)
+torch.backends.cudnn.allow_tf32 = False
+torch.backends.cuda.matmul.allow_tf32 = False
+model = MiniCPMO45Token2wav(str(a.model / "assets/token2wav"), device="cuda", float16=False)
+backend = BatchedToken2Wav(model, setup_cache_size=0, cfm_tf32=True)
+rows = load_seed_tts_rows()
+ids = make_id_sets(rows).tuning_pool[:64]
+byid = {x.row_id: x for x in rows}
+features = []
+for ident in ids:
+    wav, sr = sf.read(byid[ident].ref_wav_path, dtype="float32")
+    wav = wav.mean(axis=1) if wav.ndim == 2 else wav
+    if len(wav) < 6 * sr:
+        continue
+    wav = wav[: 6 * sr]
+    if sr != 24000:
+        g = math.gcd(sr, 24000)
+        wav = resample_poly(wav, 24000 // g, sr // g).astype("float32")
+    p = tmp / f"{len(features)}.wav"
+    sf.write(p, wav, 24000)
+    features.append(backend.prepare_prompt(str(len(features)), str(p)))
+    if len(features) == 4:
+        break
+assert len(features) == 4
+assert len({(x.speech_tokens.shape[1], x.mels.shape[1]) for x in features}) == 1
+results = []
+
+
+def error(a, b):
+    return float(torch.linalg.vector_norm(a - b) / torch.linalg.vector_norm(a).clamp_min(1e-12))
+
+
+with torch.inference_mode():
+    reference = [backend.setup_batch(x, 1)[0] for x in features]
+    candidate = backend.setup_many(features)
+    for i, (a, b) in enumerate(zip(reference, candidate)):
+        metrics = {}
+        for k in a.flow_cache:
+            if k.startswith("conformer"):
+                torch.testing.assert_close(a.flow_cache[k], b.flow_cache[k], rtol=0, atol=0)
+            metrics[k] = error(a.flow_cache[k], b.flow_cache[k])
+        tokens = features[i].speech_tokens[:, :28].contiguous()
+        torch.manual_seed(2000 + i)
+        aa, _ = backend.decode_batch(tokens, features[i], [a], last_chunk=False)
+        torch.manual_seed(2000 + i)
+        bb, _ = backend.decode_batch(tokens, features[i], [b], last_chunk=False)
+        metrics["continuation_audio"] = error(aa[0], bb[0])
+        results.append({"prompt_index": i, "errors": metrics})
+        print(results[-1], flush=True)
+report = {
+    "scope": (
+        "Four distinct six-second references from the first64 reused tuning IDs; "
+        "individual encoders, shared FP32 prompt solve, paired continuation on "
+        "reference speech tokens"
+    ),
+    "rows": results,
+    "verdict": "PASS" if all(v <= 0.01 for x in results for v in x["errors"].values()) else "FAIL",
+}
+a.out.write_text(json.dumps(report, indent=2) + "\n")
+print(report["verdict"], flush=True)

From e0fd872592ad604e6d8d0479ccfc73e4e5b26e6e Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 16:06:15 +0800
Subject: [PATCH 27/40] Record graph and precision screens; investigate
 same-GPU replicas

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   3 +-
 .../patch/peer-round2-cfm-only-fp16.patch     | 340 ++++++++++++
 .../patch/peer-round2-manifest.json           |   5 +
 .../plan/peer-round2-component-profile.json   |  11 +
 .../plan/peer-round2-stage2-replicas.json     |  14 +
 .../peer-round2-cfm-only-fp16-screen.json     | 141 +++++
 .../results/peer-round2-graph-quality.json.gz | Bin 0 -> 27167 bytes
 .../results/peer-round2-graph-screens.json    | 363 ++++++++++++
 .../peer-round2-prompt-components.json        | 519 ++++++++++++++++++
 .../results/peer-round2-screen-quality.json   |  82 +++
 .../results/peer-round2-status.json           |   8 +-
 11 files changed, 1482 insertions(+), 4 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-only-fp16.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-component-profile.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-graph-quality.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-graph-screens.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-prompt-components.json

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 139a24a00..496106658 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -8,7 +8,8 @@ The requester asked to continue until vLLM-Omni exceeds the source-pinned single
 - [Peer repeated baseline](results/peer-round2-baseline.json): exploratory mean C16/C32 throughput1698.4/2532.2 frames/s; final candidate confirmation still requires equivalent repeated comparison. The fast peer profile is not the speech-quality reference.
 - [Screening speech quality](results/peer-round2-screen-quality.json), [FP16 dispatch correction](results/peer-round2-dispatch-screen.json), and [FP32 batch-width screen](results/peer-round2-batch16-screen.json). Reused64-prompt screens do not establish final acceptance.
 - [Rejected prompt-setup numerical result](results/peer-round2-setup-numerical.json), [HiFT precision screen](results/peer-round2-screen-hift-tf32-mps.json), and [FP16 residency screen](results/peer-round2-screen-fp16-resident16-mps.json).
-- [Independent operator profile](results/peer-round2-stage2-profile.json) motivates the [active graph-coverage trials](plan/peer-round2-graph-coverage.json). Profiled requests are excluded from performance aggregates.
+- [Independent operator profile](results/peer-round2-stage2-profile.json) motivates the [completed graph-coverage trials](results/peer-round2-graph-screens.json). Profiled requests are excluded from performance aggregates.
+- [Active selective CFM precision trial](plan/peer-round2-cfm-only-fp16.json), retaining the FP32 encoder; no quality claim until scoring.
 - [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-only-fp16.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-only-fp16.patch
new file mode 100644
index 000000000..612df9eea
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-only-fp16.patch
@@ -0,0 +1,340 @@
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+new file mode 100644
+index 0000000000..39c416ddaf
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+@@ -0,0 +1,57 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Tiled attention must preserve masking and pooled-row ownership in FP16."""
++
++import pytest
++import torch
++import torch.nn.functional as F
++from torch.nn.attention import SDPBackend, sdpa_kernel
++
++from tests.helpers.mark import hardware_marks
++from vllm_omni.model_executor.models.minicpmo_4_5.cfm_attention import cfm_attention
++
++pytestmark = [pytest.mark.core_model, *hardware_marks(res={"cuda": "L4"}, num_cards=1)]
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++@pytest.mark.parametrize("pooled", [False, True])
++@pytest.mark.parametrize("masked", [False, True])
++@pytest.mark.parametrize("frames,history", [(1, 17), (23, 65), (50, 513)])
++def test_tiled_attention_matches_math_sdpa(dtype, pooled, masked, frames, history):
++    generator = torch.Generator(device="cuda").manual_seed(43)
++    batch, heads, width = 3, 4, 64
++    q = torch.randn(batch, heads, frames, width, device="cuda", dtype=dtype, generator=generator)
++    # K and V are interleaved in the real resident pool, so both views are strided.
++    storage = torch.randn(
++        7 if pooled else batch, heads, history, 2 * width, device="cuda", dtype=dtype, generator=generator
++    )
++    k, v = storage[..., :width], storage[..., width:]
++    rows = torch.tensor([5, 1, 5], device="cuda") if pooled else None
++    mask = None
++    if masked:
++        mask = torch.rand(batch, frames, history, device="cuda", generator=generator) > 0.3
++        mask[0, 0] = False
++    expected_k = k.index_select(0, rows) if pooled else k
++    expected_v = v.index_select(0, rows) if pooled else v
++    with sdpa_kernel(SDPBackend.MATH):
++        expected = F.scaled_dot_product_attention(
++            q.float(),
++            expected_k.float(),
++            expected_v.float(),
++            attn_mask=mask.unsqueeze(1) if mask is not None else None,
++        ).to(dtype)
++    actual = cfm_attention(q, k, v, mask, rows)
++    torch.testing.assert_close(actual, expected, atol=2e-3, rtol=2e-3)
++    assert torch.isfinite(actual).all()
++    if masked:
++        assert torch.count_nonzero(actual[0, :, 0]) == 0
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++def test_tiled_attention_rejects_mixed_cache_dtype(dtype):
++    q = torch.empty(1, 1, 1, 16, dtype=dtype)
++    cache_dtype = torch.float16 if dtype == torch.float32 else torch.float32
++    k = torch.empty_like(q, dtype=cache_dtype)
++    with pytest.raises(ValueError, match="matching float32 or float16"):
++        cfm_attention(q, k, k)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+index 3cf8bdd941..e40424b57c 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+@@ -44,14 +44,17 @@ def _run(body, estimator, *, rows: int, frames: int, cached: int, lengths):
+     channels = estimator.blocks[0].conv.block[1].in_channels
+     attn = estimator.blocks[0].attn
+     device = next(estimator.parameters()).device
+-    estimator_input = torch.randn(rows, 320, frames, device=device)
+-    time_embedding = estimator.t_embedder(torch.rand((), device=device).expand(rows)).unsqueeze(1)
++    dtype = next(estimator.parameters()).dtype
++    estimator_input = torch.randn(rows, 320, frames, device=device, dtype=dtype)
++    time_embedding = estimator.t_embedder(torch.rand((), device=device, dtype=dtype).expand(rows)).unsqueeze(1)
+     mask = torch.rand(rows, frames, cached + frames, device=device) > 0.3
+     mask[..., 0] = True
+-    cnn = [torch.randn(rows, 2 * channels, 2, device=device) for _ in range(depth)]
+-    att = [torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device) for _ in range(depth)]
+-    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device)
+-    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device)
++    cnn = [torch.randn(rows, 2 * channels, 2, device=device, dtype=dtype) for _ in range(depth)]
++    att = [
++        torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device, dtype=dtype) for _ in range(depth)
++    ]
++    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device, dtype=dtype)
++    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device, dtype=dtype)
+     with torch.no_grad():
+         out = body(estimator, estimator_input, time_embedding, mask, cnn, att, cnn_out, att_out, lengths)
+     return out, cnn_out, att_out
+@@ -93,3 +96,64 @@ def test_ragged_body_reuses_modulation_without_recomputing_adaln(monkeypatch, ca
+     actual = _run(precomputed, estimator, rows=4, frames=6, cached=cached, lengths=[6, 4])
+     for want, got in zip(expected, actual, strict=True):
+         torch.testing.assert_close(got, want, rtol=1e-4, atol=2e-5)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_fp16_fused_body_matches_fp16_ragged_body(monkeypatch):
++    estimator = _upstream_dit("cuda").half()
++    driver = BatchedToken2Wav.__new__(BatchedToken2Wav)
++    nn.Module.__init__(driver)
++    driver._ragged_fused_body = True
++    calls = []
++
++    def fused(*args, **kwargs):
++        calls.append(True)
++        return blocks_forward_chunk_fused(*args, **kwargs)
++
++    monkeypatch.setattr(
++        "vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav.blocks_forward_chunk_fused",
++        fused,
++    )
++    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.float16):
++        expected = _run(
++            BatchedToken2Wav._blocks_forward_chunk_ragged,
++            estimator,
++            rows=4,
++            frames=6,
++            cached=5,
++            lengths=[6, 4],
++        )
++        actual = _run(driver._ragged_body, estimator, rows=4, frames=6, cached=5, lengths=[6, 4])
++    assert calls, "FP16 service dispatch must use the fused body"
++    for want, got in zip(expected, actual, strict=True):
++        torch.testing.assert_close(got, want, rtol=2e-3, atol=2e-3)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_cfm_only_fp16_preserves_encoder_precision_and_returns_half_caches():
++    from tests.model_executor.models.minicpmo_4_5.test_code2wav_batching import _FakeToken2Wav
++
++    token2wav = _FakeToken2Wav()
++    token2wav.flow.encoder.register_parameter("anchor", nn.Parameter(torch.ones(1, device="cuda")))
++    token2wav.flow.decoder.estimator = _upstream_dit("cuda")
++    token2wav.flow.decoder.rand_noise = torch.randn(1, 80, 100, device="cuda")
++    backend = BatchedToken2Wav(token2wav, cfm_float16=True)
++    assert not backend.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
++    assert next(token2wav.flow.decoder.estimator.parameters()).dtype == torch.float16
++    matrix = torch.randn(8, 8, device="cuda")
++    with backend._autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float32
++    with backend._cfm_autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float16
++    assert not torch.is_autocast_enabled("cuda")
++    with torch.inference_mode():
++        mel, cnn, att = backend._decode_cfm(
++            torch.randn(1, 80, 6, device="cuda"),
++            torch.randn(1, 80, device="cuda"),
++            torch.randn(1, 80, 6, device="cuda"),
++            cnn_cache=None,
++            att_cache=None,
++        )
++    assert mel.dtype == cnn.dtype == att.dtype == torch.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+index 3e9c849670..96bf8528d1 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+@@ -322,14 +322,20 @@ def _cfm_matmul_tf32(fn):
+ 
+     @functools.wraps(fn)
+     def wrapper(self, *args, **kwargs):
+-        if not getattr(self, "_cfm_tf32", False):
+-            return fn(self, *args, **kwargs)
+-        previous = torch.backends.cuda.matmul.allow_tf32
+-        torch.backends.cuda.matmul.allow_tf32 = True
+-        try:
+-            return fn(self, *args, **kwargs)
+-        finally:
+-            torch.backends.cuda.matmul.allow_tf32 = previous
++        precision = (
++            self._cfm_autocast(next(self.flow.parameters()).device)
++            if getattr(self, "_cfm_only_float16", False)
++            else nullcontext()
++        )
++        with precision:
++            if not getattr(self, "_cfm_tf32", False):
++                return fn(self, *args, **kwargs)
++            previous = torch.backends.cuda.matmul.allow_tf32
++            torch.backends.cuda.matmul.allow_tf32 = True
++            try:
++                return fn(self, *args, **kwargs)
++            finally:
++                torch.backends.cuda.matmul.allow_tf32 = previous
+ 
+     return wrapper
+ 
+@@ -355,6 +361,7 @@ class BatchedToken2Wav(nn.Module):
+         setup_cache_size: int = 1,
+         cfm_tf32: bool = False,
+         encoder_graph_config: Mapping[str, Any] | None = None,
++        cfm_float16: bool = False,
+     ):
+         super().__init__()
+         if setup_cache_size < 0:
+@@ -371,6 +378,13 @@ class BatchedToken2Wav(nn.Module):
+         self.flow = token2wav.flow
+         self.hift = token2wav.hift
+         flow_parameter = next(self.flow.parameters(), None)
++        self._cfm_only_float16 = bool(cfm_float16 and not token2wav.float16)
++        if self._cfm_only_float16:
++            if flow_parameter is None or flow_parameter.device.type != "cuda":
++                raise ValueError("cfm_float16 requires CUDA")
++            self.flow.decoder.estimator.half()
++            self.flow.decoder.rand_noise = self.flow.decoder.rand_noise.half()
++
+         if flow_parameter is not None and flow_parameter.device.type == "npu":
+             from vllm_omni.platforms.npu.models.minicpmo_fused import prepare_estimator
+ 
+@@ -431,7 +445,7 @@ class BatchedToken2Wav(nn.Module):
+             del speech, source
+             torch.accelerator.empty_cache()
+         self.float16 = bool(token2wav.float16)
+-        self._estimator_att_compute_dtype = torch.float16 if self.float16 else torch.float32
++        self._estimator_att_compute_dtype = torch.float16 if self.float16 or self._cfm_only_float16 else torch.float32
+         self._estimator_att_cache_dtype = (
+             torch.bfloat16 if bfloat16_attention_cache else self._estimator_att_compute_dtype
+         )
+@@ -494,17 +508,25 @@ class BatchedToken2Wav(nn.Module):
+                 micro_batch_size = int(micro_batch_size_cfg) if micro_batch_size_cfg is not None else 4
+                 enable_whole_euler = bool(cfm_graph_cfg.get("enable_whole_euler", True))
+                 if bool(cfm_graph_cfg.get("fused_body", False)):
+-                    # A reduced-precision attention cache keeps the ragged body,
+-                    # which attends in the activation dtype through upstream.
++                    # A BF16 storage-only cache still uses the ragged body.
++                    # CUDA FP16 flow can keep its matching FP16 cache resident.
+                     # NPU uses the same schedule with AddLayerNorm and packed QKV.
+                     self._ragged_fused_body = (
+                         flow_parameter.device.type in {"cuda", "npu"}
+                         and supports_fused_body(estimator)
+-                        and self._estimator_att_cache_dtype == torch.float32
++                        and (
++                            self._estimator_att_cache_dtype == torch.float32
++                            or (
++                                flow_parameter.device.type == "cuda"
++                                and self._estimator_att_cache_dtype == torch.float16
++                                and self._estimator_att_compute_dtype == torch.float16
++                            )
++                        )
+                     )
+                     if not self._ragged_fused_body:
+                         logger.warning(
+-                            "cfm_fused_body requested but unsupported here (DiT blocks or a non-fp32 attention cache)"
++                            "cfm_fused_body requested but unsupported here "
++                            "(DiT blocks or incompatible attention cache dtype)"
+                         )
+                 # Resident request caches need the fused body and its tiled
+                 # attention, which reads keys/values out of the pool in place.
+@@ -688,6 +710,11 @@ class BatchedToken2Wav(nn.Module):
+             projected = torch.cat([self._project_speakers(feature.speaker_embedding) for feature in features])
+         return [int(feature.mels.shape[1]) for feature in features], projected
+ 
++    def _cfm_autocast(self, device: torch.device):
++        if self._cfm_only_float16:
++            return torch.amp.autocast(device.type, dtype=torch.float16)
++        return self._autocast(device)
++
+     def _autocast(self, device: torch.device):
+         if device.type != "cuda":
+             return nullcontext()
+@@ -1086,7 +1113,10 @@ class BatchedToken2Wav(nn.Module):
+         ``modulation`` comes from the Whole-Euler arena, for either body.
+         """
+         estimator_input = args[1]
+-        if slots is not None or (self._ragged_fused_body and estimator_input.dtype == torch.float32):
++        fused_dtype = estimator_input.dtype == torch.float32 or (
++            estimator_input.is_cuda and estimator_input.dtype == torch.float16
++        )
++        if slots is not None or (self._ragged_fused_body and fused_dtype):
+             # Slot-pool graphs are only built over the fused body (``slot_pool`` above).
+             if estimator_input.device.type == "npu":
+                 from vllm_omni.platforms.npu.models.minicpmo_fused import (
+@@ -1339,6 +1369,8 @@ class BatchedToken2Wav(nn.Module):
+         cache in the same form, already trimmed by ``att_keep``; the eager
+         path returns it stacked and untrimmed (ragged: per request, untrimmed).
+         """
++        if self._cfm_only_float16:
++            mu, speakers, cond = mu.half(), speakers.half(), cond.half()
+         decoder = self.flow.decoder
+         estimator = decoder.estimator
+         batch_size = int(mu.shape[0])
+@@ -1734,7 +1766,7 @@ class BatchedToken2Wav(nn.Module):
+         wrapper = self._whole_euler_graph_wrapper
+         prompt_len = int(features.mels.shape[1])
+         steady = prompt_len + _CACHE_TRIM_SUFFIX
+-        with self._autocast(wrapper.device):
++        with self._cfm_autocast(wrapper.device):
+             return wrapper.precapture(
+                 offsets=range(prompt_len, steady + 1),
+                 steady=steady,
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+index 3ab3f7f96a..e64fcd2f82 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+@@ -1,6 +1,6 @@
+ # SPDX-License-Identifier: Apache-2.0
+ # SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+-"""Tiled CFM attention: float32 tensors, ordinary TF32 Tensor Core dots."""
++"""Tiled CFM attention with FP32/TF32 or FP16 Tensor Core dots."""
+ 
+ import torch
+ from vllm.triton_utils import tl, triton
+@@ -80,7 +80,7 @@ def _attention(
+             (keys[:, None] < nk) & (ds[None, :] < dim),
+             0,
+         )
+-        accumulator = accumulator * correction[:, None] + tl.dot(prob, values, input_precision="tf32")
++        accumulator = accumulator * correction[:, None] + tl.dot(prob.to(values.dtype), values, input_precision="tf32")
+         maximum = new_max
+     result = accumulator / tl.where(denominator > 0, denominator, 1.0)[:, None]
+     tl.store(
+@@ -98,11 +98,11 @@ def cfm_attention(
+     mask: torch.Tensor | None = None,
+     kv_rows: torch.Tensor | None = None,
+ ) -> torch.Tensor:
+-    """Tiled attention with TF32 dots; optional ``kv_rows`` indexes a pooled K/V cache."""
++    """Tiled attention; optional ``kv_rows`` indexes a pooled K/V cache in place."""
+     b, heads, nq, dim = q.shape
+     nk = k.shape[2]
+-    if q.dtype != torch.float32 or k.dtype != torch.float32 or v.dtype != torch.float32:
+-        raise ValueError("CFM tiled attention requires float32 Q/K/V")
++    if q.dtype not in (torch.float32, torch.float16) or k.dtype != q.dtype or v.dtype != q.dtype:
++        raise ValueError("CFM tiled attention requires matching float32 or float16 Q/K/V")
+     num_stages = 2
+     out = torch.empty((b, nq, heads, dim), device=q.device, dtype=q.dtype)
+     _attention[(b, heads, triton.cdiv(nq, 32))](
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+index 4fdbe44879..6da73488a3 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+@@ -1618,6 +1618,7 @@ class MiniCPMO45Code2Wav(nn.Module):
+             setup_cache_size=self._setup_cache_size,
+             cfm_tf32=tf32_mode != "off",
+             encoder_graph_config=self._encoder_graph_config,
++            cfm_float16=read_bool_flag(extra, "cfm_float16", False),
+         )
+         # Captured by the first forward (the warmup run): under vLLM's weight load a graph held GiBs.
+         self._precapture_pending = read_bool_flag(extra, "cfm_graph_precapture", True)
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
index b3e8f2d95..845b6a9fa 100644
--- a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
@@ -15,6 +15,11 @@
       "source_revision": "d255857c1d1441ba77362da6d4cb628fa5dc47a8",
       "patch": "peer-round2-batch-prompt-setup.patch",
       "status": "Exploratory implementation; not quality/performance qualified"
+    },
+    "cfm-only-fp16": {
+      "source_revision": "4671fdc3736c760f1abd637e30079b3cf65d1fdf",
+      "patch": "peer-round2-cfm-only-fp16.patch",
+      "status": "Exploratory implementation; service/quality screen pending, no qualification"
     }
   },
   "note": "Apply each patch independently to the base. Default behavior remains unchanged unless the corresponding opt-in config is enabled. Do not combine or promote failed candidates as a qualified release."
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-component-profile.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-component-profile.json
new file mode 100644
index 000000000..0e4ea39dc
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-component-profile.json
@@ -0,0 +1,11 @@
+{
+  "scope": "Diagnostic only; no service throughput attribution",
+  "questions": [
+    "How much sequential prompt preparation is spent in S3, CAM++, CPU fbank/mels?",
+    "What are warm graph setup and continuation costs?"
+  ],
+  "cohort": "Four already-used six-second tuning references from setup probe; no holdout",
+  "timing": "CUDA synchronize around nested calls; inclusive wall times; first iteration excluded",
+  "resources": "Prompt diagnostic on own idle ASR reservation with allocator cap4.5%; separate graph setup/decode diagnostic queued on exclusive GPU6 after service screen",
+  "limitations": "Component timings do not equal E2E time; shared-host effects and synchronization remove overlap."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json
new file mode 100644
index 000000000..3b10e5cee
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json
@@ -0,0 +1,14 @@
+{
+  "frozen_at_utc": "2026-10-21T08:03:12.377856+00:00",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "Two Code2Wav processes on the same L20X can overlap host dispatch and GPU work under private MPS, improving high concurrency throughput without changing arithmetic.",
+  "evidence": [
+    "Instrumented stage2 span4.662s versus summed GPU kernels1.879s; instrumentation overhead prevents exact attribution",
+    "Prompt preparation diagnostic25.3ms per unique6s reference; optimizing this alone cannot close~2.8x throughput gap",
+    "Existing same-device stage2 replicas profile, previously validated only on NPU"
+  ],
+  "contrast": "Only stage2 num_replicas=2 and devices=0,0 over round2 Torch+MPS control; all capacities16, FP32, microbatch4, precision, sampling and workload unchanged.",
+  "quality_checks": "Existing orchestrator replica-routing tests and resolved-config assertions before launch; then64 reused tuning requests at C1/C16/C32 with no failed or missing audio and descriptive WER/SIM/UTMOS.",
+  "decision": "If two replicas improve, consider separately frozen four-replica trial after memory/runtime check. No speculative port of multi-frame Talker before bottleneck evidence.",
+  "holdout": "256 untouched; final acceptance still all9 bounds."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json
new file mode 100644
index 000000000..ee759eba2
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json
@@ -0,0 +1,141 @@
+{
+  "scope": "64 reused tuning prompts,discard+one, no acceptance claim",
+  "source_revision": "4671fdc3736c760f1abd637e30079b3cf65d1fdf",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 36.39867671858519,
+      "throughput_frames_s": 189.48491049067138,
+      "ttfa_p50_s": 0.2955524153076112,
+      "ttfa_p95_s": 0.3363649168051779,
+      "rtf_mean": 0.13313264543484726,
+      "rtf_duration_weighted": 0.13175728636401793,
+      "req_s": 1.758305679484264,
+      "audio_s_per_s": 7.579396419626856,
+      "e2e_p50_s": 0.5622728327289224,
+      "e2e_p95_s": 0.7596631528344004,
+      "total_audio_s": 275.88,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.07842191029340029,
+      "inter_chunk_gap_p95_s": 0.0968616978265345,
+      "inter_chunk_gap_max_s": 0.17832952551543713
+    },
+    "16": {
+      "label": "run1",
+      "concurrency": 16,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 8.619633122347295,
+      "throughput_frames_s": 815.4639414729367,
+      "ttfa_p50_s": 1.0946044619195163,
+      "ttfa_p95_s": 1.7680325752589852,
+      "rtf_mean": 0.48096031718797183,
+      "rtf_duration_weighted": 0.47059481056770924,
+      "req_s": 7.424909980689705,
+      "audio_s_per_s": 32.61855765891747,
+      "e2e_p50_s": 2.1340464050881565,
+      "e2e_p95_s": 2.768917794339359,
+      "total_audio_s": 281.16,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.0012143499916419387,
+      "stall_max_s": 0.07771839946508408,
+      "inter_chunk_gap_p50_s": 0.2308251210488379,
+      "inter_chunk_gap_p95_s": 0.5293860946316272,
+      "inter_chunk_gap_max_s": 0.9177183993160725
+    },
+    "32": {
+      "label": "run1",
+      "concurrency": 32,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
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+      "rtf_mean": 0.8840914825624063,
+      "rtf_duration_weighted": 0.8783846390830923,
+      "req_s": 7.905847394179621,
+      "audio_s_per_s": 34.573258885671756,
+      "e2e_p50_s": 3.711105795111507,
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+    }
+  },
+  "quality": "scoring pending"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-graph-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-graph-quality.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-graph-screens.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-graph-screens.json
new file mode 100644
index 000000000..bca5dfeb7
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-graph-screens.json
@@ -0,0 +1,363 @@
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+  "findings": {
+    "cfm_cap": "No gain; both configurations captured31 Whole-Euler graphs, below original32 limit. Capacity hypothesis disconfirmed.",
+    "hift_exact": "Small screening gain at C32, far below peer; no final qualification."
+  },
+  "raw_quality_sha256": "3b851200c1a06c77a99708f8ed787dd1dae0d94fb49b75248bae3ee2913d1b06"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-prompt-components.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-prompt-components.json
new file mode 100644
index 000000000..875a9ed80
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-prompt-components.json
@@ -0,0 +1,519 @@
+{
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+      "prompt_index": 2
+    },
+    {
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+      "seconds": 0.024727752432227135,
+      "repeat": 2,
+      "prompt_index": 3
+    }
+  ],
+  "cuda_peak_bytes": 1319737856,
+  "means_seconds": {
+    "s3_mel": 0.0007617516675963998,
+    "prompt_total": 0.02531451336108148,
+    "speaker_fbank": 0.0011326700914651155,
+    "flow_mel": 0.0016164479311555624,
+    "speaker": 0.012596566462889314,
+    "s3_tokens": 0.005394816282205284,
+    "audio_load": 0.0011318580945953727
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
index 89795b591..6dc765511 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
@@ -234,6 +234,88 @@
         },
         "wer_mean": 0.017342293123543125
       }
+    },
+    "screen-cfm128-batch16": {
+      "1": {
+        "n": 64,
+        "sim": 50.0393023788929,
+        "utmos": 4.211008485406637,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 695
+        },
+        "wer_mean": 0.02427338286713287
+      },
+      "16": {
+        "n": 64,
+        "sim": 50.153171479701996,
+        "utmos": 4.1996395364403725,
+        "wer": 0.026874115983026876,
+        "wer_counts": {
+          "substitutions": 14,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 692
+        },
+        "wer_mean": 0.04063774766899767
+      },
+      "32": {
+        "n": 64,
+        "sim": 50.4722001850605,
+        "utmos": 4.20328688621521,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 10,
+          "deletions": 1,
+          "insertions": 3,
+          "hits": 696
+        },
+        "wer_mean": 0.025154793123543125
+      }
+    },
+    "screen-hift-exact-batch16": {
+      "1": {
+        "n": 64,
+        "sim": 50.03935346007347,
+        "utmos": 4.211022302508354,
+        "wer": 0.019801980198019802,
+        "wer_counts": {
+          "substitutions": 11,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 695
+        },
+        "wer_mean": 0.02427338286713287
+      },
+      "16": {
+        "n": 64,
+        "sim": 50.46239650249481,
+        "utmos": 4.204923328012228,
+        "wer": 0.021216407355021217,
+        "wer_counts": {
+          "substitutions": 10,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 696
+        },
+        "wer_mean": 0.0263567162004662
+      },
+      "32": {
+        "n": 64,
+        "sim": 51.33270111680031,
+        "utmos": 4.210674352943897,
+        "wer": 0.015558698727015558,
+        "wer_counts": {
+          "substitutions": 8,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 698
+        },
+        "wer_mean": 0.018762747668997673
+      }
     }
   }
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
index d8effdff7..6e3fb5e55 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -8,11 +8,13 @@
     "HiFT scoped TF32 implementation and screening",
     "FP32 microbatch16 screening",
     "Prompt setup batching implementation and failed numerical gate",
-    "Independent stage2 profiler"
+    "Independent stage2 profiler",
+    "CFM graph capacity128 negative screen",
+    "HiFT exact batch1/2/4 screen"
   ],
   "active": [
-    "CFM graph capacity128 screening",
-    "HiFT exact batch1/2/4 graph screening"
+    "Selective CFM-only FP16 service/quality screen",
+    "Component timing diagnostic"
   ],
   "reserved_holdout_used": false,
   "quality_margins": {

From 11fa568c3002b8e6319f5af75bcfde3c7849151b Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 16:14:30 +0800
Subject: [PATCH 28/40] Preserve selective precision quality and freeze native
 batching contrast

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |    3 +-
 .../plan/peer-round2-native-coalescing.json   |   22 +
 .../plan/peer-round2-stage2-replicas.json     |    6 +-
 .../peer-round2-cfm-only-fp16-screen.json     |   43 +-
 .../results/peer-round2-components.json       | 1612 +++++++++++++++++
 .../results/peer-round2-screen-artifact.json  |    9 +-
 .../results/peer-round2-screen-quality.json   |   41 +
 ...eer-round2-screen-requests-quality.json.gz |  Bin 374138 -> 502627 bytes
 .../results/peer-round2-status.json           |    7 +-
 9 files changed, 1734 insertions(+), 9 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-components.json

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 496106658..2d875a7b4 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -9,7 +9,8 @@ The requester asked to continue until vLLM-Omni exceeds the source-pinned single
 - [Screening speech quality](results/peer-round2-screen-quality.json), [FP16 dispatch correction](results/peer-round2-dispatch-screen.json), and [FP32 batch-width screen](results/peer-round2-batch16-screen.json). Reused64-prompt screens do not establish final acceptance.
 - [Rejected prompt-setup numerical result](results/peer-round2-setup-numerical.json), [HiFT precision screen](results/peer-round2-screen-hift-tf32-mps.json), and [FP16 residency screen](results/peer-round2-screen-fp16-resident16-mps.json).
 - [Independent operator profile](results/peer-round2-stage2-profile.json) motivates the [completed graph-coverage trials](results/peer-round2-graph-screens.json). Profiled requests are excluded from performance aggregates.
-- [Active selective CFM precision trial](plan/peer-round2-cfm-only-fp16.json), retaining the FP32 encoder; no quality claim until scoring.
+- [Selective CFM precision screen](results/peer-round2-cfm-only-fp16-screen.json): C16/C32 815.5/864.3 frames/s; descriptive quality means within margins, no confidence-bound acceptance.
+- [Same-GPU replica trial](plan/peer-round2-stage2-replicas.json) and [native coalescing contrast](plan/peer-round2-native-coalescing.json) investigate host dispatch and small actual batches without reusing the holdout.
 - [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json
new file mode 100644
index 000000000..cfb1f6396
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json
@@ -0,0 +1,22 @@
+{
+  "frozen_at_utc": "2026-10-21T08:13:37.431694+00:00",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "Bounded native generation input coalescing collects more ready streams per CFM call and amortizes dispatch; increasing microbatch capacity alone did not ensure full batches.",
+  "evidence": [
+    "Stage2 profiler observed small actual HiFT batches despite microbatch16 capacity",
+    "Peer runtime/t2w_worker.py already batches ready windows (target8,max_wait40ms) with first/final exceptions",
+    "Current OmniGenerationScheduler supports bounded coalescing only on native MRV2; older all-stage MRV2 control had capacities8 and no explicit coalescing"
+  ],
+  "contrast": [
+    "Control: FP32 batch16+MPS profile, only stage2 model_runner=v2, capacities16 everywhere; no first-chunk express scheduling",
+    "Candidate: same control plus generation_min_batch_size8,generation_max_wait_ms6,generation_coalescing_policy idle_wait"
+  ],
+  "gates": [
+    "Run existing bounded coalescing scheduler tests",
+    "Resolve both configs and verify V1/V1/V2,capacity16,microbatch16,FP32",
+    "Check runtime coalescing engages rather than ignored fallback",
+    "64 reused tuning C1/C16/C32,discard+one; all failures and quality retained"
+  ],
+  "decision": "Do not combine with replica or precision changes until this contrast is evaluated.",
+  "holdout": "256 reserved IDs remain unused"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json
index 3b10e5cee..0e84e9257 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-stage2-replicas.json
@@ -10,5 +10,9 @@
   "contrast": "Only stage2 num_replicas=2 and devices=0,0 over round2 Torch+MPS control; all capacities16, FP32, microbatch4, precision, sampling and workload unchanged.",
   "quality_checks": "Existing orchestrator replica-routing tests and resolved-config assertions before launch; then64 reused tuning requests at C1/C16/C32 with no failed or missing audio and descriptive WER/SIM/UTMOS.",
   "decision": "If two replicas improve, consider separately frozen four-replica trial after memory/runtime check. No speculative port of multi-frame Talker before bottleneck evidence.",
-  "holdout": "256 untouched; final acceptance still all9 bounds."
+  "holdout": "256 untouched; final acceptance still all9 bounds.",
+  "pre_service_checks": {
+    "replica_routing_tests": "17 passed,111 deselected",
+    "resolved_config": "PASS: capacities16/16/16,stage2 num_replicas2 devices0,0,MPS enabled"
+  }
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json
index ee759eba2..9e68cd27f 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-only-fp16-screen.json
@@ -137,5 +137,46 @@
       "inter_chunk_gap_max_s": 1.2616655249148607
     }
   },
-  "quality": "scoring pending"
+  "quality": {
+    "1": {
+      "n": 64,
+      "sim": 50.12967520952225,
+      "utmos": 4.200052823871374,
+      "wer": 0.018387553041018388,
+      "wer_counts": {
+        "substitutions": 10,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 696
+      },
+      "wer_mean": 0.022971299533799533
+    },
+    "16": {
+      "n": 64,
+      "sim": 50.00295713543892,
+      "utmos": 4.234055019915104,
+      "wer": 0.016973125884016973,
+      "wer_counts": {
+        "substitutions": 7,
+        "deletions": 1,
+        "insertions": 4,
+        "hits": 699
+      },
+      "wer_mean": 0.021929632867132866
+    },
+    "32": {
+      "n": 64,
+      "sim": 51.17965564131737,
+      "utmos": 4.198266837745905,
+      "wer": 0.018387553041018388,
+      "wer_counts": {
+        "substitutions": 9,
+        "deletions": 1,
+        "insertions": 3,
+        "hits": 697
+      },
+      "wer_mean": 0.025254953379953378
+    }
+  },
+  "finding": "All three quality mean degradations inside margins versus tuning Torch+MPS control; descriptive screen only. No paired confidence-bound acceptance. Throughput remains below peer."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-components.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-components.json
new file mode 100644
index 000000000..fe90ce183
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-components.json
@@ -0,0 +1,1612 @@
+{
+  "scope": "Isolated sequential component diagnostic, four reused six-second tuning references, warm iteration excluded; nested synchronized timings are inclusive and not E2E throughput",
+  "rows": [
+    {
+      "component": "audio_load",
+      "seconds": 0.0019761724397540092,
+      "repeat": 0,
+      "prompt_index": 0
+    },
+    {
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+  "limitation": "Component diagnostic uses eager HiFT/encoder unlike service; only the CFM/setup component is graph-enabled. Nested synchronization prevents overlap. Do not infer service throughput from this trace.",
+  "means_seconds": {
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+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
index d82aeb0cf..30c8a9282 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
@@ -1,7 +1,7 @@
 {
-  "scope": "All completed first-round tuning screens; reused data, no final acceptance",
+  "scope": "Completed round-two tuning screens; reused data, no final acceptance",
   "path": "peer-round2-screen-requests-quality.json.gz",
-  "sha256": "bfcae076229b1940285b723bdd2aaebc9c451c60aa5107e553caa103d94e27c5",
+  "sha256": "fbfcb77f77ee1713fe9388ca139ca343555f6dc413fd7963c9c3c33eabbfa1e4",
   "profiles": [
     "screen-torch-mps",
     "screen-capacity32-mps",
@@ -11,7 +11,10 @@
     "screen-fp16-dispatch-mps",
     "screen-fp32-batch16-mps",
     "screen-hift-tf32-mps",
-    "screen-fp16-resident16-mps"
+    "screen-fp16-resident16-mps",
+    "screen-cfm128-batch16",
+    "screen-hift-exact-batch16",
+    "screen-cfm-only-fp16-mps"
   ],
   "privacy": "Audio and ASR hypothesis text are excluded. Audio hashes and error counts remain."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
index 6dc765511..3febd84ca 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
@@ -316,6 +316,47 @@
         },
         "wer_mean": 0.018762747668997673
       }
+    },
+    "screen-cfm-only-fp16-mps": {
+      "1": {
+        "n": 64,
+        "sim": 50.12967520952225,
+        "utmos": 4.200052823871374,
+        "wer": 0.018387553041018388,
+        "wer_counts": {
+          "substitutions": 10,
+          "deletions": 1,
+          "insertions": 2,
+          "hits": 696
+        },
+        "wer_mean": 0.022971299533799533
+      },
+      "16": {
+        "n": 64,
+        "sim": 50.00295713543892,
+        "utmos": 4.234055019915104,
+        "wer": 0.016973125884016973,
+        "wer_counts": {
+          "substitutions": 7,
+          "deletions": 1,
+          "insertions": 4,
+          "hits": 699
+        },
+        "wer_mean": 0.021929632867132866
+      },
+      "32": {
+        "n": 64,
+        "sim": 51.17965564131737,
+        "utmos": 4.198266837745905,
+        "wer": 0.018387553041018388,
+        "wer_counts": {
+          "substitutions": 9,
+          "deletions": 1,
+          "insertions": 3,
+          "hits": 697
+        },
+        "wer_mean": 0.025254953379953378
+      }
     }
   }
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
index 53f525c2c5267f83913bbf6d067a42b4175de982..c25a87ebf7590b8936421a575858617452fe9e86 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
index 6e3fb5e55..03ef87ac5 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -10,11 +10,12 @@
     "Prompt setup batching implementation and failed numerical gate",
     "Independent stage2 profiler",
     "CFM graph capacity128 negative screen",
-    "HiFT exact batch1/2/4 screen"
+    "HiFT exact batch1/2/4 screen",
+    "Selective CFM-only FP16 screen",
+    "Sequential component diagnostic"
   ],
   "active": [
-    "Selective CFM-only FP16 service/quality screen",
-    "Component timing diagnostic"
+    "Same-GPU two Code2Wav replicas screen"
   ],
   "reserved_holdout_used": false,
   "quality_margins": {

From 126c7ead968a361c42595d49ae7037762601187b Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 16:44:29 +0800
Subject: [PATCH 29/40] Record replica scaling and native coalescing regression
 evidence

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   4 +-
 .../patch/peer-round2-manifest.json           |   7 +-
 .../patch/peer-round2-native-coalescing.patch |  61 ++++++
 .../plan/peer-round2-native-coalescing.json   |  27 ++-
 .../peer-round2-native-talker-replicas.json   |  24 +++
 .../peer-round2-native-talker-replicas4.json  |  10 +
 .../plan/peer-round2-setup-control-audit.json |   7 +
 .../plan/peer-round2-speaker-torch-graph.json |  11 +
 .../peer-round2-native-stage2-screen.json     | 162 ++++++++++++++
 ...round2-native-talker-replicas2-screen.json | 203 ++++++++++++++++++
 .../results/peer-round2-replicas2-screen.json | 202 +++++++++++++++++
 .../results/peer-round2-screen-artifact.json  |   7 +-
 .../results/peer-round2-screen-quality.json   |  82 +++++++
 ...eer-round2-screen-requests-quality.json.gz | Bin 502627 -> 617667 bytes
 .../peer-round2-setup-control-audit.json      |  35 +++
 .../results/peer-round2-status.json           |  13 +-
 .../peer_round2_profile_components.py         |  99 +++++++++
 17 files changed, 947 insertions(+), 7 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-native-coalescing.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas4.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-setup-control-audit.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-control-audit.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_profile_components.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 2d875a7b4..d41ffd392 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -10,7 +10,9 @@ The requester asked to continue until vLLM-Omni exceeds the source-pinned single
 - [Rejected prompt-setup numerical result](results/peer-round2-setup-numerical.json), [HiFT precision screen](results/peer-round2-screen-hift-tf32-mps.json), and [FP16 residency screen](results/peer-round2-screen-fp16-resident16-mps.json).
 - [Independent operator profile](results/peer-round2-stage2-profile.json) motivates the [completed graph-coverage trials](results/peer-round2-graph-screens.json). Profiled requests are excluded from performance aggregates.
 - [Selective CFM precision screen](results/peer-round2-cfm-only-fp16-screen.json): C16/C32 815.5/864.3 frames/s; descriptive quality means within margins, no confidence-bound acceptance.
-- [Same-GPU replica trial](plan/peer-round2-stage2-replicas.json) and [native coalescing contrast](plan/peer-round2-native-coalescing.json) investigate host dispatch and small actual batches without reusing the holdout.
+- [Two same-GPU replicas](results/peer-round2-replicas2-screen.json): C16/C32 973.1/1057.4 frames/s; descriptive quality means within margins. [Native Talker plus two replicas](results/peer-round2-native-talker-replicas2-screen.json): 1053.7/1172.1 frames/s, but C32 SIM mean drops1.76, exceeding the0.50 margin. Neither is a qualified peer win.
+- [Native stage2 control](results/peer-round2-native-stage2-screen.json) reaches C32 898.2 frames/s. The [coalescing contrast](plan/peer-round2-native-coalescing.json) initially failed startup; its minimal constructor fix passes104 scheduler tests and is queued for a fresh service retry.
+- [Prompt-setup A/A audit](results/peer-round2-setup-control-audit.json) confirms the numerical rejection; the [speaker Torch graph probe](plan/peer-round2-speaker-torch-graph.json) and [four-replica scaling diagnostic](plan/peer-round2-native-talker-replicas4.json) remain exploratory.
 - [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
index 845b6a9fa..d981d177e 100644
--- a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
@@ -19,7 +19,12 @@
     "cfm-only-fp16": {
       "source_revision": "4671fdc3736c760f1abd637e30079b3cf65d1fdf",
       "patch": "peer-round2-cfm-only-fp16.patch",
-      "status": "Exploratory implementation; service/quality screen pending, no qualification"
+      "status": "Screen completed, no peer win; descriptive quality means within margins, no final qualification"
+    },
+    "native-coalescing": {
+      "source_revision": "e9b12cf223b4a3900f6f30772065eb058550319a",
+      "patch": "peer-round2-native-coalescing.patch",
+      "status": "Regression before FAIL, after104 tests PASS and pre-commit PASS; service retry queued"
     }
   },
   "note": "Apply each patch independently to the base. Default behavior remains unchanged unless the corresponding opt-in config is enabled. Do not combine or promote failed candidates as a qualified release."
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-native-coalescing.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-native-coalescing.patch
new file mode 100644
index 000000000..05da193a3
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-native-coalescing.patch
@@ -0,0 +1,61 @@
+diff --git a/tests/core/sched/test_generation_scheduler_init.py b/tests/core/sched/test_generation_scheduler_init.py
+index 303a050683..bdfd575fd8 100644
+--- a/tests/core/sched/test_generation_scheduler_init.py
++++ b/tests/core/sched/test_generation_scheduler_init.py
+@@ -80,12 +80,32 @@ def test_moss_profile_generation_constructor_after_platform_resolution(
+         warning.assert_called_once()
+ 
+ 
+-@pytest.mark.parametrize("stateful,tp,pp", [(False, 1, 1), (True, 2, 1), (True, 1, 2)])
+-def test_native_batch_waiting_still_rejects_unsupported_state_or_topology(construct_scheduler, stateful, tp, pp):
++def test_minicpm_native_batch_waiting_preserves_chunk_owned_slots(construct_scheduler, monkeypatch):
++    monkeypatch.setattr(current_omni_platform, "device_name", "cuda")
++    deploy = load_deploy_config(get_deploy_config_path("minicpmo_4_5_turn_mrv2.yaml"))
++    pipeline = resolve_pipeline_config("minicpmo_4_5")
++    codec = merge_pipeline_deploy(pipeline, deploy)[2]
++    scheduler = construct_scheduler(
++        _config(
++            native=codec.yaml_engine_args["use_v2_model_runner"],
++            stateful=pipeline.stages[2].retains_state_across_chunks,
++            capacity=codec.yaml_engine_args["max_num_seqs"],
++            extras={"generation_min_batch_size": 4, "generation_max_wait_ms": 12},
++        )
++    )
++    assert scheduler._native_data_plane
++    assert not scheduler._retains_state_across_chunks
++    assert scheduler._generation_min_batch_size == 4
++    assert scheduler._generation_max_wait_s == 0.012
++
++
++@pytest.mark.parametrize("stateful", [False, True])
++@pytest.mark.parametrize("tp,pp", [(2, 1), (1, 2)])
++def test_native_batch_waiting_still_rejects_unsupported_topology(construct_scheduler, stateful, tp, pp):
+     config = _config(
+         stateful=stateful, tp=tp, pp=pp, extras={"generation_min_batch_size": 32, "generation_max_wait_ms": 12}
+     )
+-    with pytest.raises(ValueError, match="stateful native MRV2 TP1/PP1"):
++    with pytest.raises(ValueError, match="native MRV2 TP1/PP1"):
+         construct_scheduler(config)
+ 
+ 
+diff --git a/vllm_omni/core/sched/omni_generation_scheduler.py b/vllm_omni/core/sched/omni_generation_scheduler.py
+index 5242daaeed..18d91126a4 100644
+--- a/vllm_omni/core/sched/omni_generation_scheduler.py
++++ b/vllm_omni/core/sched/omni_generation_scheduler.py
+@@ -90,12 +90,11 @@ class OmniGenerationScheduler(OmniSchedulerMixin, VLLMScheduler):
+                 self._generation_min_batch_size = 1
+                 self._generation_max_wait_s = 0.0
+                 self._generation_max_regular_batch = 0
+-            elif not (
+-                self._retains_state_across_chunks
+-                and parallel.tensor_parallel_size == parallel.pipeline_parallel_size == 1
+-            ):
+-                raise ValueError("Generation batch waiting requires a stateful native MRV2 TP1/PP1 stage")
++            elif not (parallel.tensor_parallel_size == parallel.pipeline_parallel_size == 1):
++                raise ValueError("Generation batch waiting requires a native MRV2 TP1/PP1 stage")
+             else:
++                # Coalescing counts ready requests before slot allocation and
++                # does not require slots to remain assigned between chunks.
+                 logger.info(
+                     "Generation input coalescing: target batch=%d, max wait=%.3f ms",
+                     self._generation_min_batch_size,
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json
index cfb1f6396..43163c0ad 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-coalescing.json
@@ -18,5 +18,30 @@
     "64 reused tuning C1/C16/C32,discard+one; all failures and quality retained"
   ],
   "decision": "Do not combine with replica or precision changes until this contrast is evaluated.",
-  "holdout": "256 reserved IDs remain unused"
+  "holdout": "256 reserved IDs remain unused",
+  "pre_service_checks": {
+    "bounded_coalescing_and_initialization_tests": "42 passed",
+    "resolved_configs": "PASS for V1/V1/V2,16/16/16 capacities,MPS in both profiles"
+  },
+  "initial_service_outcome": {
+    "control_fps": {
+      "1": 186.9,
+      "16": 774.6,
+      "32": 898.2
+    },
+    "candidate": "Startup failed before requests: constructor restricts batch waiting to retains_state_across_chunks=true, while MiniCPM intentionally has chunk-owned runner slots.",
+    "next_change": "Remove only fixed-slot retention prerequisite; retain native data-plane and TP1/PP1 constraints. Readiness coalescing precedes allocation and does not access model slot state. Do not change MiniCPM lifetime/admission flag.",
+    "regression": "Real MiniCPM pipeline constructor with coalescing must succeed with retains_state_across_chunks=false; existing lifecycle, bounded wait, control progress and distributed rejection tests must pass.",
+    "control_equivalence": "The changed guard is entered only when coalescing is configured. Disabled control behavior remains unchanged."
+  },
+  "retry": {
+    "source_revision": "e9b12cf223b4a3900f6f30772065eb058550319a",
+    "regression_before": "1 failed at original state retention guard",
+    "regression_after": "104 passed",
+    "pre_commit": "All applicable hooks passed",
+    "change": "Remove fixed-slot-retention prerequisite only; native TP1/PP1 constraints retained.",
+    "retry_frozen_at_utc": "2026-10-21T08:42:49.209878+00:00",
+    "control_runtime": "Previously completed control uses identical disabled-coalescing path.",
+    "log_policy": "Initial attempt3 failure preserved; retry uses distinct attempt4 server log."
+  }
 }
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas.json
new file mode 100644
index 000000000..65ba23307
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas.json
@@ -0,0 +1,24 @@
+{
+  "frozen_at_utc": "2026-10-21T08:22:39.262064+00:00",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "After two same-GPU Code2Wav replicas improve C16/C32 only32%/25%, native MRV2 Talker can remove per-frame host state/sampling transfers and raise the next pipeline ceiling.",
+  "evidence": [
+    "Two replicas screen C16=973.1,C32=1057.4 versus739.6/848.8 single replica",
+    "C32 request stage1 completion often precedes end by only0.2-0.7s; these intervals include queueing and are not pure model runtime",
+    "Existing MRV2 Talker keeps codec samples,16-frame penalties and EOS state on device; older all-stage MRV2 tests used8-slot stages and single Code2Wav without MPS"
+  ],
+  "contrast": "Only stage1 model_runner=v2 over measured two-Code2Wav-replica FP32/MPS configuration on same GPU0; capacities16 and microbatch4 retained.",
+  "checks": "Existing Talker MRV2 CPU+CUDA semantic tests and resolved V1/V2/V1 config before service; canonical64 reused tuning C1/C16/C32 then native quality scoring.",
+  "constraints": "No multi-frame speculative port, precision/sampling parameters unchanged.256 holdout unused.",
+  "pre_service_attempt1": {
+    "cpu_semantics": "34 passed",
+    "cuda_test": "Failed before sampler construction: flashinfer-python0.7.0.post1 versus flashinfer-cubin0.6.13",
+    "service_policy": "Pinned stage_engine_core_proc.py:248 already sets FLASHINFER_DISABLE_VERSION_CHECK=1 for every measured worker. The standalone pytest process did not run that initialization.",
+    "retry": "Mirror the existing worker environment in standalone CUDA test; retain strict numerical assertion and original dependency versions. This is not a quality-gate relaxation or a change to benchmark worker behavior."
+  },
+  "pre_service_attempt2": {
+    "environment": "Mirrors existing measured worker version-check setting",
+    "cpu_and_cuda_semantic_tests": "35 passed",
+    "resolved_config": "V1/V2/V1, capacities16, twoCode2Wav replicas onGPU0"
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas4.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas4.json
new file mode 100644
index 000000000..570601bd1
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-native-talker-replicas4.json
@@ -0,0 +1,10 @@
+{
+  "frozen_at_utc": "2026-10-21T08:40:45.745633+00:00",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "Four same-GPU Code2Wav replicas can further overlap host dispatch after native Talker plus two replicas reaches C16/C32 1053.7/1172.1 fps.",
+  "contrast": "Only Code2Wav replica count2 to4 on native Talker FP32 MPS profile; capacities16 and microbatch4 unchanged.",
+  "protocol": "64 reused tuning prompts,C1/C16/C32,discard+one; native quality scoring; exploratory cross-card evidence requires final paired same-card confirmation.",
+  "risks": "Additional graph and model memory; startup may fail within shared-card budgets. Preserve failure rather than change settings during run.",
+  "holdout": "256 reserved prompts untouched",
+  "goal_achieved": false
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-setup-control-audit.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-setup-control-audit.json
new file mode 100644
index 000000000..4d05801f2
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-setup-control-audit.json
@@ -0,0 +1,7 @@
+{
+  "frozen_at_utc": "2026-10-21T08:27:47.230224+00:00",
+  "question": "Does the failed setup waveform probe have a stable identical-state A/A control? If yes, locate divergence at continuation mel or HiFT source.",
+  "source_revision": "d255857c1d1441ba77362da6d4cb628fa5dc47a8",
+  "protocol": "Same four normalized tuning references and fixed model/noise. Deep-copy reference state for two identical A decodes, reset torch seed before every A/A/B decode, capture exact continuation mel before HiFT. No service benchmarking.",
+  "decision": "Preserve original FAIL and0.01 gate. This diagnostic does not relax it, promote batching, or touch holdout."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json
new file mode 100644
index 000000000..514e59932
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json
@@ -0,0 +1,11 @@
+{
+  "frozen_at_utc": "2026-10-21T08:30:22.792301+00:00",
+  "base_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "hypothesis": "Capture the existing Torch CAM++ forward in an exact-shape CUDA graph to eliminate repeated host launches; keep weights, operators and precision unchanged.",
+  "evidence": "Independent prompt component diagnostic: CAM++12.6ms of total25.3ms. This cannot alone close the throughput gap but may compose with pipeline improvements.",
+  "difference_from_prior_TRT_failure": "No ONNX/TensorRT conversion or operator fusion. Replay exactly the current Torch graph, keyed by shape and CUDA precision flags.",
+  "scope": "New default-off speaker graph option. Bounded graph cache, eager fallback for unsupported input/policy, owned outputs protect cached embeddings from later replays.",
+  "correctness_gate": "Bitwise equality against the same eager Torch model on real reused reference features; graph output ownership, shape fallback and precision-policy separation tests. No service trial if numerical gate fails.",
+  "performance_gate": "Measure warmed component latency first; service trial only after material component improvement.",
+  "quality_contract": "All final speech noninferiority gates unchanged;256 holdout unused."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json
new file mode 100644
index 000000000..afffe43c5
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json
@@ -0,0 +1,162 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      1,
+      1
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v2"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP32 CFM/HiFT, existing CFM TF32 policy"
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 36.91194396652281,
+      "throughput_frames_s": 186.8500885852887,
+      "ttfa_p50_s": 0.34102370170876384,
+      "ttfa_p95_s": 0.3702869470231235,
+      "rtf_mean": 0.13500075199140116,
+      "rtf_duration_weighted": 0.13361556998798232,
+      "req_s": 1.7338561214235866,
+      "audio_s_per_s": 7.4740035434115475,
+      "e2e_p50_s": 0.5853609102778137,
+      "e2e_p95_s": 0.7776444375049323,
+      "total_audio_s": 275.88,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.07618499267846346,
+      "inter_chunk_gap_p95_s": 0.09838482048362493,
+      "inter_chunk_gap_max_s": 0.12528698984533548
+    },
+    "16": {
+      "label": "run1",
+      "concurrency": 16,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 9.01857172884047,
+      "throughput_frames_s": 774.6237663841478,
+      "ttfa_p50_s": 1.4052033983170986,
+      "ttfa_p95_s": 2.3726882295217364,
+      "rtf_mean": 0.5269153729963709,
+      "rtf_duration_weighted": 0.509957118603624,
+      "req_s": 7.0964673702527135,
+      "audio_s_per_s": 30.98495065536591,
+      "e2e_p50_s": 2.0994219933636487,
+      "e2e_p95_s": 3.0082252131775022,
+      "total_audio_s": 279.44,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.012089480718714185,
+      "stall_max_s": 0.5758310919627547,
+      "inter_chunk_gap_p50_s": 0.14265686832368374,
+      "inter_chunk_gap_p95_s": 0.666555741801858,
+      "inter_chunk_gap_max_s": 1.4158310918137431
+    },
+    "32": {
+      "label": "run1",
+      "concurrency": 32,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 7.716920638456941,
+      "throughput_frames_s": 898.1561849242897,
+      "ttfa_p50_s": 1.3668728163465858,
+      "ttfa_p95_s": 3.43140716701746,
+      "rtf_mean": 0.8424855932476811,
+      "rtf_duration_weighted": 0.8417621972795848,
+      "req_s": 8.293463545686704,
+      "audio_s_per_s": 35.92624739697159,
+      "e2e_p50_s": 3.449237345252186,
+      "e2e_p95_s": 6.475283224647863,
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json
new file mode 100644
index 000000000..331d9c445
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json
@@ -0,0 +1,203 @@
+{
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+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "quality_finding": "C32 SIM mean49.2423 versus Torch/MPS control51.0028: decline1.7605 exceeds0.50 margin. Not a qualified candidate; C1/C16 means improved. Four-replica trial retained only as scaling diagnostic."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json
new file mode 100644
index 000000000..37c03b3f5
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json
@@ -0,0 +1,202 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
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+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
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+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
index 30c8a9282..1a0bfcd07 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
@@ -1,7 +1,7 @@
 {
   "scope": "Completed round-two tuning screens; reused data, no final acceptance",
   "path": "peer-round2-screen-requests-quality.json.gz",
-  "sha256": "fbfcb77f77ee1713fe9388ca139ca343555f6dc413fd7963c9c3c33eabbfa1e4",
+  "sha256": "8d74094d629566caf708ea6336c33647cd1b39dfeaf73f60e7946713cd15a116",
   "profiles": [
     "screen-torch-mps",
     "screen-capacity32-mps",
@@ -14,7 +14,10 @@
     "screen-fp16-resident16-mps",
     "screen-cfm128-batch16",
     "screen-hift-exact-batch16",
-    "screen-cfm-only-fp16-mps"
+    "screen-cfm-only-fp16-mps",
+    "screen-stage2-replicas2",
+    "screen-native-talker-replicas2",
+    "screen-native-stage2-batch16"
   ],
   "privacy": "Audio and ASR hypothesis text are excluded. Audio hashes and error counts remain."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
index 3febd84ca..6e9d74cd0 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
@@ -357,6 +357,88 @@
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 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
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z?d{;m<!<DM_A0|PMKV7@J){hNt~BR+ABrkJ(YDvO^B;AVa9o<g7xSmM>sfTewgDbe
zyaXwubQ^y?cgUL!<VtjH_0b%BtbUNb<96&s>XM74ZLZ>jMCHIYmGuA)_=<Y=fqZjD
zA~aP#-l<zK*}}Igz5Chta|u+Y46kUq2L(#f4gG;`xjceAp}vb*!mbJ{wlcx1lcuO_
z(4W$NrJMaOs0?zJo&kC(-N^)$0MR)zNO&DoW~P4`do)eixcR97M=vSZ#u<9+F6UO3
zWVUT9O8d(x^w|<KTxl^-b6<h7uNeNYAC<&;beEqOEgZ{i93aO7%JewWJPnlrxRGRy
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u?T$81eO>;8DpP-zNc_K4nS4i;iJTNx9cS83^lSNpAAbT2r&Amuv?2hq+)M@l

diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-control-audit.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-control-audit.json
new file mode 100644
index 000000000..3fc9eeae5
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-setup-control-audit.json
@@ -0,0 +1,35 @@
+{
+  "scope": "Identical-state A/A control and A/B diagnostic only; prior waveform gate remains unchanged",
+  "rows": [
+    {
+      "prompt_index": 0,
+      "aa_audio_l2": 4.089455956091115e-07,
+      "aa_mel_l2": 0.0,
+      "ab_audio_l2": 0.10460823029279709,
+      "ab_mel_l2": 8.788213017396629e-05
+    },
+    {
+      "prompt_index": 1,
+      "aa_audio_l2": 3.6402414593794674e-07,
+      "aa_mel_l2": 0.0,
+      "ab_audio_l2": 0.01225988008081913,
+      "ab_mel_l2": 9.224325185641646e-05
+    },
+    {
+      "prompt_index": 2,
+      "aa_audio_l2": 9.018204423227871e-07,
+      "aa_mel_l2": 0.0,
+      "ab_audio_l2": 0.011363813653588295,
+      "ab_mel_l2": 0.00010425836080685258
+    },
+    {
+      "prompt_index": 3,
+      "aa_audio_l2": 1.195786921925901e-06,
+      "aa_mel_l2": 0.0,
+      "ab_audio_l2": 0.04626587778329849,
+      "ab_mel_l2": 8.516170782968402e-05
+    }
+  ],
+  "verdict": "FAIL: A/A mel exact and waveform near1e-6, but A/B waveform still exceeds0.01. Original setup failure remains unchanged.",
+  "limitations": "Model construction random noise was not seeded in either probe; cross-run magnitudes are not directly comparable. Within each A/A/B comparison the model and its noise buffers are fixed."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
index 03ef87ac5..97eba3365 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -12,10 +12,19 @@
     "CFM graph capacity128 negative screen",
     "HiFT exact batch1/2/4 screen",
     "Selective CFM-only FP16 screen",
-    "Sequential component diagnostic"
+    "Sequential component diagnostic",
+    "Same-GPU two Code2Wav replicas throughput screen",
+    "Two-replica speech quality screen",
+    "Native Talker with two replicas throughput screen",
+    "Native stage2 no-coalescing control",
+    "Setup numerical A/A audit confirms prior FAIL",
+    "Native coalescing constructor fix,104 tests and pre-commit PASS"
   ],
   "active": [
-    "Same-GPU two Code2Wav replicas screen"
+    "Native Talker two-replica quality scoring",
+    "Native coalescing service retry queued",
+    "Native Talker four-replica service queued",
+    "Torch speaker graph exactness probe queued"
   ],
   "reserved_holdout_used": false,
   "quality_margins": {
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_profile_components.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_profile_components.py
new file mode 100644
index 000000000..0de804087
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_profile_components.py
@@ -0,0 +1,99 @@
+import argparse
+import functools
+import json
+import time
+from pathlib import Path
+
+import torch
+import vllm_omni.model_executor.models.step_audio2.step_audio2_token2wav as core_module
+from vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav import BatchedToken2Wav
+from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_token2wav import MiniCPMO45Token2wav
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--model", type=Path, required=True)
+parser.add_argument(
+    "--prompts",
+    type=Path,
+    required=True,
+    help="Directory containing the four normalized six-second tuning WAVs from the setup probe",
+)
+parser.add_argument("--out", type=Path, required=True)
+args = parser.parse_args()
+args.out.parent.mkdir(parents=True, exist_ok=True)
+torch.set_num_threads(4)
+torch.backends.cudnn.allow_tf32 = False
+torch.backends.cuda.matmul.allow_tf32 = True
+model = MiniCPMO45Token2wav(
+    str(args.model / "assets/token2wav"), device="cuda", drop_upstream_chunk_att_buffers=True
+)
+model.enable_device_spk_embedding(use_trt=False)
+backend = BatchedToken2Wav(
+    model,
+    setup_cache_size=0,
+    cfm_tf32=True,
+    connector_config={"codec_chunk_frames": 25, "codec_left_context_frames": 3},
+    cfm_graph_config={
+        "enabled": True,
+        "fused_body": True,
+        "micro_batch_size": 4,
+        "max_graph_batch": 32,
+        "max_graphs": 32,
+        "offset_bucket_frames": 50,
+    },
+)
+records = []
+
+
+def wrap(obj, name, label):
+    original = getattr(obj, name)
+
+    @functools.wraps(original)
+    def measured(*args, **kwargs):
+        torch.cuda.synchronize()
+        start = time.perf_counter()
+        result = original(*args, **kwargs)
+        torch.cuda.synchronize()
+        records.append({"component": label, "seconds": time.perf_counter() - start})
+        return result
+
+    setattr(obj, name, measured)
+
+
+wrap(model._core.audio_tokenizer, "quantize", "s3_tokens")
+wrap(model._core, "_forward_spk_embedding", "speaker")
+wrap(core_module, "load_audio", "audio_load")
+wrap(core_module.s3tokenizer, "log_mel_spectrogram", "s3_mel")
+wrap(core_module.kaldi, "fbank", "speaker_fbank")
+wrap(core_module, "mel_spectrogram", "flow_mel")
+wrap(model._core, "_prepare_prompt", "prompt_total")
+wrap(backend, "setup_batch", "setup_total")
+wrap(backend, "_decode_cfm", "cfm_total")
+wrap(backend, "_encode_chunk_eager", "encoder_eager")
+wrap(backend, "decode_batch", "decode_total")
+paths = sorted(args.prompts.glob("*.wav"))
+assert len(paths) == 4
+with torch.inference_mode():
+    for repeat in range(3):
+        for i, p in enumerate(paths):
+            before = len(records)
+            f = backend.prepare_prompt(f"{repeat}-{i}", str(p))
+            state = backend.setup_batch(f, 1)[0]
+            tokens = f.speech_tokens[:, :28].contiguous()
+            for step in range(4):
+                audio, states = backend.decode_batch(tokens, f, [state], last_chunk=step == 3)
+                state = states[0]
+            for row in records[before:]:
+                row.update(repeat=repeat, prompt_index=i)
+            print("DONE", repeat, i, flush=True)
+result = {
+    "scope": (
+        "Four reused tuning references; CFM graphs enabled, HiFT/encoder eager. "
+        "Inclusive synchronized timings; first iteration excluded, not service throughput"
+    ),
+    "rows": records,
+    "cuda_peak_bytes": torch.cuda.max_memory_allocated(),
+}
+args.out.write_text(json.dumps(result, indent=2) + "\n")
+for k in sorted({x["component"] for x in records}):
+    vals = [x["seconds"] for x in records if x["component"] == k and x["repeat"] > 0]
+    print(k, len(vals), sum(vals) / len(vals), flush=True)

From e6e606803551eb1200ba4bb7f3919f6f1a191831 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 17:03:17 +0800
Subject: [PATCH 30/40] Preserve coalescing result and exact speaker graph
 implementation

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   6 +-
 .../peer-round2-cfm-speaker-composition.patch | 561 ++++++++++++++++++
 .../patch/peer-round2-manifest.json           |  12 +-
 .../peer-round2-speaker-torch-graph.patch     | 225 +++++++
 .../peer-round2-cfm-speaker-composition.json  |  21 +
 .../plan/peer-round2-peer-tuning64.json       |  14 +
 .../plan/peer-round2-pipeline-replicas.json   |  56 ++
 .../plan/peer-round2-speaker-torch-graph.json |  12 +-
 .../peer-round2-native-coalescing-screen.json | 168 ++++++
 ...round2-native-talker-replicas2-screen.json |  24 +-
 ...round2-native-talker-replicas4-screen.json | 162 +++++
 .../results/peer-round2-replicas2-screen.json |  24 +-
 .../results/peer-round2-screen-artifact.json  |   6 +-
 ...eer-round2-screen-requests-quality.json.gz | Bin 617667 -> 674426 bytes
 .../peer-round2-speaker-graph-probe.json      |  56 ++
 ...er-round2-speaker-graph-wrapper-probe.json |  56 ++
 .../results/peer-round2-status.json           |  15 +-
 .../validator/peer_round2_speaker_graph.py    |  82 +++
 18 files changed, 1487 insertions(+), 13 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-speaker-composition.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-speaker-torch-graph.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-peer-tuning64.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-replicas.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-probe.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-wrapper-probe.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_speaker_graph.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index d41ffd392..4b6e11d9b 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -11,8 +11,10 @@ The requester asked to continue until vLLM-Omni exceeds the source-pinned single
 - [Independent operator profile](results/peer-round2-stage2-profile.json) motivates the [completed graph-coverage trials](results/peer-round2-graph-screens.json). Profiled requests are excluded from performance aggregates.
 - [Selective CFM precision screen](results/peer-round2-cfm-only-fp16-screen.json): C16/C32 815.5/864.3 frames/s; descriptive quality means within margins, no confidence-bound acceptance.
 - [Two same-GPU replicas](results/peer-round2-replicas2-screen.json): C16/C32 973.1/1057.4 frames/s; descriptive quality means within margins. [Native Talker plus two replicas](results/peer-round2-native-talker-replicas2-screen.json): 1053.7/1172.1 frames/s, but C32 SIM mean drops1.76, exceeding the0.50 margin. Neither is a qualified peer win.
-- [Native stage2 control](results/peer-round2-native-stage2-screen.json) reaches C32 898.2 frames/s. The [coalescing contrast](plan/peer-round2-native-coalescing.json) initially failed startup; its minimal constructor fix passes104 scheduler tests and is queued for a fresh service retry.
-- [Prompt-setup A/A audit](results/peer-round2-setup-control-audit.json) confirms the numerical rejection; the [speaker Torch graph probe](plan/peer-round2-speaker-torch-graph.json) and [four-replica scaling diagnostic](plan/peer-round2-native-talker-replicas4.json) remain exploratory.
+- [Native stage2 control](results/peer-round2-native-stage2-screen.json) reaches C32 898.2 frames/s. The [coalescing contrast](results/peer-round2-native-coalescing-screen.json) initially failed startup; its constructor fix passes104 scheduler tests. The successful retry reaches C16/C32 773.9/904.8, with no material throughput gain.
+- [Prompt-setup A/A audit](results/peer-round2-setup-control-audit.json) confirms the numerical rejection; the [four-replica scaling diagnostic](results/peer-round2-native-talker-replicas4-screen.json) reaches C32 1332.4, with quality pending.
+- [Exact Torch speaker graph](results/peer-round2-speaker-graph-wrapper-probe.json): four real references are bitwise equal; component latency falls from about11.4 to4.9ms. Output ownership, shape capacity, policy fallback, and backend integration checks pass. [Service and composition trials](plan/peer-round2-cfm-speaker-composition.json) remain unqualified.
+- [Matched peer tuning workload](plan/peer-round2-peer-tuning64.json) supplements the unchanged320-request repeated baseline; cross-cohort screening ratios are not final comparisons.
 - [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-speaker-composition.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-speaker-composition.patch
new file mode 100644
index 000000000..08b28ac08
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-cfm-speaker-composition.patch
@@ -0,0 +1,561 @@
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+new file mode 100644
+index 0000000000..39c416ddaf
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+@@ -0,0 +1,57 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Tiled attention must preserve masking and pooled-row ownership in FP16."""
++
++import pytest
++import torch
++import torch.nn.functional as F
++from torch.nn.attention import SDPBackend, sdpa_kernel
++
++from tests.helpers.mark import hardware_marks
++from vllm_omni.model_executor.models.minicpmo_4_5.cfm_attention import cfm_attention
++
++pytestmark = [pytest.mark.core_model, *hardware_marks(res={"cuda": "L4"}, num_cards=1)]
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++@pytest.mark.parametrize("pooled", [False, True])
++@pytest.mark.parametrize("masked", [False, True])
++@pytest.mark.parametrize("frames,history", [(1, 17), (23, 65), (50, 513)])
++def test_tiled_attention_matches_math_sdpa(dtype, pooled, masked, frames, history):
++    generator = torch.Generator(device="cuda").manual_seed(43)
++    batch, heads, width = 3, 4, 64
++    q = torch.randn(batch, heads, frames, width, device="cuda", dtype=dtype, generator=generator)
++    # K and V are interleaved in the real resident pool, so both views are strided.
++    storage = torch.randn(
++        7 if pooled else batch, heads, history, 2 * width, device="cuda", dtype=dtype, generator=generator
++    )
++    k, v = storage[..., :width], storage[..., width:]
++    rows = torch.tensor([5, 1, 5], device="cuda") if pooled else None
++    mask = None
++    if masked:
++        mask = torch.rand(batch, frames, history, device="cuda", generator=generator) > 0.3
++        mask[0, 0] = False
++    expected_k = k.index_select(0, rows) if pooled else k
++    expected_v = v.index_select(0, rows) if pooled else v
++    with sdpa_kernel(SDPBackend.MATH):
++        expected = F.scaled_dot_product_attention(
++            q.float(),
++            expected_k.float(),
++            expected_v.float(),
++            attn_mask=mask.unsqueeze(1) if mask is not None else None,
++        ).to(dtype)
++    actual = cfm_attention(q, k, v, mask, rows)
++    torch.testing.assert_close(actual, expected, atol=2e-3, rtol=2e-3)
++    assert torch.isfinite(actual).all()
++    if masked:
++        assert torch.count_nonzero(actual[0, :, 0]) == 0
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++def test_tiled_attention_rejects_mixed_cache_dtype(dtype):
++    q = torch.empty(1, 1, 1, 16, dtype=dtype)
++    cache_dtype = torch.float16 if dtype == torch.float32 else torch.float32
++    k = torch.empty_like(q, dtype=cache_dtype)
++    with pytest.raises(ValueError, match="matching float32 or float16"):
++        cfm_attention(q, k, k)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+index 8a6b81a8fc..5db1e06a76 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+@@ -37,11 +37,15 @@ class _FakeToken2Wav:
+         self.device_spk_calls = 0
+         self.trt_spk_calls = 0
+         self.device_spk_use_trt = None
++        self.speaker_graph_config = None
+ 
+     def enable_device_spk_embedding(self, *, use_trt=True):
+         self.device_spk_calls += 1
+         self.device_spk_use_trt = use_trt
+ 
++    def enable_speaker_cuda_graph(self, config):
++        self.speaker_graph_config = config
++
+     def enable_trt_spk_embedding(self, *, cpu_reference=False):
+         self.trt_spk_calls += 1
+         self.trt_cpu_reference = cpu_reference
+@@ -150,6 +154,7 @@ def test_cuda_speaker_backend_preserves_lazy_model_loading(tmp_path, monkeypatch
+ 
+ 
+ _OTHER_DEFAULTS = {
++    "token2wav_spk_cuda_graph",
+     "token2wav_spk_cpu_reference",
+     "token2wav_float16",
+     "token2wav_trt",
+@@ -295,3 +300,12 @@ def test_facade_forwards_speaker_reference_policy(mocker, cpu_reference):
+     facade._core = core
+     facade.enable_trt_spk_embedding(cpu_reference=cpu_reference)
+     core.enable_trt_spk_embedding.assert_called_once_with(cpu_reference=cpu_reference)
++
++
++@pytest.mark.parametrize("value,enabled", [(True, True), ("true", True), (False, False), ("false", False)])
++def test_speaker_graph_flag_reaches_selected_backend(tmp_path, monkeypatch, value, enabled):
++    monkeypatch.setattr(current_omni_platform, "is_cuda", lambda: True)
++    monkeypatch.setattr(current_omni_platform, "is_npu", lambda: False)
++    model, speaker = _build_backend(tmp_path, monkeypatch, {"token2wav_spk_cuda_graph": value})
++    assert speaker.device_spk_calls == 1
++    assert speaker.speaker_graph_config is (model.vllm_config if enabled else None)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+index 3cf8bdd941..e40424b57c 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+@@ -44,14 +44,17 @@ def _run(body, estimator, *, rows: int, frames: int, cached: int, lengths):
+     channels = estimator.blocks[0].conv.block[1].in_channels
+     attn = estimator.blocks[0].attn
+     device = next(estimator.parameters()).device
+-    estimator_input = torch.randn(rows, 320, frames, device=device)
+-    time_embedding = estimator.t_embedder(torch.rand((), device=device).expand(rows)).unsqueeze(1)
++    dtype = next(estimator.parameters()).dtype
++    estimator_input = torch.randn(rows, 320, frames, device=device, dtype=dtype)
++    time_embedding = estimator.t_embedder(torch.rand((), device=device, dtype=dtype).expand(rows)).unsqueeze(1)
+     mask = torch.rand(rows, frames, cached + frames, device=device) > 0.3
+     mask[..., 0] = True
+-    cnn = [torch.randn(rows, 2 * channels, 2, device=device) for _ in range(depth)]
+-    att = [torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device) for _ in range(depth)]
+-    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device)
+-    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device)
++    cnn = [torch.randn(rows, 2 * channels, 2, device=device, dtype=dtype) for _ in range(depth)]
++    att = [
++        torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device, dtype=dtype) for _ in range(depth)
++    ]
++    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device, dtype=dtype)
++    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device, dtype=dtype)
+     with torch.no_grad():
+         out = body(estimator, estimator_input, time_embedding, mask, cnn, att, cnn_out, att_out, lengths)
+     return out, cnn_out, att_out
+@@ -93,3 +96,64 @@ def test_ragged_body_reuses_modulation_without_recomputing_adaln(monkeypatch, ca
+     actual = _run(precomputed, estimator, rows=4, frames=6, cached=cached, lengths=[6, 4])
+     for want, got in zip(expected, actual, strict=True):
+         torch.testing.assert_close(got, want, rtol=1e-4, atol=2e-5)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_fp16_fused_body_matches_fp16_ragged_body(monkeypatch):
++    estimator = _upstream_dit("cuda").half()
++    driver = BatchedToken2Wav.__new__(BatchedToken2Wav)
++    nn.Module.__init__(driver)
++    driver._ragged_fused_body = True
++    calls = []
++
++    def fused(*args, **kwargs):
++        calls.append(True)
++        return blocks_forward_chunk_fused(*args, **kwargs)
++
++    monkeypatch.setattr(
++        "vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav.blocks_forward_chunk_fused",
++        fused,
++    )
++    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.float16):
++        expected = _run(
++            BatchedToken2Wav._blocks_forward_chunk_ragged,
++            estimator,
++            rows=4,
++            frames=6,
++            cached=5,
++            lengths=[6, 4],
++        )
++        actual = _run(driver._ragged_body, estimator, rows=4, frames=6, cached=5, lengths=[6, 4])
++    assert calls, "FP16 service dispatch must use the fused body"
++    for want, got in zip(expected, actual, strict=True):
++        torch.testing.assert_close(got, want, rtol=2e-3, atol=2e-3)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_cfm_only_fp16_preserves_encoder_precision_and_returns_half_caches():
++    from tests.model_executor.models.minicpmo_4_5.test_code2wav_batching import _FakeToken2Wav
++
++    token2wav = _FakeToken2Wav()
++    token2wav.flow.encoder.register_parameter("anchor", nn.Parameter(torch.ones(1, device="cuda")))
++    token2wav.flow.decoder.estimator = _upstream_dit("cuda")
++    token2wav.flow.decoder.rand_noise = torch.randn(1, 80, 100, device="cuda")
++    backend = BatchedToken2Wav(token2wav, cfm_float16=True)
++    assert not backend.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
++    assert next(token2wav.flow.decoder.estimator.parameters()).dtype == torch.float16
++    matrix = torch.randn(8, 8, device="cuda")
++    with backend._autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float32
++    with backend._cfm_autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float16
++    assert not torch.is_autocast_enabled("cuda")
++    with torch.inference_mode():
++        mel, cnn, att = backend._decode_cfm(
++            torch.randn(1, 80, 6, device="cuda"),
++            torch.randn(1, 80, device="cuda"),
++            torch.randn(1, 80, 6, device="cuda"),
++            cnn_cache=None,
++            att_cache=None,
++        )
++    assert mel.dtype == cnn.dtype == att.dtype == torch.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..0b739fade8
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+@@ -0,0 +1,81 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++from types import SimpleNamespace
++
++import pytest
++import torch
++from vllm.config import ModelConfig, VllmConfig
++
++from tests.helpers.mark import hardware_test
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++pytestmark = [pytest.mark.core_model]
++
++
++class _Speaker(torch.nn.Module):
++    def forward(self, x):
++        return x.mean(dim=1)
++
++
++def _config():
++    config = VllmConfig()
++    config.model_config = ModelConfig.__new__(ModelConfig)
++    config.model_config.multimodal_config = None
++    return config
++
++
++@pytest.mark.cpu
++def test_cpu_fallback_does_not_mutate_shared_model_or_config():
++    speaker = CampplusTorch(_Speaker(), "cpu")
++    config = _config()
++    wrapper = SpeakerCudaGraph(speaker, config)
++    feat = torch.randn(17, 80, dtype=torch.bfloat16)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert config.model_config.multimodal_config is None
++    assert wrapper.graph.vllm_config.model_config.multimodal_config is not None
++    assert not wrapper.graph.graphs
++    assert wrapper.speaker is speaker
++
++
++@pytest.mark.cpu
++def test_facade_rejects_non_torch_speaker():
++    from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_token2wav import MiniCPMO45Token2wav
++
++    facade = MiniCPMO45Token2wav.__new__(MiniCPMO45Token2wav)
++    facade._core = SimpleNamespace(_spk_model=object())
++    with pytest.raises(ValueError, match="CUDA Torch speaker"):
++        facade.enable_speaker_cuda_graph(_config())
++
++
++@hardware_test(res={"cuda": "L4"}, num_cards=1)
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA required")
++@torch.inference_mode()
++def test_replay_ownership_shape_capacity_and_precision_fallback():
++    speaker = CampplusTorch(_Speaker(), "cuda:0")
++    wrapper = SpeakerCudaGraph(speaker, _config(), max_graphs=1)
++    feat = torch.randn(17, 80, device="cuda")
++    wrapper(feat)
++    retained = wrapper(feat)
++    expected = speaker(feat).clone()
++    feat.add_(3)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert torch.equal(retained, expected)
++    assert len(wrapper.graph.graphs) == 1
++    other = torch.randn(19, 80, device="cuda")
++    assert torch.equal(wrapper(other), speaker(other))
++    assert len(wrapper.graph.graphs) == 1
++    hits = wrapper.graph.get_cumulative_stats()["graph_hits"]
++    original = torch.backends.cudnn.allow_tf32
++    try:
++        torch.backends.cudnn.allow_tf32 = not original
++        assert torch.equal(wrapper(feat), speaker(feat))
++        assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits
++    finally:
++        torch.backends.cudnn.allow_tf32 = original
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
++    with torch.autocast("cuda", dtype=torch.bfloat16):
++        assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+index 3e9c849670..96bf8528d1 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+@@ -322,14 +322,20 @@ def _cfm_matmul_tf32(fn):
+ 
+     @functools.wraps(fn)
+     def wrapper(self, *args, **kwargs):
+-        if not getattr(self, "_cfm_tf32", False):
+-            return fn(self, *args, **kwargs)
+-        previous = torch.backends.cuda.matmul.allow_tf32
+-        torch.backends.cuda.matmul.allow_tf32 = True
+-        try:
+-            return fn(self, *args, **kwargs)
+-        finally:
+-            torch.backends.cuda.matmul.allow_tf32 = previous
++        precision = (
++            self._cfm_autocast(next(self.flow.parameters()).device)
++            if getattr(self, "_cfm_only_float16", False)
++            else nullcontext()
++        )
++        with precision:
++            if not getattr(self, "_cfm_tf32", False):
++                return fn(self, *args, **kwargs)
++            previous = torch.backends.cuda.matmul.allow_tf32
++            torch.backends.cuda.matmul.allow_tf32 = True
++            try:
++                return fn(self, *args, **kwargs)
++            finally:
++                torch.backends.cuda.matmul.allow_tf32 = previous
+ 
+     return wrapper
+ 
+@@ -355,6 +361,7 @@ class BatchedToken2Wav(nn.Module):
+         setup_cache_size: int = 1,
+         cfm_tf32: bool = False,
+         encoder_graph_config: Mapping[str, Any] | None = None,
++        cfm_float16: bool = False,
+     ):
+         super().__init__()
+         if setup_cache_size < 0:
+@@ -371,6 +378,13 @@ class BatchedToken2Wav(nn.Module):
+         self.flow = token2wav.flow
+         self.hift = token2wav.hift
+         flow_parameter = next(self.flow.parameters(), None)
++        self._cfm_only_float16 = bool(cfm_float16 and not token2wav.float16)
++        if self._cfm_only_float16:
++            if flow_parameter is None or flow_parameter.device.type != "cuda":
++                raise ValueError("cfm_float16 requires CUDA")
++            self.flow.decoder.estimator.half()
++            self.flow.decoder.rand_noise = self.flow.decoder.rand_noise.half()
++
+         if flow_parameter is not None and flow_parameter.device.type == "npu":
+             from vllm_omni.platforms.npu.models.minicpmo_fused import prepare_estimator
+ 
+@@ -431,7 +445,7 @@ class BatchedToken2Wav(nn.Module):
+             del speech, source
+             torch.accelerator.empty_cache()
+         self.float16 = bool(token2wav.float16)
+-        self._estimator_att_compute_dtype = torch.float16 if self.float16 else torch.float32
++        self._estimator_att_compute_dtype = torch.float16 if self.float16 or self._cfm_only_float16 else torch.float32
+         self._estimator_att_cache_dtype = (
+             torch.bfloat16 if bfloat16_attention_cache else self._estimator_att_compute_dtype
+         )
+@@ -494,17 +508,25 @@ class BatchedToken2Wav(nn.Module):
+                 micro_batch_size = int(micro_batch_size_cfg) if micro_batch_size_cfg is not None else 4
+                 enable_whole_euler = bool(cfm_graph_cfg.get("enable_whole_euler", True))
+                 if bool(cfm_graph_cfg.get("fused_body", False)):
+-                    # A reduced-precision attention cache keeps the ragged body,
+-                    # which attends in the activation dtype through upstream.
++                    # A BF16 storage-only cache still uses the ragged body.
++                    # CUDA FP16 flow can keep its matching FP16 cache resident.
+                     # NPU uses the same schedule with AddLayerNorm and packed QKV.
+                     self._ragged_fused_body = (
+                         flow_parameter.device.type in {"cuda", "npu"}
+                         and supports_fused_body(estimator)
+-                        and self._estimator_att_cache_dtype == torch.float32
++                        and (
++                            self._estimator_att_cache_dtype == torch.float32
++                            or (
++                                flow_parameter.device.type == "cuda"
++                                and self._estimator_att_cache_dtype == torch.float16
++                                and self._estimator_att_compute_dtype == torch.float16
++                            )
++                        )
+                     )
+                     if not self._ragged_fused_body:
+                         logger.warning(
+-                            "cfm_fused_body requested but unsupported here (DiT blocks or a non-fp32 attention cache)"
++                            "cfm_fused_body requested but unsupported here "
++                            "(DiT blocks or incompatible attention cache dtype)"
+                         )
+                 # Resident request caches need the fused body and its tiled
+                 # attention, which reads keys/values out of the pool in place.
+@@ -688,6 +710,11 @@ class BatchedToken2Wav(nn.Module):
+             projected = torch.cat([self._project_speakers(feature.speaker_embedding) for feature in features])
+         return [int(feature.mels.shape[1]) for feature in features], projected
+ 
++    def _cfm_autocast(self, device: torch.device):
++        if self._cfm_only_float16:
++            return torch.amp.autocast(device.type, dtype=torch.float16)
++        return self._autocast(device)
++
+     def _autocast(self, device: torch.device):
+         if device.type != "cuda":
+             return nullcontext()
+@@ -1086,7 +1113,10 @@ class BatchedToken2Wav(nn.Module):
+         ``modulation`` comes from the Whole-Euler arena, for either body.
+         """
+         estimator_input = args[1]
+-        if slots is not None or (self._ragged_fused_body and estimator_input.dtype == torch.float32):
++        fused_dtype = estimator_input.dtype == torch.float32 or (
++            estimator_input.is_cuda and estimator_input.dtype == torch.float16
++        )
++        if slots is not None or (self._ragged_fused_body and fused_dtype):
+             # Slot-pool graphs are only built over the fused body (``slot_pool`` above).
+             if estimator_input.device.type == "npu":
+                 from vllm_omni.platforms.npu.models.minicpmo_fused import (
+@@ -1339,6 +1369,8 @@ class BatchedToken2Wav(nn.Module):
+         cache in the same form, already trimmed by ``att_keep``; the eager
+         path returns it stacked and untrimmed (ragged: per request, untrimmed).
+         """
++        if self._cfm_only_float16:
++            mu, speakers, cond = mu.half(), speakers.half(), cond.half()
+         decoder = self.flow.decoder
+         estimator = decoder.estimator
+         batch_size = int(mu.shape[0])
+@@ -1734,7 +1766,7 @@ class BatchedToken2Wav(nn.Module):
+         wrapper = self._whole_euler_graph_wrapper
+         prompt_len = int(features.mels.shape[1])
+         steady = prompt_len + _CACHE_TRIM_SUFFIX
+-        with self._autocast(wrapper.device):
++        with self._cfm_autocast(wrapper.device):
+             return wrapper.precapture(
+                 offsets=range(prompt_len, steady + 1),
+                 steady=steady,
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+index 3ab3f7f96a..e64fcd2f82 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+@@ -1,6 +1,6 @@
+ # SPDX-License-Identifier: Apache-2.0
+ # SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+-"""Tiled CFM attention: float32 tensors, ordinary TF32 Tensor Core dots."""
++"""Tiled CFM attention with FP32/TF32 or FP16 Tensor Core dots."""
+ 
+ import torch
+ from vllm.triton_utils import tl, triton
+@@ -80,7 +80,7 @@ def _attention(
+             (keys[:, None] < nk) & (ds[None, :] < dim),
+             0,
+         )
+-        accumulator = accumulator * correction[:, None] + tl.dot(prob, values, input_precision="tf32")
++        accumulator = accumulator * correction[:, None] + tl.dot(prob.to(values.dtype), values, input_precision="tf32")
+         maximum = new_max
+     result = accumulator / tl.where(denominator > 0, denominator, 1.0)[:, None]
+     tl.store(
+@@ -98,11 +98,11 @@ def cfm_attention(
+     mask: torch.Tensor | None = None,
+     kv_rows: torch.Tensor | None = None,
+ ) -> torch.Tensor:
+-    """Tiled attention with TF32 dots; optional ``kv_rows`` indexes a pooled K/V cache."""
++    """Tiled attention; optional ``kv_rows`` indexes a pooled K/V cache in place."""
+     b, heads, nq, dim = q.shape
+     nk = k.shape[2]
+-    if q.dtype != torch.float32 or k.dtype != torch.float32 or v.dtype != torch.float32:
+-        raise ValueError("CFM tiled attention requires float32 Q/K/V")
++    if q.dtype not in (torch.float32, torch.float16) or k.dtype != q.dtype or v.dtype != q.dtype:
++        raise ValueError("CFM tiled attention requires matching float32 or float16 Q/K/V")
+     num_stages = 2
+     out = torch.empty((b, nq, heads, dim), device=q.device, dtype=q.dtype)
+     _attention[(b, heads, triton.cdiv(nq, 32))](
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+index 4fdbe44879..1b8aeaee6d 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+@@ -1607,6 +1607,9 @@ class MiniCPMO45Code2Wav(nn.Module):
+                     "MiniCPM-o Code2Wav: campplus speaker embedding falling back to CPU onnxruntime "
+                     "(token2wav_device_spk=false)"
+                 )
++        if read_bool_flag(extra, "token2wav_spk_cuda_graph", False):
++            token2wav.enable_speaker_cuda_graph(self.vllm_config)
++            logger.info("MiniCPM-o Code2Wav: exact-shape Torch speaker CUDA graphs enabled")
+         self.backend = BatchedToken2Wav(
+             token2wav,
+             trt_stepper=trt_stepper,
+@@ -1618,6 +1621,7 @@ class MiniCPMO45Code2Wav(nn.Module):
+             setup_cache_size=self._setup_cache_size,
+             cfm_tf32=tf32_mode != "off",
+             encoder_graph_config=self._encoder_graph_config,
++            cfm_float16=read_bool_flag(extra, "cfm_float16", False),
+         )
+         # Captured by the first forward (the warmup run): under vLLM's weight load a graph held GiBs.
+         self._precapture_pending = read_bool_flag(extra, "cfm_graph_precapture", True)
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+index de0f232f0a..b98d4a0f8b 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+@@ -130,6 +130,16 @@ class MiniCPMO45Token2wav:
+         """Run CAM++ on device, optionally without TensorRT on CUDA."""
+         self._core.enable_device_spk_embedding(use_trt=use_trt)
+ 
++    def enable_speaker_cuda_graph(self, vllm_config) -> None:
++        """Replay the current Torch speaker forward without changing its math."""
++        from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++        from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++        speaker = self._core._spk_model
++        if not isinstance(speaker, CampplusTorch) or speaker.device.type != "cuda":
++            raise ValueError("Speaker CUDA graphs require the CUDA Torch speaker model")
++        self._core._spk_model = SpeakerCudaGraph(speaker, vllm_config)
++
+     def __call__(self, generated_speech_tokens, prompt_wav) -> bytes:
+         """One-shot tokens → 24 kHz WAV bytes."""
+         return self._core.forward(
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..eed3b976eb
+--- /dev/null
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+@@ -0,0 +1,56 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Exact-shape replay of the existing Torch CAM++ speaker model."""
++
++from copy import copy
++
++import torch
++from vllm.config import VllmConfig
++from vllm.config.multimodal import MultiModalConfig
++
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.encoder_cuda_graph import EncoderCudaGraph
++
++
++def _precision_policy() -> tuple[bool, ...]:
++    return (
++        torch.backends.cuda.matmul.allow_tf32,
++        torch.backends.cudnn.allow_tf32,
++        torch.backends.cudnn.enabled,
++        torch.backends.cudnn.benchmark,
++        torch.backends.cudnn.deterministic,
++        torch.are_deterministic_algorithms_enabled(),
++    )
++
++
++class SpeakerCudaGraph:
++    """Keep the shared eager model untouched and own this consumer's graphs.
++
++    Shapes are not padded. A changed precision policy runs eagerly instead of
++    replaying kernels captured with another policy. The existing encoder graph
++    manager bounds shape admission, isolates streams, and returns owned outputs.
++    """
++
++    def __init__(self, speaker: CampplusTorch, vllm_config: VllmConfig, *, max_graphs: int = 4):
++        self.speaker = speaker
++        self.device = speaker.device
++        # Code2Wav is a generation stage, so its model config need not carry
++        # multimodal limits. The local exact-shape adapter needs only defaults.
++        config = copy(vllm_config)
++        config.model_config = copy(config.model_config)
++        if config.model_config.multimodal_config is None:
++            config.model_config.multimodal_config = MultiModalConfig()
++        self.graph = EncoderCudaGraph(speaker.model.forward, config, max_graphs=max_graphs)
++        self._policy: tuple[bool, ...] | None = None
++
++    @torch.inference_mode()
++    def __call__(self, feat: torch.Tensor) -> torch.Tensor:
++        if self.device.type != "cuda" or torch.is_autocast_enabled("cuda"):
++            return self.speaker(feat)
++        policy = _precision_policy()
++        if self._policy is None:
++            self._policy = policy
++        elif policy != self._policy:
++            return self.speaker(feat)
++        feat = feat.to(self.device, non_blocking=True).unsqueeze(0).float()
++        return self.graph(feat)
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
index d981d177e..a697af644 100644
--- a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
@@ -24,7 +24,17 @@
     "native-coalescing": {
       "source_revision": "e9b12cf223b4a3900f6f30772065eb058550319a",
       "patch": "peer-round2-native-coalescing.patch",
-      "status": "Regression before FAIL, after104 tests PASS and pre-commit PASS; service retry queued"
+      "status": "104 scheduler tests and pre-commit PASS; service C16/C32 773.9/904.8, no material gain; quality pending"
+    },
+    "speaker-torch-graph": {
+      "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
+      "patch": "peer-round2-speaker-torch-graph.patch",
+      "status": "Bitwise component and lifecycle gates PASS, service screen pending"
+    },
+    "cfm-speaker-composition": {
+      "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+      "patch": "peer-round2-cfm-speaker-composition.patch",
+      "status": "Composition tests and service queued; no qualification"
     }
   },
   "note": "Apply each patch independently to the base. Default behavior remains unchanged unless the corresponding opt-in config is enabled. Do not combine or promote failed candidates as a qualified release."
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-speaker-torch-graph.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-speaker-torch-graph.patch
new file mode 100644
index 000000000..675f3b6ab
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-speaker-torch-graph.patch
@@ -0,0 +1,225 @@
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+index 8a6b81a8fc..5db1e06a76 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+@@ -37,11 +37,15 @@ class _FakeToken2Wav:
+         self.device_spk_calls = 0
+         self.trt_spk_calls = 0
+         self.device_spk_use_trt = None
++        self.speaker_graph_config = None
+ 
+     def enable_device_spk_embedding(self, *, use_trt=True):
+         self.device_spk_calls += 1
+         self.device_spk_use_trt = use_trt
+ 
++    def enable_speaker_cuda_graph(self, config):
++        self.speaker_graph_config = config
++
+     def enable_trt_spk_embedding(self, *, cpu_reference=False):
+         self.trt_spk_calls += 1
+         self.trt_cpu_reference = cpu_reference
+@@ -150,6 +154,7 @@ def test_cuda_speaker_backend_preserves_lazy_model_loading(tmp_path, monkeypatch
+ 
+ 
+ _OTHER_DEFAULTS = {
++    "token2wav_spk_cuda_graph",
+     "token2wav_spk_cpu_reference",
+     "token2wav_float16",
+     "token2wav_trt",
+@@ -295,3 +300,12 @@ def test_facade_forwards_speaker_reference_policy(mocker, cpu_reference):
+     facade._core = core
+     facade.enable_trt_spk_embedding(cpu_reference=cpu_reference)
+     core.enable_trt_spk_embedding.assert_called_once_with(cpu_reference=cpu_reference)
++
++
++@pytest.mark.parametrize("value,enabled", [(True, True), ("true", True), (False, False), ("false", False)])
++def test_speaker_graph_flag_reaches_selected_backend(tmp_path, monkeypatch, value, enabled):
++    monkeypatch.setattr(current_omni_platform, "is_cuda", lambda: True)
++    monkeypatch.setattr(current_omni_platform, "is_npu", lambda: False)
++    model, speaker = _build_backend(tmp_path, monkeypatch, {"token2wav_spk_cuda_graph": value})
++    assert speaker.device_spk_calls == 1
++    assert speaker.speaker_graph_config is (model.vllm_config if enabled else None)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..0b739fade8
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+@@ -0,0 +1,81 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++from types import SimpleNamespace
++
++import pytest
++import torch
++from vllm.config import ModelConfig, VllmConfig
++
++from tests.helpers.mark import hardware_test
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++pytestmark = [pytest.mark.core_model]
++
++
++class _Speaker(torch.nn.Module):
++    def forward(self, x):
++        return x.mean(dim=1)
++
++
++def _config():
++    config = VllmConfig()
++    config.model_config = ModelConfig.__new__(ModelConfig)
++    config.model_config.multimodal_config = None
++    return config
++
++
++@pytest.mark.cpu
++def test_cpu_fallback_does_not_mutate_shared_model_or_config():
++    speaker = CampplusTorch(_Speaker(), "cpu")
++    config = _config()
++    wrapper = SpeakerCudaGraph(speaker, config)
++    feat = torch.randn(17, 80, dtype=torch.bfloat16)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert config.model_config.multimodal_config is None
++    assert wrapper.graph.vllm_config.model_config.multimodal_config is not None
++    assert not wrapper.graph.graphs
++    assert wrapper.speaker is speaker
++
++
++@pytest.mark.cpu
++def test_facade_rejects_non_torch_speaker():
++    from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_token2wav import MiniCPMO45Token2wav
++
++    facade = MiniCPMO45Token2wav.__new__(MiniCPMO45Token2wav)
++    facade._core = SimpleNamespace(_spk_model=object())
++    with pytest.raises(ValueError, match="CUDA Torch speaker"):
++        facade.enable_speaker_cuda_graph(_config())
++
++
++@hardware_test(res={"cuda": "L4"}, num_cards=1)
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA required")
++@torch.inference_mode()
++def test_replay_ownership_shape_capacity_and_precision_fallback():
++    speaker = CampplusTorch(_Speaker(), "cuda:0")
++    wrapper = SpeakerCudaGraph(speaker, _config(), max_graphs=1)
++    feat = torch.randn(17, 80, device="cuda")
++    wrapper(feat)
++    retained = wrapper(feat)
++    expected = speaker(feat).clone()
++    feat.add_(3)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert torch.equal(retained, expected)
++    assert len(wrapper.graph.graphs) == 1
++    other = torch.randn(19, 80, device="cuda")
++    assert torch.equal(wrapper(other), speaker(other))
++    assert len(wrapper.graph.graphs) == 1
++    hits = wrapper.graph.get_cumulative_stats()["graph_hits"]
++    original = torch.backends.cudnn.allow_tf32
++    try:
++        torch.backends.cudnn.allow_tf32 = not original
++        assert torch.equal(wrapper(feat), speaker(feat))
++        assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits
++    finally:
++        torch.backends.cudnn.allow_tf32 = original
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
++    with torch.autocast("cuda", dtype=torch.bfloat16):
++        assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+index 4fdbe44879..7f6374961b 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+@@ -1607,6 +1607,9 @@ class MiniCPMO45Code2Wav(nn.Module):
+                     "MiniCPM-o Code2Wav: campplus speaker embedding falling back to CPU onnxruntime "
+                     "(token2wav_device_spk=false)"
+                 )
++        if read_bool_flag(extra, "token2wav_spk_cuda_graph", False):
++            token2wav.enable_speaker_cuda_graph(self.vllm_config)
++            logger.info("MiniCPM-o Code2Wav: exact-shape Torch speaker CUDA graphs enabled")
+         self.backend = BatchedToken2Wav(
+             token2wav,
+             trt_stepper=trt_stepper,
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+index de0f232f0a..b98d4a0f8b 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+@@ -130,6 +130,16 @@ class MiniCPMO45Token2wav:
+         """Run CAM++ on device, optionally without TensorRT on CUDA."""
+         self._core.enable_device_spk_embedding(use_trt=use_trt)
+ 
++    def enable_speaker_cuda_graph(self, vllm_config) -> None:
++        """Replay the current Torch speaker forward without changing its math."""
++        from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++        from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++        speaker = self._core._spk_model
++        if not isinstance(speaker, CampplusTorch) or speaker.device.type != "cuda":
++            raise ValueError("Speaker CUDA graphs require the CUDA Torch speaker model")
++        self._core._spk_model = SpeakerCudaGraph(speaker, vllm_config)
++
+     def __call__(self, generated_speech_tokens, prompt_wav) -> bytes:
+         """One-shot tokens → 24 kHz WAV bytes."""
+         return self._core.forward(
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..eed3b976eb
+--- /dev/null
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+@@ -0,0 +1,56 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Exact-shape replay of the existing Torch CAM++ speaker model."""
++
++from copy import copy
++
++import torch
++from vllm.config import VllmConfig
++from vllm.config.multimodal import MultiModalConfig
++
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.encoder_cuda_graph import EncoderCudaGraph
++
++
++def _precision_policy() -> tuple[bool, ...]:
++    return (
++        torch.backends.cuda.matmul.allow_tf32,
++        torch.backends.cudnn.allow_tf32,
++        torch.backends.cudnn.enabled,
++        torch.backends.cudnn.benchmark,
++        torch.backends.cudnn.deterministic,
++        torch.are_deterministic_algorithms_enabled(),
++    )
++
++
++class SpeakerCudaGraph:
++    """Keep the shared eager model untouched and own this consumer's graphs.
++
++    Shapes are not padded. A changed precision policy runs eagerly instead of
++    replaying kernels captured with another policy. The existing encoder graph
++    manager bounds shape admission, isolates streams, and returns owned outputs.
++    """
++
++    def __init__(self, speaker: CampplusTorch, vllm_config: VllmConfig, *, max_graphs: int = 4):
++        self.speaker = speaker
++        self.device = speaker.device
++        # Code2Wav is a generation stage, so its model config need not carry
++        # multimodal limits. The local exact-shape adapter needs only defaults.
++        config = copy(vllm_config)
++        config.model_config = copy(config.model_config)
++        if config.model_config.multimodal_config is None:
++            config.model_config.multimodal_config = MultiModalConfig()
++        self.graph = EncoderCudaGraph(speaker.model.forward, config, max_graphs=max_graphs)
++        self._policy: tuple[bool, ...] | None = None
++
++    @torch.inference_mode()
++    def __call__(self, feat: torch.Tensor) -> torch.Tensor:
++        if self.device.type != "cuda" or torch.is_autocast_enabled("cuda"):
++            return self.speaker(feat)
++        policy = _precision_policy()
++        if self._policy is None:
++            self._policy = policy
++        elif policy != self._policy:
++            return self.speaker(feat)
++        feat = feat.to(self.device, non_blocking=True).unsqueeze(0).float()
++        return self.graph(feat)
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json
new file mode 100644
index 000000000..d0f5b6e74
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json
@@ -0,0 +1,21 @@
+{
+  "frozen_at_utc": "2026-10-21T08:59:05.207595+00:00",
+  "base_revision": "4671fdc3736c760f1abd637e30079b3cf65d1fdf",
+  "speaker_commit": "17246ce5e6",
+  "hypothesis": "Compose selective CFM FP16 with bitwise Torch speaker replay under two ordinary Talker and four Code2Wav replicas, where replication may expose device compute as the next limit.",
+  "evidence": [
+    "Selective CFM-only FP16 retained FP32 encoder/speaker/HiFT and passed descriptive quality means, but single-worker throughput did not improve",
+    "Speaker graph four real inputs bitwise equal, component2.3x speedup",
+    "Native Talker four vocoders only C32 1332.4 versus1172.1 with two, showing diminishing vocoder replication gains"
+  ],
+  "contrast": "Against pending FP32 ordinary Talker2/Code2Wav4 speaker-graph profile: only enable cfm_float16 on matching composed source. All other settings including8GiB stage0 KV identical.",
+  "checks": [
+    "Resolve configuration and strict opt-in flags",
+    "Run existing selective CFM precision and speaker graph tests on composed tree",
+    "No weight, diffusion-step, sampling or quality-margin changes"
+  ],
+  "protocol": "64 reused tuning,discard+one,C1/C16/C32 plus native quality scoring; no holdout use",
+  "qualification": "Exploratory; final same-card repeated comparison and all quality confidence bounds remain required.",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "integration": "Cherry-pick applied cleanly; service controller requires combined precision, graph and flag tests to pass before launch."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-peer-tuning64.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-peer-tuning64.json
new file mode 100644
index 000000000..ebf07ceec
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-peer-tuning64.json
@@ -0,0 +1,14 @@
+{
+  "frozen_at_utc": "2026-10-21T08:57:27.534236+00:00",
+  "source_revision": "a4f4778f312791c2d190b48e521141887ed160c8",
+  "profile": "track_s_fast_r11 unchanged",
+  "purpose": "Match the exact64 reused tuning prompt workload and discard+one protocol of exploratory Omni screens. Existing320 evaluation repeated baseline remains unchanged; do not treat cross-cohort screening ratios as final wins.",
+  "concurrency": [
+    1,
+    16,
+    32
+  ],
+  "mps": true,
+  "model_revision": "503e754207c94da6bb26850b4469f367c9ea3582",
+  "holdout_used": false
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-replicas.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-replicas.json
new file mode 100644
index 000000000..8af6676c4
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-replicas.json
@@ -0,0 +1,56 @@
+{
+  "frozen_at_utc": "2026-10-21T08:55:29.736386+00:00",
+  "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
+  "hypothesis": "Replicate both ordinary Talker and Code2Wav to overlap host work rather than only scaling the vocoder. Exact Torch speaker graphs reduce prompt host launch work.",
+  "evidence": [
+    "V1 Talker plus two vocoders reaches C32 1057.4 with descriptive quality means within margins",
+    "Native Talker adds11% but its C32 SIM screen exceeds margin; retain ordinary Talker",
+    "Torch speaker graph component is bitwise equal and2.3x faster"
+  ],
+  "candidate": {
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "capacities_per_replica": [
+      16,
+      16,
+      16
+    ],
+    "stage0_kv_bytes": 8589934592,
+    "stage1_kv_bytes_per_replica": 4294967296,
+    "micro_batch_size": 4,
+    "cuda_mps": true,
+    "speaker_cuda_graph": true,
+    "precision": "FP32 CFM/HiFT unchanged"
+  },
+  "memory_policy": "Explicit8GiB stage0 KV exceeds single40960-token context requirement and leaves memory for replicas. This is a composite exploratory profile, not isolated attribution of replica or KV changes.",
+  "protocol": "64 reused tuning prompts,discard+one,C1/C16/C32; zero failed requests; native quality screening; no holdout use",
+  "qualification": "No final claim without paired repeated peer comparison and all frozen quality confidence bounds.",
+  "resolved_config_check": {
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "mps": true,
+    "speaker_graph": true,
+    "result": "PASS"
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json
index 514e59932..b03b9b315 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-speaker-torch-graph.json
@@ -7,5 +7,15 @@
   "scope": "New default-off speaker graph option. Bounded graph cache, eager fallback for unsupported input/policy, owned outputs protect cached embeddings from later replays.",
   "correctness_gate": "Bitwise equality against the same eager Torch model on real reused reference features; graph output ownership, shape fallback and precision-policy separation tests. No service trial if numerical gate fails.",
   "performance_gate": "Measure warmed component latency first; service trial only after material component improvement.",
-  "quality_contract": "All final speech noninferiority gates unchanged;256 holdout unused."
+  "quality_contract": "All final speech noninferiority gates unchanged;256 holdout unused.",
+  "implementation_design": "Reuse existing exact-shape EncoderCudaGraph manager with four-shape cap, owned outputs and stream isolation; consumer-local speaker wrapper leaves shared eager model untouched; changed precision policy or autocast uses eager fallback.",
+  "feasibility_gate": "Four real reference inputs bitwise equal, zero max absolute error; warmed eager11-13ms versus graph4.9ms. Production wrapper and service gates still pending.",
+  "service_contrast": {
+    "frozen_at_utc": "2026-10-21T08:51:46.358014+00:00",
+    "baseline": "Previously measured V1/V1/V1 two Code2Wav replicas with MPS; C16/C32 973.1/1057.4, quality means within margins",
+    "candidate": "Same configuration plus token2wav_spk_cuda_graph true; max4 exact shapes, ordinary Talker retained",
+    "protocol": "64 reused tuning,discard+one,C1/C16/C32; native quality scoring. Different card possible; no final same-card claim.",
+    "gates": "3 wrapper CPU/CUDA tests PASS; 4 real inputs bitwise equal; 318 existing integration tests PASS; 105 updated flag/CPU tests PASS; pre-commit PASS"
+  },
+  "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1"
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json
new file mode 100644
index 000000000..3651ab679
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json
@@ -0,0 +1,168 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "e9b12cf223b4a3900f6f30772065eb058550319a",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      1,
+      1
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v2"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP32 CFM/HiFT, existing CFM TF32 policy",
+    "coalescing": {
+      "min_batch": 8,
+      "max_wait_ms": 6,
+      "policy": "idle_wait",
+      "engaged_in_server_log": true
+    }
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
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+      "cache_evidence": {},
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+      "server_startup_s": null,
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+      "valid": true,
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+  "quality": {},
+  "quality_status": "Scoring pending"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json
index 331d9c445..4bef16ba6 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas2-screen.json
@@ -199,5 +199,27 @@
     }
   },
   "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
-  "quality_finding": "C32 SIM mean49.2423 versus Torch/MPS control51.0028: decline1.7605 exceeds0.50 margin. Not a qualified candidate; C1/C16 means improved. Four-replica trial retained only as scaling diagnostic."
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
+      "wer_pp": -0.8486562942008486,
+      "sim_x100_drop": -0.7500781416893005,
+      "utmos_drop": -0.02006734162569046,
+      "within_mean_margins": true
+    },
+    "16": {
+      "wer_pp": -0.7072135785007072,
+      "sim_x100_drop": -1.3642717003822327,
+      "utmos_drop": -0.016416117548942566,
+      "within_mean_margins": true
+    },
+    "32": {
+      "wer_pp": -0.14144271570014147,
+      "sim_x100_drop": 1.7604798376560211,
+      "utmos_drop": -0.018871638923883438,
+      "within_mean_margins": false
+    }
+  },
+  "mean_screen_within_margins": false,
+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds.",
+  "quality_finding": "C32 SIM mean decline1.7605 exceeds0.50 margin; not a qualified candidate."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json
new file mode 100644
index 000000000..cb41fa7a2
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json
@@ -0,0 +1,162 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      1,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v2",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP32 CFM/HiFT, existing CFM TF32 policy"
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
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+      "mps_policy": "off",
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+      "ids_sha256": "",
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+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
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+      "throughput_frames_s": 212.87448270190214,
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+      "e2e_p50_s": 0.5100491913035512,
+      "e2e_p95_s": 0.6654237742535769,
+      "total_audio_s": 279.96,
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+      "n_requests": 64,
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+      "valid": true,
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+      "throughput_frames_s": 1207.4694042912267,
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+      "e2e_p50_s": 1.4199548321776092,
+      "e2e_p95_s": 1.6978545924182982,
+      "total_audio_s": 281.56,
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+      "inter_chunk_gap_p50_s": 0.12460947129875422,
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+      "label": "run1",
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+      "measured": true,
+      "gpu": "",
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+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
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+      "makespan_s": 5.29280614759773,
+      "throughput_frames_s": 1332.3745104854677,
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+      "ttfa_p95_s": 2.400166882527992,
+      "rtf_mean": 0.5418641596127827,
+      "rtf_duration_weighted": 0.5395365579185033,
+      "req_s": 12.091884383305436,
+      "audio_s_per_s": 53.29498041941871,
+      "e2e_p50_s": 2.1292040711268783,
+      "e2e_p95_s": 4.264313547266647,
+      "total_audio_s": 282.08,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.00021377972734626383,
+      "stall_max_s": 0.013681902550160885,
+      "inter_chunk_gap_p50_s": 0.2513433205895126,
+      "inter_chunk_gap_p95_s": 0.5490834197495132,
+      "inter_chunk_gap_max_s": 0.8548506069928408
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+  },
+  "quality": {},
+  "quality_status": "Scoring pending"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json
index 37c03b3f5..b1b8badb7 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-replicas2-screen.json
@@ -198,5 +198,27 @@
       "wer_mean": 0.019467511655011656
     }
   },
-  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification"
+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
+      "wer_pp": 0.0,
+      "sim_x100_drop": -0.007801532745361328,
+      "utmos_drop": -0.0004766695201396942,
+      "within_mean_margins": true
+    },
+    "16": {
+      "wer_pp": -0.42432814710042444,
+      "sim_x100_drop": -0.46340715885162354,
+      "utmos_drop": 0.003962721675634384,
+      "within_mean_margins": true
+    },
+    "32": {
+      "wer_pp": -0.28288543140028294,
+      "sim_x100_drop": 0.15683206915855408,
+      "utmos_drop": 0.012685157358646393,
+      "within_mean_margins": true
+    }
+  },
+  "mean_screen_within_margins": true,
+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
index 1a0bfcd07..f92d55e25 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
@@ -1,7 +1,7 @@
 {
   "scope": "Completed round-two tuning screens; reused data, no final acceptance",
   "path": "peer-round2-screen-requests-quality.json.gz",
-  "sha256": "8d74094d629566caf708ea6336c33647cd1b39dfeaf73f60e7946713cd15a116",
+  "sha256": "54fc11745c94743fc97d573d026a45d06f4d7d836a1b36bb4d5d20820b326189",
   "profiles": [
     "screen-torch-mps",
     "screen-capacity32-mps",
@@ -17,7 +17,9 @@
     "screen-cfm-only-fp16-mps",
     "screen-stage2-replicas2",
     "screen-native-talker-replicas2",
-    "screen-native-stage2-batch16"
+    "screen-native-stage2-batch16",
+    "screen-native-coalesce8-batch16",
+    "screen-native-talker-replicas4"
   ],
   "privacy": "Audio and ASR hypothesis text are excluded. Audio hashes and error counts remain."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
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zXAc5IN(B5yM(s-S<>E>ctI!qpnm6dl8Ar+r3h4hn0Q7Hv{o@;7{{26-DF5+a|MIW@
R{nuZA{SO52OF}cxDgddL{44+f

diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-probe.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-probe.json
new file mode 100644
index 000000000..f9808eb15
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-probe.json
@@ -0,0 +1,56 @@
+{
+  "scope": "Four reused real reference features; exact Torch CAM++ graph diagnostic, no service performance claim",
+  "rows": [
+    {
+      "index": 0,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.011056637484580278,
+      "graph_s": 0.004893266269937158
+    },
+    {
+      "index": 1,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.011136047448962927,
+      "graph_s": 0.004889287520200014
+    },
+    {
+      "index": 2,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.01085416846908629,
+      "graph_s": 0.0048878711182624105
+    },
+    {
+      "index": 3,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.012561971647664904,
+      "graph_s": 0.004896736517548561
+    }
+  ],
+  "gate": "PASS",
+  "source_revision": "172395ef6ea072c531a89dc18ab868ff2f9ada12",
+  "implementation": "Standalone graph feasibility probe; production wrapper validation separately pending"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-wrapper-probe.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-wrapper-probe.json
new file mode 100644
index 000000000..05a4e5a8d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-wrapper-probe.json
@@ -0,0 +1,56 @@
+{
+  "scope": "Four reused real reference features; exact Torch CAM++ graph diagnostic, no service performance claim",
+  "rows": [
+    {
+      "index": 0,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.011628901679068803,
+      "graph_s": 0.004940513847395777
+    },
+    {
+      "index": 1,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.011352018034085632,
+      "graph_s": 0.004936109529808164
+    },
+    {
+      "index": 2,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.011271076370030641,
+      "graph_s": 0.0049291577655822035
+    },
+    {
+      "index": 3,
+      "shape": [
+        598,
+        80
+      ],
+      "eager_repeat_equal": true,
+      "graph_equal": true,
+      "max_abs": 0.0,
+      "eager_s": 0.011377271730452776,
+      "graph_s": 0.004927852563560009
+    }
+  ],
+  "gate": "PASS",
+  "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
+  "validation": "3 CPU/CUDA wrapper tests,318 existing integration tests,105 updated flag/CPU tests and pre-commit passed"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
index 97eba3365..9cc018fab 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -18,13 +18,18 @@
     "Native Talker with two replicas throughput screen",
     "Native stage2 no-coalescing control",
     "Setup numerical A/A audit confirms prior FAIL",
-    "Native coalescing constructor fix,104 tests and pre-commit PASS"
+    "Native coalescing constructor fix,104 tests and pre-commit PASS",
+    "Native coalescing6ms screen, no material throughput gain",
+    "Native Talker four-vocoder screen,C32 1332.4",
+    "Torch speaker exact graph implementation, real-feature bitwise gate and CPU/CUDA checks"
   ],
   "active": [
-    "Native Talker two-replica quality scoring",
-    "Native coalescing service retry queued",
-    "Native Talker four-replica service queued",
-    "Torch speaker graph exactness probe queued"
+    "Coalescing/control speech quality scoring",
+    "Native Talker four-replica quality queued",
+    "Matched peer64-tuning baseline",
+    "Ordinary Talker plus speaker-graph two-vocoder service screen",
+    "Ordinary Talker2/Code2Wav4 speaker-graph screen",
+    "Selective CFM plus speaker graph composition tests/service queued"
   ],
   "reserved_holdout_used": false,
   "quality_margins": {
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_speaker_graph.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_speaker_graph.py
new file mode 100644
index 000000000..40b471181
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_speaker_graph.py
@@ -0,0 +1,82 @@
+import argparse
+import hashlib
+import json
+import time
+from pathlib import Path
+
+import torch
+import torchaudio
+from torchaudio.compliance import kaldi
+from vllm.config import ModelConfig, VllmConfig
+from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import get_campplus_torch
+from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
+
+parser = argparse.ArgumentParser(
+    description="Check exact Torch CAM++ graph replay on four reused reference WAVs"
+)
+parser.add_argument("--model-assets", type=Path, required=True)
+parser.add_argument("--prompts", type=Path, required=True)
+parser.add_argument("--out", type=Path, required=True)
+a = parser.parse_args()
+paths = sorted(a.prompts.glob("*.wav"))
+assert len(paths) == 4, "Expected four normalized reference WAVs"
+
+torch.set_num_threads(4)
+torch.backends.cudnn.allow_tf32 = False
+torch.backends.cuda.matmul.allow_tf32 = True
+model = get_campplus_torch(str(a.model_assets / "campplus.onnx"), "cuda")
+features = []
+for p in paths:
+    wav, sr = torchaudio.load(p)
+    if sr != 16000:
+        wav = torchaudio.functional.resample(wav, sr, 16000)
+    feat = kaldi.fbank(wav, num_mel_bins=80, dither=0, sample_frequency=16000)
+    feat -= feat.mean(dim=0, keepdim=True)
+    features.append(feat.cuda())
+
+config = VllmConfig()
+config.model_config = ModelConfig.__new__(ModelConfig)
+config.model_config.multimodal_config = None
+wrapper = SpeakerCudaGraph(model, config)
+rows = []
+with torch.inference_mode():
+    for i, feat in enumerate(features):
+        wrapper(feat)
+        captured = wrapper(feat)
+        eager = model(feat)
+        eager2 = model(feat)
+        torch.cuda.synchronize()
+
+        def measure(fn):
+            vals = []
+            for _ in range(20):
+                torch.cuda.synchronize()
+                start = time.perf_counter()
+                fn()
+                torch.cuda.synchronize()
+                vals.append(time.perf_counter() - start)
+            return sum(vals) / len(vals)
+
+        def replay():
+            return wrapper(feat)
+
+        row = {
+            "index": i,
+            "reference_sha256": hashlib.sha256(paths[i].read_bytes()).hexdigest(),
+            "shape": list(feat.shape),
+            "eager_repeat_equal": torch.equal(eager, eager2),
+            "graph_equal": torch.equal(eager, captured),
+            "max_abs": float((eager - captured).abs().max()),
+            "eager_s": measure(lambda: model(feat)),
+            "graph_s": measure(replay),
+        }
+        rows.append(row)
+        print(row, flush=True)
+
+d = {
+    "scope": "Four reused references; CAM++ component diagnostic, not service performance",
+    "rows": rows,
+    "gate": "PASS" if all(x["graph_equal"] and x["eager_repeat_equal"] for x in rows) else "FAIL",
+}
+a.out.write_text(json.dumps(d, indent=2) + "\n")
+assert d["gate"] == "PASS", d

From 6caf11e3d236ab3f8a2d6408c0bf6f1ac006ee3a Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 17:40:02 +0800
Subject: [PATCH 31/40] Preserve matched peer screens and freeze clustered
 quality repeats

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   8 +-
 .../peer-round2-cfm-speaker-composition.json  |   3 +-
 .../peer-round2-pipeline-cpu-profile.json     |   9 +
 .../plan/peer-round2-quality-repeats.json     |  26 ++
 .../plan/peer-round2-temporal-window.json     |  22 ++
 .../peer-round2-cfm-speaker-screen.json       | 228 ++++++++++++++++
 .../peer-round2-native-coalescing-screen.json |  66 ++++-
 .../peer-round2-native-stage2-screen.json     |  66 ++++-
 ...round2-native-talker-replicas4-screen.json |  66 ++++-
 ...peer-round2-peer-tuning64-requests.json.gz | Bin 0 -> 32086 bytes
 .../results/peer-round2-peer-tuning64.json    | 143 ++++++++++
 .../peer-round2-pipeline-replicas-screen.json | 226 ++++++++++++++++
 .../results/peer-round2-screen-artifact.json  |   8 +-
 .../results/peer-round2-screen-quality.json   | 246 ++++++++++++++++++
 ...eer-round2-screen-requests-quality.json.gz | Bin 674426 -> 866977 bytes
 .../peer-round2-speaker-graph-screen.json     | 225 ++++++++++++++++
 .../results/peer-round2-status.json           |  21 +-
 .../results/peer-round2-window50-screen.json  | 166 ++++++++++++
 .../peer_round2_clustered_quality.py          |  95 +++++++
 .../test_peer_round2_clustered_quality.py     |  77 ++++++
 20 files changed, 1683 insertions(+), 18 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-cpu-profile.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-quality-repeats.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-temporal-window.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-speaker-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-peer-tuning64-requests.json.gz
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-peer-tuning64.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-replicas-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_clustered_quality.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_clustered_quality.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 4b6e11d9b..84a8b2fac 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -12,9 +12,13 @@ The requester asked to continue until vLLM-Omni exceeds the source-pinned single
 - [Selective CFM precision screen](results/peer-round2-cfm-only-fp16-screen.json): C16/C32 815.5/864.3 frames/s; descriptive quality means within margins, no confidence-bound acceptance.
 - [Two same-GPU replicas](results/peer-round2-replicas2-screen.json): C16/C32 973.1/1057.4 frames/s; descriptive quality means within margins. [Native Talker plus two replicas](results/peer-round2-native-talker-replicas2-screen.json): 1053.7/1172.1 frames/s, but C32 SIM mean drops1.76, exceeding the0.50 margin. Neither is a qualified peer win.
 - [Native stage2 control](results/peer-round2-native-stage2-screen.json) reaches C32 898.2 frames/s. The [coalescing contrast](results/peer-round2-native-coalescing-screen.json) initially failed startup; its constructor fix passes104 scheduler tests. The successful retry reaches C16/C32 773.9/904.8, with no material throughput gain.
-- [Prompt-setup A/A audit](results/peer-round2-setup-control-audit.json) confirms the numerical rejection; the [four-replica scaling diagnostic](results/peer-round2-native-talker-replicas4-screen.json) reaches C32 1332.4, with quality pending.
+- [Prompt-setup A/A audit](results/peer-round2-setup-control-audit.json) confirms the numerical rejection; the [four-replica scaling diagnostic](results/peer-round2-native-talker-replicas4-screen.json) reaches C32 1332.4, but C32 WER increases1.4144 percentage points in the descriptive screen, exceeding the0.20 margin.
 - [Exact Torch speaker graph](results/peer-round2-speaker-graph-wrapper-probe.json): four real references are bitwise equal; component latency falls from about11.4 to4.9ms. Output ownership, shape capacity, policy fallback, and backend integration checks pass. [Service and composition trials](plan/peer-round2-cfm-speaker-composition.json) remain unqualified.
-- [Matched peer tuning workload](plan/peer-round2-peer-tuning64.json) supplements the unchanged320-request repeated baseline; cross-cohort screening ratios are not final comparisons.
+- [Matched peer tuning workload](results/peer-round2-peer-tuning64.json) reaches C16/C32 1493.4/2544.1 frames/s on the same64 prompt IDs; the unchanged320-request repeated baseline remains the formal target.
+- [Ordinary Talker2 / Code2Wav4 FP32](results/peer-round2-pipeline-replicas-screen.json) reaches C16/C32 1103.9/1423.5 frames/s; [selective CFM FP16 composition](results/peer-round2-cfm-speaker-screen.json) reaches1184.3/1510.9. Both have descriptive means within margins, without confidence-bound qualification.
+- [50-frame window screen](results/peer-round2-window50-screen.json) reaches1316.0/1592.2 frames/s, below the matched peer. C32 TTFA p50/p95 is1.517/1.973s and the first audio chunk averages1.84s. Quality scoring is pending. Larger windows affect first-audio latency and numerical context; this is not equivalent-latency streaming.
+- [Three-repeat quality design](plan/peer-round2-quality-repeats.json) was frozen before generating any reserved holdout output. The256 paired prompt clusters remain the independent units: sum WER counts and average SIM/UTMOS within each prompt across three fixed-seed runs, then apply unchanged20,000-draw bootstrap and all9 margins. [Validator controls](validator/test_peer_round2_clustered_quality.py) pass8 synthetic cases; this is not a real quality verdict. Earlier FAILs remain unchanged.
+- [Separate CPU/GIL diagnostic](plan/peer-round2-pipeline-cpu-profile.json) is excluded from performance reporting and will guide the next implementation hypothesis.
 - [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json
index d0f5b6e74..dc93629d0 100644
--- a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cfm-speaker-composition.json
@@ -17,5 +17,6 @@
   "protocol": "64 reused tuning,discard+one,C1/C16/C32 plus native quality scoring; no holdout use",
   "qualification": "Exploratory; final same-card repeated comparison and all quality confidence bounds remain required.",
   "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
-  "integration": "Cherry-pick applied cleanly; service controller requires combined precision, graph and flag tests to pass before launch."
+  "integration": "Cherry-pick applied cleanly; service controller requires combined precision, graph and flag tests to pass before launch.",
+  "pre_service_combined_tests": "113 passed; source unchanged after tests"
 }
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-cpu-profile.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-cpu-profile.json
new file mode 100644
index 000000000..5f5f9ecca
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-pipeline-cpu-profile.json
@@ -0,0 +1,9 @@
+{
+  "frozen_at_utc": "2026-10-21T09:30:32.863019+00:00",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "profile": "Ordinary Talker2/Code2Wav4, selective CFM and exact speaker graph,25-frame windows",
+  "hypothesis": "Diminishing replication gains may reflect central orchestration or per-frame host work rather than vocoder compute alone. Sample all Python descendants to locate GIL work.",
+  "protocol": "Fresh reservedGPU service; unprofiled64-tuning warm/discard+one atC32, then separate64-tuning discard+three while20s100Hz py-spy samples all descendants holding the GIL. Record per-process CPU-time deltas.",
+  "exclusions": "All requests of this diagnostic, including warm runs, excluded from every performance aggregate; no speech quality acceptance or holdout use.",
+  "limitations": "Sampling perturbs the process; GIL-only stacks omit native CPU work, so CPU-time deltas and prior operator traces provide complementary evidence."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-quality-repeats.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-quality-repeats.json
new file mode 100644
index 000000000..6ca3ee30a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-quality-repeats.json
@@ -0,0 +1,26 @@
+{
+  "frozen_at_utc": "2026-10-21T09:24:32.509328+00:00",
+  "base_plan_sha256": "8e204a1e6e95c7ff1148c26ce093d1de73a447ce46fe5b19f99b35b3c5e8f9ab",
+  "reason": "Reduce within-prompt inference variation before any holdout generation, retaining256 independent prompt clusters and all original margins.",
+  "measured_runs": [
+    1,
+    2,
+    3
+  ],
+  "discarded_run": 0,
+  "sampling_seed": 42,
+  "bootstrap_unit": "256 paired prompts; sum WER counts and average SIM/UTMOS across three repeats within each prompt before resampling prompts",
+  "bootstrap_draws": 20000,
+  "bootstrap_seed": 20261022,
+  "confidence": "One-sided95 percent upper degradation bound for each of three metrics at C1/C16/C32; all9 must pass",
+  "margins": {
+    "wer_percentage_points": 0.2,
+    "sim_x100_drop": 0.5,
+    "utmos_drop": 0.05
+  },
+  "reference_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "holdout_generated_before_freeze": false,
+  "prior_verdicts": "All earlier FAILs unchanged; original single-repeat validator retained unchanged",
+  "driver": "peer_round2_holdout.py --repeats 3; score all three measured runs with identical scorer weights/config",
+  "validator": "peer_round2_clustered_quality.py delegates to unchanged paired bootstrap after within-prompt aggregation"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-temporal-window.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-temporal-window.json
new file mode 100644
index 000000000..a9fa05015
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-temporal-window.json
@@ -0,0 +1,22 @@
+{
+  "frozen_at_utc": "2026-10-21T09:13:38.765171+00:00",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "hypothesis": "Larger temporal codec windows amortize per-chunk CFM/HiFT dispatch and improve kernel utilization without requiring larger request batches.",
+  "priority": "User selected high-concurrency throughput priority, with TTFA/RTF reported; no latency threshold was specified.",
+  "contrast": "Same selective-CFM, Torch speaker graph, ordinary Talker2/Code2Wav4 profile; only codec_chunk_frames changes25 to50 or100. Existing graph geometry derives steady shapes from this value; exact short-tail admission remains unchanged.",
+  "tradeoff": "Initial window also grows: the current connector uses one configured window for every payload. TTFA may approach completion for short utterances; do not claim equivalent first-audio behavior.",
+  "candidates": [
+    50,
+    100
+  ],
+  "protocol": "Each fresh service:64 reused tuning,C1/C16/C32,discard+one,all native quality metrics. No sample exclusions or holdout use.",
+  "acceptance": "Zero failures and all original final quality confidence bounds; benchmark audio-frame accounting unchanged. Larger-window results must disclose first-chunk duration and TTFA.",
+  "fp32_control_addendum": {
+    "frozen_at_utc": "2026-10-21T09:19:47.883091+00:00",
+    "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
+    "candidate": "100-frame window with FP32 CFM, otherwise ordinary Talker2/Code2Wav4 plus speaker graph",
+    "reason": "The FP32 25-frame pipeline screen now has all descriptive quality means within margins; test whether larger windows alone suffice, retaining this precision path. This also contrasts against selective-CFM100 before final selection.",
+    "protocol": "Same64 reused tuning,discard+one,C1/C16/C32 and native scoring; no holdout",
+    "chunk_processor_tests": "45 passed"
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-speaker-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-speaker-screen.json
new file mode 100644
index 000000000..3c95b259d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-cfm-speaker-screen.json
@@ -0,0 +1,228 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json
index 3651ab679..272f25486 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-coalescing-screen.json
@@ -163,6 +163,68 @@
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json
index afffe43c5..c0c218e73 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-stage2-screen.json
@@ -157,6 +157,68 @@
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json
index cb41fa7a2..632ca556f 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-native-talker-replicas4-screen.json
@@ -157,6 +157,68 @@
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-peer-tuning64.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-peer-tuning64.json
new file mode 100644
index 000000000..fbc11039d
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-peer-tuning64.json
@@ -0,0 +1,143 @@
+{
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+  "source_revision": "a4f4778f312791c2d190b48e521141887ed160c8",
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+      "n_requests": 64,
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+  "requests_sha256": "6184f89a0dd09b3a3ade00d311affe97f1857e004e177e617c18414f17257b70",
+  "metadata_note": "Raw helper labels are defaults; actual cohort=tuning, MPS=on, revision pinned above.",
+  "holdout_used": false
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-replicas-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-replicas-screen.json
new file mode 100644
index 000000000..bf9b0e474
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-replicas-screen.json
@@ -0,0 +1,226 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP32 CFM/HiFT, existing CFM TF32 policy",
+    "speaker_graph": true,
+    "stage0_kv_bytes": 8589934592
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
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+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
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+      "candidate_id": "",
+      "config_digest": "",
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+  },
+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
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+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
index f92d55e25..1f196c075 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
@@ -1,7 +1,7 @@
 {
   "scope": "Completed round-two tuning screens; reused data, no final acceptance",
   "path": "peer-round2-screen-requests-quality.json.gz",
-  "sha256": "54fc11745c94743fc97d573d026a45d06f4d7d836a1b36bb4d5d20820b326189",
+  "sha256": "d45d2ed92dd930d6ab203e0e36105c1f570001f35a707af8dd07b507a4c8aa68",
   "profiles": [
     "screen-torch-mps",
     "screen-capacity32-mps",
@@ -19,7 +19,11 @@
     "screen-native-talker-replicas2",
     "screen-native-stage2-batch16",
     "screen-native-coalesce8-batch16",
-    "screen-native-talker-replicas4"
+    "screen-native-talker-replicas4",
+    "screen-speaker-graph-replicas2",
+    "screen-pipeline-replicas2x4",
+    "screen-cfm-speaker-replicas2x4",
+    "screen-cfm-speaker-window50"
   ],
   "privacy": "Audio and ASR hypothesis text are excluded. Audio hashes and error counts remain."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
index 6e9d74cd0..f9c48c064 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
@@ -439,6 +439,252 @@
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-screen.json
new file mode 100644
index 000000000..160f0b519
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-speaker-graph-screen.json
@@ -0,0 +1,225 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      1,
+      2
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP32 CFM/HiFT, existing CFM TF32 policy",
+    "speaker_graph": true
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
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+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
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+      "seed_index": 0,
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+      "strict": false,
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+      "n_requests": 64,
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+      "n_requests": 64,
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+      "inter_chunk_gap_max_s": 0.748159397393465
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+  },
+  "quality": {
+    "1": {
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+      "sim": 50.04666182398796,
+      "utmos": 4.21150366216898,
+      "wer": 0.021216407355021217,
+      "wer_counts": {
+        "substitutions": 12,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 694
+      },
+      "wer_mean": 0.025693837412587413
+    },
+    "16": {
+      "n": 64,
+      "sim": 49.90199637413025,
+      "utmos": 4.19744374230504,
+      "wer": 0.018387553041018388,
+      "wer_counts": {
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+    "32": {
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+      "sim": 50.555298656225204,
+      "utmos": 4.217923618853092,
+      "wer": 0.016973125884016973,
+      "wer_counts": {
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+        "deletions": 1,
+        "insertions": 2,
+        "hits": 697
+      },
+      "wer_mean": 0.02150895979020979
+    }
+  },
+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
+      "wer_pp": 0.14144271570014147,
+      "sim_x100_drop": -0.007773846387863159,
+      "utmos_drop": -0.0005114823579788208,
+      "within_mean_margins": true
+    },
+    "16": {
+      "wer_pp": -0.14144271570014147,
+      "sim_x100_drop": 0.14313480257987976,
+      "utmos_drop": 0.02523399144411087,
+      "within_mean_margins": true
+    },
+    "32": {
+      "wer_pp": -0.14144271570014147,
+      "sim_x100_drop": 0.44750285148620605,
+      "utmos_drop": 0.002481665462255478,
+      "within_mean_margins": true
+    }
+  },
+  "mean_screen_within_margins": true,
+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
index 9cc018fab..468ab80fd 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -21,15 +21,22 @@
     "Native coalescing constructor fix,104 tests and pre-commit PASS",
     "Native coalescing6ms screen, no material throughput gain",
     "Native Talker four-vocoder screen,C32 1332.4",
-    "Torch speaker exact graph implementation, real-feature bitwise gate and CPU/CUDA checks"
+    "Torch speaker exact graph implementation, real-feature bitwise gate and CPU/CUDA checks",
+    "Matched peer64 tuning baseline,C16/C32 1493.4/2544.1",
+    "Native coalescing quality exceeds margins",
+    "Native Talker four-replica quality exceeds WER margin",
+    "Speaker graph2replica descriptive means within margins,C32 1074.3",
+    "Ordinary Talker2/vocoder4 FP32 descriptive means within margins,C32 1423.5",
+    "Combined precision/speaker graph113 tests PASS",
+    "Selective CFM speaker2x4 screen, C16/C32 1184.3/1510.9; descriptive means within margins",
+    "50-frame window screen, C16/C32 1316.0/1592.2; no peer win",
+    "Three-repeat prompt-cluster quality design frozen before holdout generation;8 synthetic validator controls PASS"
   ],
   "active": [
-    "Coalescing/control speech quality scoring",
-    "Native Talker four-replica quality queued",
-    "Matched peer64-tuning baseline",
-    "Ordinary Talker plus speaker-graph two-vocoder service screen",
-    "Ordinary Talker2/Code2Wav4 speaker-graph screen",
-    "Selective CFM plus speaker graph composition tests/service queued"
+    "Selective CFM window100 service",
+    "FP32 window100 control service",
+    "Temporal-window speech scoring queued",
+    "Independent CPU/GIL diagnostic service initializing"
   ],
   "reserved_holdout_used": false,
   "quality_margins": {
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json
new file mode 100644
index 000000000..b830a0ee0
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json
@@ -0,0 +1,166 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
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+      2,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v1",
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+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP16 CFM estimator/noise/cache; FP32 encoder, speaker and HiFT",
+    "stage0_kv_bytes": 8589934592,
+    "speaker_graph": true,
+    "codec_chunk_frames": 50
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
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+      "inter_chunk_gap_p50_s": 0.2648253464139998,
+      "inter_chunk_gap_p95_s": 0.7029368493240327,
+      "inter_chunk_gap_max_s": 0.8016324387863278
+    }
+  },
+  "quality": {},
+  "quality_status": "Scoring pending",
+  "latency_note": "The same codec window applies to first and subsequent chunks; larger windows increase first-audio delay. See TTFA and first_chunk_mean_s."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_clustered_quality.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_clustered_quality.py
new file mode 100644
index 000000000..6a7cc4144
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_clustered_quality.py
@@ -0,0 +1,95 @@
+"""Aggregate three fixed-seed repetitions within each frozen prompt cluster."""
+
+import argparse
+import json
+import math
+from pathlib import Path
+
+from peer_round2_noninferiority import evaluate
+
+COUNTS = ("substitutions", "deletions", "insertions", "hits")
+
+
+def aggregate(docs, expected_ids):
+    if len(docs) != 3:
+        raise ValueError("Require exactly three measured repetitions")
+    expected = set(expected_ids)
+    if len(expected_ids) != 256 or len(expected) != 256:
+        raise ValueError("Require 256 frozen prompt clusters")
+    for doc in docs:
+        if set(doc["rows"]) != expected or set(doc["tasks"]) != {"wer", "sim", "utmos"}:
+            raise ValueError("Incomplete repetition or mismatched prompt IDs")
+    rows = {}
+    for prompt in sorted(expected):
+        samples = [doc["rows"][prompt] for doc in docs]
+        for sample in samples:
+            counts = sample["wer"]
+            if any(type(counts[k]) is not int or counts[k] < 0 for k in COUNTS):
+                raise ValueError("Invalid WER counts")
+            if not all(math.isfinite(sample[k]) for k in ("sim", "utmos")):
+                raise ValueError("Nonfinite quality scores")
+        words = [sum(s["wer"][k] for k in ("substitutions", "deletions", "hits")) for s in samples]
+        if words[0] <= 0 or len(set(words)) != 1:
+            raise ValueError("Reference denominator changed between repetitions")
+        rows[prompt] = {
+            "wer": {k: sum(s["wer"][k] for s in samples) for k in COUNTS},
+            "sim": sum(s["sim"] for s in samples) / 3,
+            "utmos": sum(s["utmos"] for s in samples) / 3,
+        }
+    return {"rows": rows, "tasks": ["wer", "sim", "utmos"]}
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--plan", type=Path, required=True)
+    parser.add_argument("--repeat-plan", type=Path, required=True)
+    parser.add_argument("--quality-dir", type=Path, required=True)
+    parser.add_argument("--out", type=Path, required=True)
+    args = parser.parse_args()
+    if args.out.exists():
+        raise FileExistsError("Refusing to overwrite an acceptance report")
+    plan = json.loads(args.plan.read_text())
+    repeated = json.loads(args.repeat_plan.read_text())
+    report = {
+        "scope": "Unused 256-prompt holdout, three repetitions clustered by prompt",
+        "bootstrap_unit": "prompt; not individual generated waveform",
+        "cells": {},
+    }
+    try:
+        import hashlib
+
+        if hashlib.sha256(args.plan.read_bytes()).hexdigest() != repeated["base_plan_sha256"]:
+            raise ValueError("Base acceptance plan changed after repeat design was frozen")
+        if repeated["measured_runs"] != [1, 2, 3]:
+            raise ValueError("Unexpected measured repetitions")
+        if set(plan["quality_concurrency"]) != {1, 16, 32}:
+            raise ValueError("Require all three frozen concurrency cells")
+        for concurrency in plan["quality_concurrency"]:
+            merged = []
+            for role in ("main", "candidate"):
+                docs = [
+                    json.loads(
+                        (
+                            args.quality_dir
+                            / f"peer-round2-holdout-{role}-c{concurrency}-run{run}.json"
+                        ).read_text()
+                    )
+                    for run in repeated["measured_runs"]
+                ]
+                merged.append(aggregate(docs, plan["quality_holdout_ids"]))
+            report["cells"][str(concurrency)] = evaluate(
+                *merged, plan["margins"], plan["quality_holdout_ids"]
+            )
+        report["verdict"] = (
+            "PASS"
+            if all(cell["verdict"] == "PASS" for cell in report["cells"].values())
+            else "FAIL"
+        )
+    except (OSError, ValueError, KeyError, TypeError) as exc:
+        report.update(verdict="INCONCLUSIVE", reason=str(exc))
+    args.out.write_text(json.dumps(report, indent=2) + "\n")
+    print(json.dumps(report))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_clustered_quality.py b/evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_clustered_quality.py
new file mode 100644
index 000000000..5908862dd
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_clustered_quality.py
@@ -0,0 +1,77 @@
+"""Acceptance controls use synthetic IDs only; no holdout audio is generated."""
+
+from copy import deepcopy
+
+import pytest
+from peer_round2_clustered_quality import aggregate
+from peer_round2_noninferiority import evaluate
+
+IDS = [f"synthetic-{i:03d}" for i in range(256)]
+MARGINS = {"wer_percentage_points": 0.2, "sim_x100_drop": 0.5, "utmos_drop": 0.05}
+
+
+def document():
+    return {
+        "tasks": ["wer", "sim", "utmos"],
+        "rows": {
+            key: {
+                "wer": {"substitutions": 0, "deletions": 0, "insertions": 0, "hits": 10},
+                "sim": 50.0,
+                "utmos": 4.0,
+            }
+            for key in IDS
+        },
+    }
+
+
+def test_identical_repeats_pass_without_expanding_prompt_count():
+    merged = aggregate([document() for _ in range(3)], IDS)
+    assert len(merged["rows"]) == 256
+    assert merged["rows"][IDS[0]]["wer"]["hits"] == 30
+    result = evaluate(merged, deepcopy(merged), MARGINS, IDS)
+    assert result["n"] == 256
+    assert result["verdict"] == "PASS"
+    assert all(metric["upper_one_sided_95"] == 0 for metric in result["metrics"].values())
+
+
+def test_within_prompt_average_keeps_between_prompt_bootstrap_uncertainty():
+    reference = document()
+    repeats = [document() for _ in range(3)]
+    expected = document()
+    for i, prompt in enumerate(IDS):
+        between = -1 if i < 128 else 1
+        expected["rows"][prompt]["sim"] += between
+        for repeat, within in zip(repeats, (-2, 0, 2), strict=True):
+            repeat["rows"][prompt]["sim"] += between + within
+    measured = evaluate(aggregate([reference] * 3, IDS), aggregate(repeats, IDS), MARGINS, IDS)
+    single_cluster_means = evaluate(reference, expected, MARGINS, IDS)
+    assert measured == single_cluster_means
+    assert measured["metrics"]["sim_x100_drop"]["upper_one_sided_95"] > 0
+
+
+def test_real_degradation_is_not_averaged_away():
+    reference = aggregate([document() for _ in range(3)], IDS)
+    bad = document()
+    for row in bad["rows"].values():
+        row["sim"] -= 1
+    candidate = aggregate([deepcopy(bad) for _ in range(3)], IDS)
+    assert evaluate(reference, candidate, MARGINS, IDS)["verdict"] == "FAIL"
+
+
+@pytest.mark.parametrize(
+    "case", ["missing_run", "missing_id", "denominator", "nonfinite", "negative"]
+)
+def test_incomplete_or_invalid_repetitions_are_rejected(case):
+    docs = [document() for _ in range(3)]
+    if case == "missing_run":
+        docs.pop()
+    elif case == "missing_id":
+        docs[1]["rows"].pop(IDS[0])
+    elif case == "denominator":
+        docs[1]["rows"][IDS[0]]["wer"]["hits"] += 1
+    elif case == "nonfinite":
+        docs[1]["rows"][IDS[0]]["sim"] = float("nan")
+    else:
+        docs[1]["rows"][IDS[0]]["wer"]["insertions"] = -1
+    with pytest.raises(ValueError):
+        aggregate(docs, IDS)

From 6d9c3f864bd0b3b096f1b98d5df7b787e90c8201 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 18:16:12 +0800
Subject: [PATCH 32/40] Record window quality rejections and packed
 conditioning experiment

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |    7 +-
 .../patch/peer-round2-manifest.json           |   13 +-
 ...er-round2-tensor-handoff-composition.patch | 1055 +++++++++++++++++
 .../plan/peer-round2-cpu-profile-retry.json   |    9 +
 .../plan/peer-round2-tensor-handoff.json      |   62 +
 .../plan/peer-round2-window50-coverage.json   |   42 +
 .../peer-round2-fp32-window100-screen.json    |  228 ++++
 .../peer-round2-pipeline-cpu-profile.json     |  879 ++++++++++++++
 .../results/peer-round2-screen-artifact.json  |    7 +-
 .../results/peer-round2-screen-quality.json   |  164 +++
 ...eer-round2-screen-requests-quality.json.gz |  Bin 866977 -> 977391 bytes
 .../results/peer-round2-status.json           |   14 +-
 .../peer-round2-tensor-handoff-micro.json     |  232 ++++
 .../results/peer-round2-window100-screen.json |  228 ++++
 .../peer-round2-window50-covered-screen.json  |  241 ++++
 .../results/peer-round2-window50-screen.json  |   68 +-
 .../peer_round2_bench_tensor_handoff.py       |   76 ++
 .../validator/peer_round2_performance_pair.py |  222 ++++
 .../test_peer_round2_performance_pair.py      |   51 +
 19 files changed, 3582 insertions(+), 16 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-composition.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-cpu-profile-retry.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-tensor-handoff.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-window50-coverage.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-fp32-window100-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-cpu-profile.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-micro.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-window100-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-covered-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_bench_tensor_handoff.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/peer_round2_performance_pair.py
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_performance_pair.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 84a8b2fac..2faef63d8 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -16,9 +16,12 @@ The requester asked to continue until vLLM-Omni exceeds the source-pinned single
 - [Exact Torch speaker graph](results/peer-round2-speaker-graph-wrapper-probe.json): four real references are bitwise equal; component latency falls from about11.4 to4.9ms. Output ownership, shape capacity, policy fallback, and backend integration checks pass. [Service and composition trials](plan/peer-round2-cfm-speaker-composition.json) remain unqualified.
 - [Matched peer tuning workload](results/peer-round2-peer-tuning64.json) reaches C16/C32 1493.4/2544.1 frames/s on the same64 prompt IDs; the unchanged320-request repeated baseline remains the formal target.
 - [Ordinary Talker2 / Code2Wav4 FP32](results/peer-round2-pipeline-replicas-screen.json) reaches C16/C32 1103.9/1423.5 frames/s; [selective CFM FP16 composition](results/peer-round2-cfm-speaker-screen.json) reaches1184.3/1510.9. Both have descriptive means within margins, without confidence-bound qualification.
-- [50-frame window screen](results/peer-round2-window50-screen.json) reaches1316.0/1592.2 frames/s, below the matched peer. C32 TTFA p50/p95 is1.517/1.973s and the first audio chunk averages1.84s. Quality scoring is pending. Larger windows affect first-audio latency and numerical context; this is not equivalent-latency streaming.
+- [50-frame window screen](results/peer-round2-window50-screen.json) reaches1316.0/1592.2 frames/s, below the matched peer. C32 TTFA p50/p95 is1.517/1.973s and the first audio chunk averages1.84s. All descriptive quality means are within margins. Larger windows affect first-audio latency and numerical context; this is not equivalent-latency streaming.
 - [Three-repeat quality design](plan/peer-round2-quality-repeats.json) was frozen before generating any reserved holdout output. The256 paired prompt clusters remain the independent units: sum WER counts and average SIM/UTMOS within each prompt across three fixed-seed runs, then apply unchanged20,000-draw bootstrap and all9 margins. [Validator controls](validator/test_peer_round2_clustered_quality.py) pass8 synthetic cases; this is not a real quality verdict. Earlier FAILs remain unchanged.
-- [Separate CPU/GIL diagnostic](plan/peer-round2-pipeline-cpu-profile.json) is excluded from performance reporting and will guide the next implementation hypothesis.
+- [Same-GPU performance runner](validator/peer_round2_performance_pair.py) is prepared for the selected candidate: clean pinned sources, model hashes, a complete deployment YAML, one visible device, sequential fresh peer/candidate starts, and320 requests ×3 measured repeats at all six concurrencies. Its10 preflight controls pass; no final candidate comparison has run.
+- [CPU/GIL diagnostic](results/peer-round2-pipeline-cpu-profile.json) identified scalar-list storage in Talker as a hypothesis. The100Hz attempt accumulated67s sampling lag and was invalidated; a separate CPU-counter run and sparse2Hz nonblocking samples corroborate the location, without quantitative critical-path attribution. All diagnostic requests are excluded from performance reporting.
+- [Packed conditioning transport plan](plan/peer-round2-tensor-handoff.json) preserves ordinary-turn float32 values using the existing Omni serializer. The [synthetic CPU transport microbenchmark](results/peer-round2-tensor-handoff-micro.json) measures median34.53ms for lists versus0.498ms for packed bytes, with bitwise equal values. Source regression checks pass213 tests with1 existing skip; service gain and speech quality remain unverified.
+- [50-frame exact-coverage contrast](results/peer-round2-window50-covered-screen.json) reaches C16/C32 1367.4/1663.7 but exceeds C1 WER and C32 SIM descriptive margins. [100-frame selective-CFM](results/peer-round2-window100-screen.json) and [FP32 control](results/peer-round2-fp32-window100-screen.json) also fail descriptive quality margins and do not beat the peer.
 - [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
index a697af644..af2e2869b 100644
--- a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
@@ -24,18 +24,23 @@
     "native-coalescing": {
       "source_revision": "e9b12cf223b4a3900f6f30772065eb058550319a",
       "patch": "peer-round2-native-coalescing.patch",
-      "status": "104 scheduler tests and pre-commit PASS; service C16/C32 773.9/904.8, no material gain; quality pending"
+      "status": "104 tests PASS; no material service gain; descriptive quality margins exceeded"
     },
     "speaker-torch-graph": {
       "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
       "patch": "peer-round2-speaker-torch-graph.patch",
-      "status": "Bitwise component and lifecycle gates PASS, service screen pending"
+      "status": "Bitwise component checks PASS; service screen no peer win"
     },
     "cfm-speaker-composition": {
       "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
       "patch": "peer-round2-cfm-speaker-composition.patch",
-      "status": "Composition tests and service queued; no qualification"
+      "status": "113 combined tests PASS; C32 1510.9 with descriptive means within margins; no final qualification"
+    },
+    "tensor-handoff-composition": {
+      "source_revision": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
+      "patch": "peer-round2-tensor-handoff-composition.patch",
+      "status": "213 regression tests and precommit PASS; synthetic CPU transport values bitwise equal; service and speech qualification pending"
     }
   },
-  "note": "Apply each patch independently to the base. Default behavior remains unchanged unless the corresponding opt-in config is enabled. Do not combine or promote failed candidates as a qualified release."
+  "note": "Apply each patch independently to the base. Precision and speaker extensions are opt-in. The packed-turn-handoff composition changes ordinary-turn transport by default while preserving float32 values. Rejected profiles remain rejected; no patch is a qualified peer-beating release."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-composition.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-composition.patch
new file mode 100644
index 000000000..ce8d176c6
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-composition.patch
@@ -0,0 +1,1055 @@
+diff --git a/docs/design/minicpm_o45_mrv2_performance.md b/docs/design/minicpm_o45_mrv2_performance.md
+index b3586ed2b7..a00f751448 100644
+--- a/docs/design/minicpm_o45_mrv2_performance.md
++++ b/docs/design/minicpm_o45_mrv2_performance.md
+@@ -54,6 +54,21 @@ On CUDA, disabling TF32 with `token2wav_allow_tf32: false` or
+ Slot pooling and its `cfm_row_offset_merge` option remain opt-in. Fusion changes
+ floating-point rounding and does not promise identical waveforms.
+ 
++## Turn-mode conditioning transport
++
++Ordinary turn-mode `llm2tts` packs reference audio and thinker hidden states
++with the existing Omni tensor serializer. The request envelope's
++`model_intermediate_buffer` is untyped, so these values cross EngineCore as
++owned bytes and are restored to CPU float32 tensors by the Talker and codec
++bridge. This avoids scalar-list construction, worker list traversal and
++list-to-tensor conversion. Values match the previous list-to-float32 path;
++sampling and acoustic computation are unchanged.
++
++Legacy lists and local tensors remain accepted by consumers. Native duplex
++continues producing its existing lists. Each decode owns its storage, and the
++packed snapshot cannot be changed by later producer mutations. Transport
++microbenchmarks alone do not establish service throughput or speech quality.
++
+ ## Code2Wav batching across reference audio
+ 
+ With CUDA ragged Whole-Euler enabled, ready requests with different reference
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+new file mode 100644
+index 0000000000..39c416ddaf
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+@@ -0,0 +1,57 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Tiled attention must preserve masking and pooled-row ownership in FP16."""
++
++import pytest
++import torch
++import torch.nn.functional as F
++from torch.nn.attention import SDPBackend, sdpa_kernel
++
++from tests.helpers.mark import hardware_marks
++from vllm_omni.model_executor.models.minicpmo_4_5.cfm_attention import cfm_attention
++
++pytestmark = [pytest.mark.core_model, *hardware_marks(res={"cuda": "L4"}, num_cards=1)]
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++@pytest.mark.parametrize("pooled", [False, True])
++@pytest.mark.parametrize("masked", [False, True])
++@pytest.mark.parametrize("frames,history", [(1, 17), (23, 65), (50, 513)])
++def test_tiled_attention_matches_math_sdpa(dtype, pooled, masked, frames, history):
++    generator = torch.Generator(device="cuda").manual_seed(43)
++    batch, heads, width = 3, 4, 64
++    q = torch.randn(batch, heads, frames, width, device="cuda", dtype=dtype, generator=generator)
++    # K and V are interleaved in the real resident pool, so both views are strided.
++    storage = torch.randn(
++        7 if pooled else batch, heads, history, 2 * width, device="cuda", dtype=dtype, generator=generator
++    )
++    k, v = storage[..., :width], storage[..., width:]
++    rows = torch.tensor([5, 1, 5], device="cuda") if pooled else None
++    mask = None
++    if masked:
++        mask = torch.rand(batch, frames, history, device="cuda", generator=generator) > 0.3
++        mask[0, 0] = False
++    expected_k = k.index_select(0, rows) if pooled else k
++    expected_v = v.index_select(0, rows) if pooled else v
++    with sdpa_kernel(SDPBackend.MATH):
++        expected = F.scaled_dot_product_attention(
++            q.float(),
++            expected_k.float(),
++            expected_v.float(),
++            attn_mask=mask.unsqueeze(1) if mask is not None else None,
++        ).to(dtype)
++    actual = cfm_attention(q, k, v, mask, rows)
++    torch.testing.assert_close(actual, expected, atol=2e-3, rtol=2e-3)
++    assert torch.isfinite(actual).all()
++    if masked:
++        assert torch.count_nonzero(actual[0, :, 0]) == 0
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++def test_tiled_attention_rejects_mixed_cache_dtype(dtype):
++    q = torch.empty(1, 1, 1, 16, dtype=dtype)
++    cache_dtype = torch.float16 if dtype == torch.float32 else torch.float32
++    k = torch.empty_like(q, dtype=cache_dtype)
++    with pytest.raises(ValueError, match="matching float32 or float16"):
++        cfm_attention(q, k, k)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+index 8a6b81a8fc..5db1e06a76 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+@@ -37,11 +37,15 @@ class _FakeToken2Wav:
+         self.device_spk_calls = 0
+         self.trt_spk_calls = 0
+         self.device_spk_use_trt = None
++        self.speaker_graph_config = None
+ 
+     def enable_device_spk_embedding(self, *, use_trt=True):
+         self.device_spk_calls += 1
+         self.device_spk_use_trt = use_trt
+ 
++    def enable_speaker_cuda_graph(self, config):
++        self.speaker_graph_config = config
++
+     def enable_trt_spk_embedding(self, *, cpu_reference=False):
+         self.trt_spk_calls += 1
+         self.trt_cpu_reference = cpu_reference
+@@ -150,6 +154,7 @@ def test_cuda_speaker_backend_preserves_lazy_model_loading(tmp_path, monkeypatch
+ 
+ 
+ _OTHER_DEFAULTS = {
++    "token2wav_spk_cuda_graph",
+     "token2wav_spk_cpu_reference",
+     "token2wav_float16",
+     "token2wav_trt",
+@@ -295,3 +300,12 @@ def test_facade_forwards_speaker_reference_policy(mocker, cpu_reference):
+     facade._core = core
+     facade.enable_trt_spk_embedding(cpu_reference=cpu_reference)
+     core.enable_trt_spk_embedding.assert_called_once_with(cpu_reference=cpu_reference)
++
++
++@pytest.mark.parametrize("value,enabled", [(True, True), ("true", True), (False, False), ("false", False)])
++def test_speaker_graph_flag_reaches_selected_backend(tmp_path, monkeypatch, value, enabled):
++    monkeypatch.setattr(current_omni_platform, "is_cuda", lambda: True)
++    monkeypatch.setattr(current_omni_platform, "is_npu", lambda: False)
++    model, speaker = _build_backend(tmp_path, monkeypatch, {"token2wav_spk_cuda_graph": value})
++    assert speaker.device_spk_calls == 1
++    assert speaker.speaker_graph_config is (model.vllm_config if enabled else None)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+index 3cf8bdd941..e40424b57c 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+@@ -44,14 +44,17 @@ def _run(body, estimator, *, rows: int, frames: int, cached: int, lengths):
+     channels = estimator.blocks[0].conv.block[1].in_channels
+     attn = estimator.blocks[0].attn
+     device = next(estimator.parameters()).device
+-    estimator_input = torch.randn(rows, 320, frames, device=device)
+-    time_embedding = estimator.t_embedder(torch.rand((), device=device).expand(rows)).unsqueeze(1)
++    dtype = next(estimator.parameters()).dtype
++    estimator_input = torch.randn(rows, 320, frames, device=device, dtype=dtype)
++    time_embedding = estimator.t_embedder(torch.rand((), device=device, dtype=dtype).expand(rows)).unsqueeze(1)
+     mask = torch.rand(rows, frames, cached + frames, device=device) > 0.3
+     mask[..., 0] = True
+-    cnn = [torch.randn(rows, 2 * channels, 2, device=device) for _ in range(depth)]
+-    att = [torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device) for _ in range(depth)]
+-    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device)
+-    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device)
++    cnn = [torch.randn(rows, 2 * channels, 2, device=device, dtype=dtype) for _ in range(depth)]
++    att = [
++        torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device, dtype=dtype) for _ in range(depth)
++    ]
++    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device, dtype=dtype)
++    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device, dtype=dtype)
+     with torch.no_grad():
+         out = body(estimator, estimator_input, time_embedding, mask, cnn, att, cnn_out, att_out, lengths)
+     return out, cnn_out, att_out
+@@ -93,3 +96,64 @@ def test_ragged_body_reuses_modulation_without_recomputing_adaln(monkeypatch, ca
+     actual = _run(precomputed, estimator, rows=4, frames=6, cached=cached, lengths=[6, 4])
+     for want, got in zip(expected, actual, strict=True):
+         torch.testing.assert_close(got, want, rtol=1e-4, atol=2e-5)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_fp16_fused_body_matches_fp16_ragged_body(monkeypatch):
++    estimator = _upstream_dit("cuda").half()
++    driver = BatchedToken2Wav.__new__(BatchedToken2Wav)
++    nn.Module.__init__(driver)
++    driver._ragged_fused_body = True
++    calls = []
++
++    def fused(*args, **kwargs):
++        calls.append(True)
++        return blocks_forward_chunk_fused(*args, **kwargs)
++
++    monkeypatch.setattr(
++        "vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav.blocks_forward_chunk_fused",
++        fused,
++    )
++    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.float16):
++        expected = _run(
++            BatchedToken2Wav._blocks_forward_chunk_ragged,
++            estimator,
++            rows=4,
++            frames=6,
++            cached=5,
++            lengths=[6, 4],
++        )
++        actual = _run(driver._ragged_body, estimator, rows=4, frames=6, cached=5, lengths=[6, 4])
++    assert calls, "FP16 service dispatch must use the fused body"
++    for want, got in zip(expected, actual, strict=True):
++        torch.testing.assert_close(got, want, rtol=2e-3, atol=2e-3)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_cfm_only_fp16_preserves_encoder_precision_and_returns_half_caches():
++    from tests.model_executor.models.minicpmo_4_5.test_code2wav_batching import _FakeToken2Wav
++
++    token2wav = _FakeToken2Wav()
++    token2wav.flow.encoder.register_parameter("anchor", nn.Parameter(torch.ones(1, device="cuda")))
++    token2wav.flow.decoder.estimator = _upstream_dit("cuda")
++    token2wav.flow.decoder.rand_noise = torch.randn(1, 80, 100, device="cuda")
++    backend = BatchedToken2Wav(token2wav, cfm_float16=True)
++    assert not backend.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
++    assert next(token2wav.flow.decoder.estimator.parameters()).dtype == torch.float16
++    matrix = torch.randn(8, 8, device="cuda")
++    with backend._autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float32
++    with backend._cfm_autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float16
++    assert not torch.is_autocast_enabled("cuda")
++    with torch.inference_mode():
++        mel, cnn, att = backend._decode_cfm(
++            torch.randn(1, 80, 6, device="cuda"),
++            torch.randn(1, 80, device="cuda"),
++            torch.randn(1, 80, 6, device="cuda"),
++            cnn_cache=None,
++            att_cache=None,
++        )
++    assert mel.dtype == cnn.dtype == att.dtype == torch.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py b/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
+index d93755fec0..e10fecfc92 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
+@@ -22,6 +22,7 @@ from types import SimpleNamespace
+ import pytest
+ import torch
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_omni import (
+     MiniCPMO45OmniForConditionalGeneration,
+ )
+@@ -149,7 +150,10 @@ class TestBasicShape:
+         out = llm2tts([thinker_output], prompt=None)
+ 
+         assert out[0]["prompt_token_ids"] == [0, 0, 0]
+-        assert torch.equal(torch.tensor(out[0]["model_intermediate_buffer"]["hidden_states"]["tts"]), hidden[1:])
++        assert torch.equal(
++            torch.as_tensor(unpack_handoff_tensor(out[0]["model_intermediate_buffer"]["hidden_states"]["tts"])),
++            hidden[1:],
++        )
+ 
+     def test_returns_one_entry_per_input(self) -> None:
+         hidden = torch.zeros((3, _HIDDEN_DIM))
+@@ -210,7 +214,7 @@ class TestBasicShape:
+         buffer = result["model_intermediate_buffer"]
+         assert result["prompt_token_ids"] == [0, 0, 0, 0]
+         assert buffer["ids"]["tts"] == [20, 21]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[2:4])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[2:4])
+ 
+     def test_latent_in_multimodal_output_takes_precedence(self) -> None:
+         # When both ``multimodal_output["latent"]`` and ``hidden_states`` are
+@@ -234,7 +238,9 @@ class TestBasicShape:
+         )
+         buffer = result[0]["model_intermediate_buffer"]
+         # latent (ones) won over hidden_states (zeros)
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), latent[3:4].to(torch.float32))
++        assert torch.equal(
++            torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), latent[3:4].to(torch.float32)
++        )
+ 
+ 
+ class TestTtsRegionDetection:
+@@ -269,7 +275,7 @@ class TestTtsRegionDetection:
+         # 4.5 BOS at idx 2 -> slice starts at 3; end at idx 5 -> slice ends at 5.
+         buffer, hidden = self._run([10, 11], [151703, 30, 31, tts_end_id, 40])
+         assert buffer["ids"]["tts"] == [30, 31]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[3:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[3:5])
+ 
+     def test_bos_without_eos_runs_to_end(self) -> None:
+         # When BOS is found but EOS is missing (typical for an in-flight or
+@@ -278,12 +284,12 @@ class TestTtsRegionDetection:
+         # sequence: [10, 11, 151703, 30, 31]
+         buffer, hidden = self._run([10, 11], [151703, 30, 31])
+         assert buffer["ids"]["tts"] == [30, 31]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[3:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[3:5])
+ 
+     def test_plain_chat_without_tts_markers_uses_assistant_span(self) -> None:
+         buffer, hidden = self._run([10, 11], [20, 21, 22])
+         assert buffer["ids"]["tts"] == [20, 21, 22]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[2:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[2:5])
+ 
+ 
+ class TestPromptAndMultiModal:
+@@ -325,7 +331,7 @@ class TestPromptAndMultiModal:
+         )
+ 
+         intermediate_buffer = stage_outputs[0]["model_intermediate_buffer"]
+-        assert intermediate_buffer["codes"]["ref"] == [0.25, -0.5]
++        assert torch.equal(unpack_handoff_tensor(intermediate_buffer["codes"]["ref"]), torch.tensor([0.25, -0.5]))
+         assert intermediate_buffer["meta"]["ref_audio_sr"] == 16000
+ 
+     def test_serving_reference_audio_is_added_to_stage_handoff(self) -> None:
+@@ -338,7 +344,7 @@ class TestPromptAndMultiModal:
+         )
+ 
+         intermediate_buffer = stage_outputs[0]["model_intermediate_buffer"]
+-        assert intermediate_buffer["codes"]["ref"] == [0.125, -0.25]
++        assert torch.equal(unpack_handoff_tensor(intermediate_buffer["codes"]["ref"]), torch.tensor([0.125, -0.25]))
+         assert intermediate_buffer["meta"]["ref_audio_sr"] == 24000
+ 
+     def test_missing_reference_audio_does_not_add_stage_handoff_fields(self) -> None:
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..0b739fade8
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+@@ -0,0 +1,81 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++from types import SimpleNamespace
++
++import pytest
++import torch
++from vllm.config import ModelConfig, VllmConfig
++
++from tests.helpers.mark import hardware_test
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++pytestmark = [pytest.mark.core_model]
++
++
++class _Speaker(torch.nn.Module):
++    def forward(self, x):
++        return x.mean(dim=1)
++
++
++def _config():
++    config = VllmConfig()
++    config.model_config = ModelConfig.__new__(ModelConfig)
++    config.model_config.multimodal_config = None
++    return config
++
++
++@pytest.mark.cpu
++def test_cpu_fallback_does_not_mutate_shared_model_or_config():
++    speaker = CampplusTorch(_Speaker(), "cpu")
++    config = _config()
++    wrapper = SpeakerCudaGraph(speaker, config)
++    feat = torch.randn(17, 80, dtype=torch.bfloat16)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert config.model_config.multimodal_config is None
++    assert wrapper.graph.vllm_config.model_config.multimodal_config is not None
++    assert not wrapper.graph.graphs
++    assert wrapper.speaker is speaker
++
++
++@pytest.mark.cpu
++def test_facade_rejects_non_torch_speaker():
++    from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_token2wav import MiniCPMO45Token2wav
++
++    facade = MiniCPMO45Token2wav.__new__(MiniCPMO45Token2wav)
++    facade._core = SimpleNamespace(_spk_model=object())
++    with pytest.raises(ValueError, match="CUDA Torch speaker"):
++        facade.enable_speaker_cuda_graph(_config())
++
++
++@hardware_test(res={"cuda": "L4"}, num_cards=1)
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA required")
++@torch.inference_mode()
++def test_replay_ownership_shape_capacity_and_precision_fallback():
++    speaker = CampplusTorch(_Speaker(), "cuda:0")
++    wrapper = SpeakerCudaGraph(speaker, _config(), max_graphs=1)
++    feat = torch.randn(17, 80, device="cuda")
++    wrapper(feat)
++    retained = wrapper(feat)
++    expected = speaker(feat).clone()
++    feat.add_(3)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert torch.equal(retained, expected)
++    assert len(wrapper.graph.graphs) == 1
++    other = torch.randn(19, 80, device="cuda")
++    assert torch.equal(wrapper(other), speaker(other))
++    assert len(wrapper.graph.graphs) == 1
++    hits = wrapper.graph.get_cumulative_stats()["graph_hits"]
++    original = torch.backends.cudnn.allow_tf32
++    try:
++        torch.backends.cudnn.allow_tf32 = not original
++        assert torch.equal(wrapper(feat), speaker(feat))
++        assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits
++    finally:
++        torch.backends.cudnn.allow_tf32 = original
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
++    with torch.autocast("cuda", dtype=torch.bfloat16):
++        assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py b/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
+index fc3b66cb36..eadfda43e7 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
+@@ -13,6 +13,7 @@ import torch
+ import torch.nn as nn
+ from torch.overrides import TorchFunctionMode
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_omni import (
+     MiniCPMO45OmniForConditionalGeneration,
+ )
+@@ -1049,7 +1050,8 @@ def test_empty_speech_segment_finishes_without_sampling_codes() -> None:
+     assert decode_updates["codes"]["audio"].shape == (0,)
+ 
+ 
+-def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker) -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker, packed) -> None:
+     talker = _make_talker()
+     talker.emb_text = nn.Embedding(1, 2)
+     condition = torch.arange(18, dtype=torch.float32).reshape(9, 2)
+@@ -1063,7 +1065,7 @@ def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker) -> Non
+         _omni_prompt_len=68,
+         request_id="req-chunked-prefill",
+         tts_token_ids=torch.tensor([1]),
+-        tts_hidden_states=torch.ones(1, 2),
++        tts_hidden_states=pack_handoff_tensor(torch.ones(1, 2)) if packed else torch.ones(1, 2),
+     )
+ 
+     assert torch.equal(embeds, condition)
+diff --git a/tests/model_executor/models/test_minicpmo_handoff.py b/tests/model_executor/models/test_minicpmo_handoff.py
+new file mode 100644
+index 0000000000..f861646fab
+--- /dev/null
++++ b/tests/model_executor/models/test_minicpmo_handoff.py
+@@ -0,0 +1,51 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++from typing import Any
++
++import pytest
++import torch
++from vllm.v1.serial_utils import MsgpackDecoder, MsgpackEncoder
++
++from vllm_omni.distributed.omni_connectors.utils.serialization import OmniSerializer
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor, unpack_handoff_tensor
++
++pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float64, torch.bfloat16])
++@pytest.mark.parametrize("shape", [(), (0, 4), (3, 4), (144000,)])
++def test_packed_handoff_matches_legacy_values_across_untyped_wire(dtype, shape):
++    source = (
++        torch.linspace(-1.23456789, 1.987654321, int(torch.tensor(shape).prod().item()), dtype=torch.float64)
++        .reshape(shape)
++        .to(dtype)
++    )
++    if source.ndim == 2:
++        source = source.t()
++    expected = torch.tensor(source.tolist(), dtype=torch.float32).reshape(source.shape)
++    packed = pack_handoff_tensor(source)
++    envelope = {"model_intermediate_buffer": {"hidden_states": {"tts": packed}}}
++    # The real request field is dict[str, Any]: raw tensors cannot rely on a
++    # typed decoder hook here. Only standard bytes cross this boundary.
++    received = MsgpackDecoder(dict[str, Any]).decode(MsgpackEncoder().encode(envelope))
++    actual = unpack_handoff_tensor(received["model_intermediate_buffer"]["hidden_states"]["tts"])
++    assert isinstance(actual, torch.Tensor)
++    assert actual.shape == source.shape
++    assert torch.equal(actual, expected)
++    source.fill_(-7)
++    assert torch.equal(actual, expected)
++    other = unpack_handoff_tensor(packed)
++    actual.fill_(9)
++    assert torch.equal(other, expected)
++
++
++def test_legacy_handoff_values_remain_supported():
++    for value in (None, [1.0, 2.0], torch.ones(2)):
++        assert unpack_handoff_tensor(value) is value
++
++
++@pytest.mark.parametrize("payload", ["not a tensor", [1.0], torch.ones(2, dtype=torch.int64)])
++def test_invalid_packed_type_rejected(payload):
++    with pytest.raises(ValueError, match="CPU float32 tensor"):
++        unpack_handoff_tensor(OmniSerializer.serialize(payload))
+diff --git a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
+index 13036689ba..c3b8e69f90 100644
+--- a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
++++ b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
+@@ -8,6 +8,7 @@ import pytest
+ import torch
+ from vllm.v1.request import RequestStatus
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor
+ from vllm_omni.model_executor.stage_input_processors.minicpmo_4_5_omni import (
+     _extract_codec_delta,
+     tts2code2wav_async_chunk,
+@@ -237,11 +238,12 @@ def test_duplex_final_segment_preserves_every_code_and_closes_once(
+     assert not duplicate.meta.last_chunk
+ 
+ 
+-def test_first_chunk_forwards_reference_voice_and_duplex_identity() -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_first_chunk_forwards_reference_voice_and_duplex_identity(packed) -> None:
+     manager = _manager()
+     request = _request("req")
+     request.model_intermediate_buffer = {
+-        "codes": {"ref": [0.1, -0.1]},
++        "codes": {"ref": pack_handoff_tensor(torch.tensor([0.1, -0.1])) if packed else [0.1, -0.1]},
+         "meta": {"ref_audio_sr": 16000},
+     }
+     request.additional_information = {
+@@ -292,11 +294,12 @@ def test_first_chunk_falls_back_to_legacy_reference_fields() -> None:
+     assert payload.meta.ref_audio_sr == 16000
+ 
+ 
+-def test_full_payload_forwards_all_codes_and_request_metadata() -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_full_payload_forwards_all_codes_and_request_metadata(packed) -> None:
+     manager = _manager()
+     request = _request("req")
+     request.model_intermediate_buffer = {
+-        "codes": {"ref": [0.1, -0.1]},
++        "codes": {"ref": pack_handoff_tensor(torch.tensor([0.1, -0.1])) if packed else [0.1, -0.1]},
+         "meta": {
+             "ref_audio_sr": 16000,
+             "native_duplex_segment_text": "hello",
+diff --git a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
+index edb5a3535f..c9c385cc70 100644
+--- a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
++++ b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
+@@ -7,6 +7,7 @@ import pytest
+ import torch
+ 
+ from vllm_omni.engine.orchestrator import StreamingInputState
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.stage_input_processors.minicpmo_4_5_omni import (
+     _extract_first_audio_ref,
+     llm2tts,
+@@ -71,7 +72,7 @@ def test_plain_chat_handoff_owns_talker_prompt_contract() -> None:
+ 
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == output_ids
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[2:4])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[2:4])
+     assert converted["prompt_token_ids"] == [0, 0, 0, 0]
+     assert info["meta"]["replace_streaming_prompt"] is True
+     assert info["meta"]["next_stage_prompt_len"] == 4
+@@ -98,7 +99,7 @@ def test_llm2tts_carries_request_ref_audio() -> None:
+     )[0]
+ 
+     info = converted["model_intermediate_buffer"]
+-    assert info["codes"]["ref"] == ref_waveform.tolist()
++    assert torch.equal(unpack_handoff_tensor(info["codes"]["ref"]), ref_waveform)
+     assert info["meta"]["ref_audio_sr"] == 22050
+     assert info["ids"]["tts"] == [11, 12]
+ 
+@@ -191,7 +192,7 @@ def test_native_duplex_uses_forwarded_row_ledger_after_later_audio_prefill() ->
+ 
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_selects_latest_contiguous_forwarded_span() -> None:
+@@ -224,7 +225,7 @@ def test_native_duplex_selects_latest_contiguous_forwarded_span() -> None:
+     converted = llm2tts([source], prompt=[{}], _streaming_context=context)[0]
+ 
+     info = converted["model_intermediate_buffer"]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[5:7])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[5:7])
+ 
+ 
+ def test_native_duplex_rejects_missing_forwarded_terminal_token() -> None:
+@@ -303,7 +304,7 @@ def test_native_duplex_ledger_tolerates_async_lookahead_row_after_terminator() -
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_ledger_without_forwarded_terminator() -> None:
+@@ -317,7 +318,7 @@ def test_native_duplex_ledger_without_forwarded_terminator() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_turn_eos_row_is_handed_to_talker() -> None:
+@@ -333,7 +334,7 @@ def test_native_duplex_turn_eos_row_is_handed_to_talker() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 9310]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+     assert info["meta"]["turn_end"] is True
+ 
+ 
+@@ -351,7 +352,7 @@ def test_native_duplex_ledger_anchors_on_unit_after_reinjected_listens() -> None
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[9:11])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[9:11])
+ 
+ 
+ @pytest.mark.parametrize("previous_terminator_forwarded", [False, True])
+@@ -372,7 +373,10 @@ def test_native_duplex_ledger_prefers_latest_repeat_of_the_unit(
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[current_start + 1 : current_start + 3])
++    assert torch.equal(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])),
++        latent[current_start + 1 : current_start + 3],
++    )
+ 
+ 
+ def test_native_duplex_ledger_rejects_non_contiguous_positions() -> None:
+@@ -397,7 +401,7 @@ def test_native_duplex_mid_turn_tts_bos_slices_after_boundary() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ @pytest.mark.parametrize("opening", [9304, 9301])
+@@ -417,7 +421,9 @@ def test_native_duplex_mid_unit_tts_bos_keeps_earlier_text(opening, turn_end) ->
+ 
+     expected = [21, 22, 9301, 9310] if turn_end else [21, 22, 9301]
+     assert info["ids"]["tts"] == expected
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[3 : 3 + len(expected)])
++    torch.testing.assert_close(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3 : 3 + len(expected)]
++    )
+     assert info.get("meta", {}).get("turn_end", False) is turn_end
+ 
+ 
+@@ -435,7 +441,9 @@ def test_native_duplex_folded_boundary_with_mid_unit_tts_bos(terminator) -> None
+ 
+     expected = [21, 22, 9301, *terminator[:-1]]
+     assert info["ids"]["tts"] == expected
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[2 : 2 + len(expected)])
++    torch.testing.assert_close(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[2 : 2 + len(expected)]
++    )
+ 
+ 
+ @pytest.mark.parametrize("folded_decisions", [0, 1, 2])
+@@ -471,7 +479,7 @@ def test_native_duplex_tts_bos_aligns_after_window_rebuild(folded_decisions, bos
+     converted = llm2tts([source], prompt=[{}], _streaming_context=SimpleNamespace(bridge_states={}))[0]
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == [21, 22]
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[-3:-1])
++    torch.testing.assert_close(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[-3:-1])
+ 
+ 
+ def test_native_duplex_continuation_appends_only_new_talker_condition() -> None:
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+index 3e9c849670..96bf8528d1 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+@@ -322,14 +322,20 @@ def _cfm_matmul_tf32(fn):
+ 
+     @functools.wraps(fn)
+     def wrapper(self, *args, **kwargs):
+-        if not getattr(self, "_cfm_tf32", False):
+-            return fn(self, *args, **kwargs)
+-        previous = torch.backends.cuda.matmul.allow_tf32
+-        torch.backends.cuda.matmul.allow_tf32 = True
+-        try:
+-            return fn(self, *args, **kwargs)
+-        finally:
+-            torch.backends.cuda.matmul.allow_tf32 = previous
++        precision = (
++            self._cfm_autocast(next(self.flow.parameters()).device)
++            if getattr(self, "_cfm_only_float16", False)
++            else nullcontext()
++        )
++        with precision:
++            if not getattr(self, "_cfm_tf32", False):
++                return fn(self, *args, **kwargs)
++            previous = torch.backends.cuda.matmul.allow_tf32
++            torch.backends.cuda.matmul.allow_tf32 = True
++            try:
++                return fn(self, *args, **kwargs)
++            finally:
++                torch.backends.cuda.matmul.allow_tf32 = previous
+ 
+     return wrapper
+ 
+@@ -355,6 +361,7 @@ class BatchedToken2Wav(nn.Module):
+         setup_cache_size: int = 1,
+         cfm_tf32: bool = False,
+         encoder_graph_config: Mapping[str, Any] | None = None,
++        cfm_float16: bool = False,
+     ):
+         super().__init__()
+         if setup_cache_size < 0:
+@@ -371,6 +378,13 @@ class BatchedToken2Wav(nn.Module):
+         self.flow = token2wav.flow
+         self.hift = token2wav.hift
+         flow_parameter = next(self.flow.parameters(), None)
++        self._cfm_only_float16 = bool(cfm_float16 and not token2wav.float16)
++        if self._cfm_only_float16:
++            if flow_parameter is None or flow_parameter.device.type != "cuda":
++                raise ValueError("cfm_float16 requires CUDA")
++            self.flow.decoder.estimator.half()
++            self.flow.decoder.rand_noise = self.flow.decoder.rand_noise.half()
++
+         if flow_parameter is not None and flow_parameter.device.type == "npu":
+             from vllm_omni.platforms.npu.models.minicpmo_fused import prepare_estimator
+ 
+@@ -431,7 +445,7 @@ class BatchedToken2Wav(nn.Module):
+             del speech, source
+             torch.accelerator.empty_cache()
+         self.float16 = bool(token2wav.float16)
+-        self._estimator_att_compute_dtype = torch.float16 if self.float16 else torch.float32
++        self._estimator_att_compute_dtype = torch.float16 if self.float16 or self._cfm_only_float16 else torch.float32
+         self._estimator_att_cache_dtype = (
+             torch.bfloat16 if bfloat16_attention_cache else self._estimator_att_compute_dtype
+         )
+@@ -494,17 +508,25 @@ class BatchedToken2Wav(nn.Module):
+                 micro_batch_size = int(micro_batch_size_cfg) if micro_batch_size_cfg is not None else 4
+                 enable_whole_euler = bool(cfm_graph_cfg.get("enable_whole_euler", True))
+                 if bool(cfm_graph_cfg.get("fused_body", False)):
+-                    # A reduced-precision attention cache keeps the ragged body,
+-                    # which attends in the activation dtype through upstream.
++                    # A BF16 storage-only cache still uses the ragged body.
++                    # CUDA FP16 flow can keep its matching FP16 cache resident.
+                     # NPU uses the same schedule with AddLayerNorm and packed QKV.
+                     self._ragged_fused_body = (
+                         flow_parameter.device.type in {"cuda", "npu"}
+                         and supports_fused_body(estimator)
+-                        and self._estimator_att_cache_dtype == torch.float32
++                        and (
++                            self._estimator_att_cache_dtype == torch.float32
++                            or (
++                                flow_parameter.device.type == "cuda"
++                                and self._estimator_att_cache_dtype == torch.float16
++                                and self._estimator_att_compute_dtype == torch.float16
++                            )
++                        )
+                     )
+                     if not self._ragged_fused_body:
+                         logger.warning(
+-                            "cfm_fused_body requested but unsupported here (DiT blocks or a non-fp32 attention cache)"
++                            "cfm_fused_body requested but unsupported here "
++                            "(DiT blocks or incompatible attention cache dtype)"
+                         )
+                 # Resident request caches need the fused body and its tiled
+                 # attention, which reads keys/values out of the pool in place.
+@@ -688,6 +710,11 @@ class BatchedToken2Wav(nn.Module):
+             projected = torch.cat([self._project_speakers(feature.speaker_embedding) for feature in features])
+         return [int(feature.mels.shape[1]) for feature in features], projected
+ 
++    def _cfm_autocast(self, device: torch.device):
++        if self._cfm_only_float16:
++            return torch.amp.autocast(device.type, dtype=torch.float16)
++        return self._autocast(device)
++
+     def _autocast(self, device: torch.device):
+         if device.type != "cuda":
+             return nullcontext()
+@@ -1086,7 +1113,10 @@ class BatchedToken2Wav(nn.Module):
+         ``modulation`` comes from the Whole-Euler arena, for either body.
+         """
+         estimator_input = args[1]
+-        if slots is not None or (self._ragged_fused_body and estimator_input.dtype == torch.float32):
++        fused_dtype = estimator_input.dtype == torch.float32 or (
++            estimator_input.is_cuda and estimator_input.dtype == torch.float16
++        )
++        if slots is not None or (self._ragged_fused_body and fused_dtype):
+             # Slot-pool graphs are only built over the fused body (``slot_pool`` above).
+             if estimator_input.device.type == "npu":
+                 from vllm_omni.platforms.npu.models.minicpmo_fused import (
+@@ -1339,6 +1369,8 @@ class BatchedToken2Wav(nn.Module):
+         cache in the same form, already trimmed by ``att_keep``; the eager
+         path returns it stacked and untrimmed (ragged: per request, untrimmed).
+         """
++        if self._cfm_only_float16:
++            mu, speakers, cond = mu.half(), speakers.half(), cond.half()
+         decoder = self.flow.decoder
+         estimator = decoder.estimator
+         batch_size = int(mu.shape[0])
+@@ -1734,7 +1766,7 @@ class BatchedToken2Wav(nn.Module):
+         wrapper = self._whole_euler_graph_wrapper
+         prompt_len = int(features.mels.shape[1])
+         steady = prompt_len + _CACHE_TRIM_SUFFIX
+-        with self._autocast(wrapper.device):
++        with self._cfm_autocast(wrapper.device):
+             return wrapper.precapture(
+                 offsets=range(prompt_len, steady + 1),
+                 steady=steady,
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+index 3ab3f7f96a..e64fcd2f82 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+@@ -1,6 +1,6 @@
+ # SPDX-License-Identifier: Apache-2.0
+ # SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+-"""Tiled CFM attention: float32 tensors, ordinary TF32 Tensor Core dots."""
++"""Tiled CFM attention with FP32/TF32 or FP16 Tensor Core dots."""
+ 
+ import torch
+ from vllm.triton_utils import tl, triton
+@@ -80,7 +80,7 @@ def _attention(
+             (keys[:, None] < nk) & (ds[None, :] < dim),
+             0,
+         )
+-        accumulator = accumulator * correction[:, None] + tl.dot(prob, values, input_precision="tf32")
++        accumulator = accumulator * correction[:, None] + tl.dot(prob.to(values.dtype), values, input_precision="tf32")
+         maximum = new_max
+     result = accumulator / tl.where(denominator > 0, denominator, 1.0)[:, None]
+     tl.store(
+@@ -98,11 +98,11 @@ def cfm_attention(
+     mask: torch.Tensor | None = None,
+     kv_rows: torch.Tensor | None = None,
+ ) -> torch.Tensor:
+-    """Tiled attention with TF32 dots; optional ``kv_rows`` indexes a pooled K/V cache."""
++    """Tiled attention; optional ``kv_rows`` indexes a pooled K/V cache in place."""
+     b, heads, nq, dim = q.shape
+     nk = k.shape[2]
+-    if q.dtype != torch.float32 or k.dtype != torch.float32 or v.dtype != torch.float32:
+-        raise ValueError("CFM tiled attention requires float32 Q/K/V")
++    if q.dtype not in (torch.float32, torch.float16) or k.dtype != q.dtype or v.dtype != q.dtype:
++        raise ValueError("CFM tiled attention requires matching float32 or float16 Q/K/V")
+     num_stages = 2
+     out = torch.empty((b, nq, heads, dim), device=q.device, dtype=q.dtype)
+     _attention[(b, heads, triton.cdiv(nq, 32))](
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py b/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py
+new file mode 100644
+index 0000000000..00314dfc12
+--- /dev/null
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py
+@@ -0,0 +1,32 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Owned CPU tensor snapshots for the untyped turn-mode request envelope."""
++
++import torch
++
++from vllm_omni.distributed.omni_connectors.utils.serialization import OmniSerializer
++
++
++def pack_handoff_tensor(value: torch.Tensor) -> bytes:
++    """Keep legacy list-to-float32 values without creating Python scalar lists.
++
++    EngineCore's ``model_intermediate_buffer`` has Any-valued fields, so raw
++    tensors would lose their type on its msgpack wire. The existing Omni codec
++    packs an owned byte snapshot and restores the dtype/shape at the consumer.
++    """
++    tensor = value.detach().to(device="cpu", dtype=torch.float32).contiguous()
++    if tensor.numel() == 0:
++        # Empty transposed tensors may report contiguous with a nonunit last
++        # stride; the shared codec reinterprets that dimension as bytes.
++        tensor = torch.empty(tensor.shape, dtype=torch.float32)
++    return OmniSerializer.serialize(tensor)
++
++
++def unpack_handoff_tensor(value: object) -> object:
++    """Accept existing local tensors/lists as well as packed turn handoffs."""
++    if not isinstance(value, bytes):
++        return value
++    tensor = OmniSerializer.deserialize(value)
++    if not isinstance(tensor, torch.Tensor) or tensor.dtype != torch.float32 or tensor.device.type != "cpu":
++        raise ValueError("MiniCPM-o packed handoff must contain a CPU float32 tensor")
++    return tensor
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+index 4fdbe44879..1b8aeaee6d 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+@@ -1607,6 +1607,9 @@ class MiniCPMO45Code2Wav(nn.Module):
+                     "MiniCPM-o Code2Wav: campplus speaker embedding falling back to CPU onnxruntime "
+                     "(token2wav_device_spk=false)"
+                 )
++        if read_bool_flag(extra, "token2wav_spk_cuda_graph", False):
++            token2wav.enable_speaker_cuda_graph(self.vllm_config)
++            logger.info("MiniCPM-o Code2Wav: exact-shape Torch speaker CUDA graphs enabled")
+         self.backend = BatchedToken2Wav(
+             token2wav,
+             trt_stepper=trt_stepper,
+@@ -1618,6 +1621,7 @@ class MiniCPMO45Code2Wav(nn.Module):
+             setup_cache_size=self._setup_cache_size,
+             cfm_tf32=tf32_mode != "off",
+             encoder_graph_config=self._encoder_graph_config,
++            cfm_float16=read_bool_flag(extra, "cfm_float16", False),
+         )
+         # Captured by the first forward (the warmup run): under vLLM's weight load a graph held GiBs.
+         self._precapture_pending = read_bool_flag(extra, "cfm_graph_precapture", True)
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
+index 6f0bf23388..ba09bf4814 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
+@@ -41,6 +41,7 @@ from vllm_omni.model_executor.models.minicpmo_4_5 import (
+ from vllm_omni.model_executor.models.minicpmo_4_5.config_flags import (
+     parse_bool_flag as _bool_flag,
+ )
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.talker_codec_sample import (
+     HISTORY_WINDOW,
+     TalkerCodecDeviceState,
+@@ -1085,6 +1086,7 @@ class MiniCPMO45OmniTTSForConditionalGeneration(nn.Module, SupportsPP):
+ 
+         if is_prefill or first_call:
+             token_ids, hidden_states = get_tts_handoff(info_dict)
++            hidden_states = unpack_handoff_tensor(hidden_states)
+             # Cross-process stage transport serializes CPU tensors as lists.
+             # Normalize both local tensor handoffs and transported payloads
+             # before validating/building the Talker condition.
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+index de0f232f0a..b98d4a0f8b 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+@@ -130,6 +130,16 @@ class MiniCPMO45Token2wav:
+         """Run CAM++ on device, optionally without TensorRT on CUDA."""
+         self._core.enable_device_spk_embedding(use_trt=use_trt)
+ 
++    def enable_speaker_cuda_graph(self, vllm_config) -> None:
++        """Replay the current Torch speaker forward without changing its math."""
++        from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++        from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++        speaker = self._core._spk_model
++        if not isinstance(speaker, CampplusTorch) or speaker.device.type != "cuda":
++            raise ValueError("Speaker CUDA graphs require the CUDA Torch speaker model")
++        self._core._spk_model = SpeakerCudaGraph(speaker, vllm_config)
++
+     def __call__(self, generated_speech_tokens, prompt_wav) -> bytes:
+         """One-shot tokens → 24 kHz WAV bytes."""
+         return self._core.forward(
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..eed3b976eb
+--- /dev/null
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+@@ -0,0 +1,56 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Exact-shape replay of the existing Torch CAM++ speaker model."""
++
++from copy import copy
++
++import torch
++from vllm.config import VllmConfig
++from vllm.config.multimodal import MultiModalConfig
++
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.encoder_cuda_graph import EncoderCudaGraph
++
++
++def _precision_policy() -> tuple[bool, ...]:
++    return (
++        torch.backends.cuda.matmul.allow_tf32,
++        torch.backends.cudnn.allow_tf32,
++        torch.backends.cudnn.enabled,
++        torch.backends.cudnn.benchmark,
++        torch.backends.cudnn.deterministic,
++        torch.are_deterministic_algorithms_enabled(),
++    )
++
++
++class SpeakerCudaGraph:
++    """Keep the shared eager model untouched and own this consumer's graphs.
++
++    Shapes are not padded. A changed precision policy runs eagerly instead of
++    replaying kernels captured with another policy. The existing encoder graph
++    manager bounds shape admission, isolates streams, and returns owned outputs.
++    """
++
++    def __init__(self, speaker: CampplusTorch, vllm_config: VllmConfig, *, max_graphs: int = 4):
++        self.speaker = speaker
++        self.device = speaker.device
++        # Code2Wav is a generation stage, so its model config need not carry
++        # multimodal limits. The local exact-shape adapter needs only defaults.
++        config = copy(vllm_config)
++        config.model_config = copy(config.model_config)
++        if config.model_config.multimodal_config is None:
++            config.model_config.multimodal_config = MultiModalConfig()
++        self.graph = EncoderCudaGraph(speaker.model.forward, config, max_graphs=max_graphs)
++        self._policy: tuple[bool, ...] | None = None
++
++    @torch.inference_mode()
++    def __call__(self, feat: torch.Tensor) -> torch.Tensor:
++        if self.device.type != "cuda" or torch.is_autocast_enabled("cuda"):
++            return self.speaker(feat)
++        policy = _precision_policy()
++        if self._policy is None:
++            self._policy = policy
++        elif policy != self._policy:
++            return self.speaker(feat)
++        feat = feat.to(self.device, non_blocking=True).unsqueeze(0).float()
++        return self.graph(feat)
+diff --git a/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py b/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
+index d707b8e53e..b8de386efa 100644
+--- a/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
++++ b/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
+@@ -20,6 +20,7 @@ from vllm_omni.model_executor.models.minicpmo_4_5 import (
+     MINICPMO45_DUPLEX_CODEC_TOKENS_PER_CHUNK,
+     MINICPMO45_DUPLEX_TURN_END_CODEC_TOKENS,
+ )
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor, unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.pipeline import MINICPMO45_REFERENCE_AUDIO_KEY
+ 
+ logger = logging.getLogger(__name__)
+@@ -461,7 +462,7 @@ def tts2code2wav_async_chunk(
+     if int(record["cache_epoch"]) == 0 and chunk_seq == 0:
+         codes_info = _request_intermediate_section(request, "codes")
+         meta_info = _request_intermediate_section(request, "meta")
+-        raw_ref_audio = codes_info.get("ref")
++        raw_ref_audio = unpack_handoff_tensor(codes_info.get("ref"))
+         raw_ref_audio_sr = meta_info.get("ref_audio_sr")
+         ref_audio_sr = _coerce_int(raw_ref_audio_sr)
+         if raw_ref_audio is not None:
+@@ -521,7 +522,7 @@ def tts2code2wav_full_payload(
+     meta_info = _request_intermediate_section(request, "meta")
+     duplex_info = _request_intermediate_section(request, "duplex")
+ 
+-    ref_audio = codes_info.get("ref")
++    ref_audio = unpack_handoff_tensor(codes_info.get("ref"))
+     finished = torch.tensor(True, dtype=torch.bool)
+     return OmniPayloadStruct(
+         codes=CodesStruct(
+@@ -1149,8 +1150,12 @@ def llm2tts(
+             )
+         if ref_audio is not None:
+             ref_waveform, ref_sr = ref_audio
+-            set_ref_audio(model_intermediate_buffer, _to_transport_list(ref_waveform), ref_sr)
+-        handoff_hidden = _to_transport_list(tts_hidden_slice) if tts_hidden_slice is not None else None
++            set_ref_audio(
++                model_intermediate_buffer,
++                _to_transport_list(ref_waveform) if is_native_duplex_handoff else pack_handoff_tensor(ref_waveform),
++                ref_sr,
++            )
++        handoff_hidden = _to_transport_list(tts_hidden_slice) if is_native_duplex_handoff else tts_hidden_slice
+         native_turn_end_handoff = False
+         turn_text_ends_sentence = False
+         if is_native_duplex_handoff:
+@@ -1158,7 +1163,11 @@ def llm2tts(
+             native_turn_end_handoff = turn_eos_id is not None and handoff_ids is not None and turn_eos_id in handoff_ids
+             if not handoff_ids:
+                 continue
+-        set_tts_handoff(model_intermediate_buffer, handoff_ids, handoff_hidden)
++        set_tts_handoff(
++            model_intermediate_buffer,
++            handoff_ids,
++            pack_handoff_tensor(handoff_hidden) if isinstance(handoff_hidden, torch.Tensor) else handoff_hidden,
++        )
+         if is_native_duplex_handoff:
+             # Always write the flag: the connector merges per-request meta across
+             # units, so a turn_end=True left by the previous turn's last unit would
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cpu-profile-retry.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cpu-profile-retry.json
new file mode 100644
index 000000000..2a184d7af
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-cpu-profile-retry.json
@@ -0,0 +1,9 @@
+{
+  "frozen_at_utc": "2026-10-21T09:54:46.971129+00:00",
+  "prior_attempt": "100Hz subprocess sampler accumulated67.16s lag; manually interrupted, retained1277 samples but quantitative attribution invalid; all requests excluded",
+  "retry": "Reuse already warmed owned service; sequential CPU-time-only and2Hz nonblocking GIL subprocess sampling15s; each canonical64 C32 warmup/discard+3; all timings remain diagnostic-only",
+  "sampling_limit": "Nonblocking stacks can be inconsistent; record profiler errors and sampling lag; CPU counters from separate no-profiler run provide independent context",
+  "controller_handling": "Pause only owned controller during recovery to keep service alive; resume in finally; original attempt timing includes intervention and is invalid",
+  "holdout_used": false,
+  "verdict": "INCONCLUSIVE"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-tensor-handoff.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-tensor-handoff.json
new file mode 100644
index 000000000..c4c6ba306
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-tensor-handoff.json
@@ -0,0 +1,62 @@
+{
+  "frozen_at_utc": "2026-10-21T09:59:30.955099+00:00",
+  "plane": "harness",
+  "parent_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "hypothesis": "Ordinary turn handoff materializes reference waveform and hidden states as Python lists, traverses them in worker storage, then recreates tensors. Packed CPU tensor bytes using the existing Omni serializer can preserve values while reducing host work.",
+  "evidence": "Both perturbed100Hz and limited2Hz GIL samples hit _store_value list comprehension; independent CPU counters show Talker processes highest CPU time. Samples do not quantify unprofiled savings.",
+  "wire_constraint": "model_intermediate_buffer values are Any; raw torch.Tensor cannot rely on typed vLLM MsgpackDecoder hooks. Use existing OmniSerde bytes, not a new unsafe serializer.",
+  "scope": "Ordinary turn llm2tts only; native duplex list producer unchanged; consumers accept legacy lists and packed bytes. No sampling, numeric kernel, window, cache-capacity or weights changes.",
+  "controls": [
+    "Bitwise float32 equivalence with legacy list-to-float32 path",
+    "Actual vLLM MsgpackEncoder/Decoder Any-field roundtrip",
+    "Owned snapshots and independent decode outputs",
+    "Empty/noncontiguous/bfloat16 inputs and invalid packed payloads",
+    "Existing stage-input, async connector and Talker tests",
+    "CPU transport microbenchmark before unprofiled service screen"
+  ],
+  "service": "Same64 reused tuning prompts C1/16/32 discard+one; compare selectiveCFM speaker2x4 window25 parent; quality score all3 cells",
+  "final_acceptance": "Unchanged peer comparison and unused256 prompt-cluster quality gates",
+  "holdout_used": false,
+  "verdict": "INCONCLUSIVE",
+  "microbenchmark": {
+    "reference_shape": [
+      144000
+    ],
+    "hidden_shape": [
+      32,
+      4096
+    ],
+    "source_hidden_dtype": "bfloat16",
+    "consumer_dtype": "float32",
+    "warmup_each": 10,
+    "iterations_each": 100,
+    "order": "alternating AB/BA",
+    "stages": "producer, actual vLLM msgpack Any-field roundtrip, existing runner storage, float32 consumer",
+    "gate": "bitwise equality mandatory; timing is descriptive, no service claim"
+  },
+  "pre_execution_composition_addendum": {
+    "at_utc": "2026-10-21T10:08:27.166322+00:00",
+    "screens": [
+      {
+        "candidate": "screen-tensor-handoff25",
+        "control": "screen-cfm-speaker-replicas2x4",
+        "window": 25
+      },
+      {
+        "candidate": "screen-tensor-handoff50",
+        "control": "screen-cfm-speaker-window50",
+        "window": 50
+      }
+    ],
+    "reason": "Both parent profiles had descriptive means within margins; vary only packed transport relative to each. Expanded HiFT coverage profile exceeded quality means and is not the chosen50-frame parent.",
+    "tests": "213 passed,1 pre-existing skipped; precommit in progress",
+    "holdout_used": false
+  },
+  "candidate_revision": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
+  "validation": {
+    "regression_tests_passed": 213,
+    "pre_existing_skipped": 1,
+    "precommit": "PASS, including commit hooks",
+    "micro_bitwise_equal": true
+  }
+}
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-window50-coverage.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-window50-coverage.json
new file mode 100644
index 000000000..ea496bf39
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-window50-coverage.json
@@ -0,0 +1,42 @@
+{
+  "frozen_at_utc": "2026-10-21T09:41:00.011599+00:00",
+  "scope": "One-plane infra graph-coverage contrast on the existing 50-frame selective-CFM profile",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "hypothesis": "Larger audio windows expose final/short-first HiFT shapes outside existing continuation4..28 capture coverage; exact unpadded graph coverage may reduce host launch overhead.",
+  "diagnostic_evidence": {
+    "profile": "FP32 window100",
+    "eager_hift_calls_in_server_log": 310,
+    "distinct_shapes": 76,
+    "limitation": "Whole server log including warmup/discard, not per-run timing attribution"
+  },
+  "control": "screen-cfm-speaker-window50",
+  "candidate": "screen-cfm-speaker-window50-covered",
+  "only_changes": {
+    "hift_graph_first_chunk_frames": [
+      4,
+      53
+    ],
+    "hift_graph_continuation_frames": [
+      4,
+      53
+    ]
+  },
+  "unchanged": {
+    "exact_batch_sizes": [
+      1
+    ],
+    "codec_chunk_frames": 50,
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "sampling": "canonical pinned parameters",
+    "precision": "FP16 CFM only; FP32 encoder/speaker/HiFT"
+  },
+  "workload": "same64 reused tuning prompts; C1/16/32; discard+one measured",
+  "quality": "Score all three cells before promotion; no reserved holdout used",
+  "qualification": "Exploratory; final repeated peer comparison and all9 frozen quality bounds still required",
+  "latency": "First window remains50; report TTFA and first chunk duration",
+  "verdict": "INCONCLUSIVE"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-fp32-window100-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-fp32-window100-screen.json
new file mode 100644
index 000000000..73f4578ef
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-fp32-window100-screen.json
@@ -0,0 +1,228 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "17246ce5e695c7f0c58d53f42aa586e1e94390f1",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP32 CFM/HiFT, existing CFM TF32 policy",
+    "stage0_kv_bytes": 8589934592,
+    "speaker_graph": true,
+    "codec_chunk_frames": 100
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 37.29429988376796,
+      "throughput_frames_s": 184.93442755314632,
+      "ttfa_p50_s": 0.5609735790640116,
+      "ttfa_p95_s": 0.6110739761497825,
+      "rtf_mean": 0.1369307923308603,
+      "rtf_duration_weighted": 0.1347393830134931,
+      "req_s": 1.7160799424969357,
+      "audio_s_per_s": 7.397377102125853,
+      "e2e_p50_s": 0.5840785643085837,
+      "e2e_p95_s": 0.7460732581093905,
+      "total_audio_s": 275.88,
+      "first_chunk_mean_s": 3.635625,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.03912687301635742,
+      "inter_chunk_gap_p95_s": 0.16619705976918328,
+      "inter_chunk_gap_max_s": 0.21081500221043825
+    },
+    "16": {
+      "label": "run1",
+      "concurrency": 16,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 5.59145837277174,
+      "throughput_frames_s": 1249.226862532729,
+      "ttfa_p50_s": 1.1959868026897311,
+      "ttfa_p95_s": 1.5735268655233086,
+      "rtf_mean": 0.30558573093240005,
+      "rtf_duration_weighted": 0.3001696228049029,
+      "req_s": 11.446029950192507,
+      "audio_s_per_s": 49.969074501309166,
+      "e2e_p50_s": 1.2731213858351111,
+      "e2e_p95_s": 1.8080036663915962,
+      "total_audio_s": 279.4,
+      "first_chunk_mean_s": 3.65,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.1827668915502727,
+      "inter_chunk_gap_p95_s": 0.39608303224667907,
+      "inter_chunk_gap_max_s": 0.429201103746891
+    },
+    "32": {
+      "label": "run1",
+      "concurrency": 32,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 5.071101407520473,
+      "throughput_frames_s": 1365.7782488294756,
+      "ttfa_p50_s": 1.7940716501325369,
+      "ttfa_p95_s": 2.89736017761752,
+      "rtf_mean": 0.5003153664185347,
+      "rtf_duration_weighted": 0.5061451101119202,
+      "req_s": 12.620532475467288,
+      "audio_s_per_s": 54.63112995317903,
+      "e2e_p50_s": 1.8486395636573434,
+      "e2e_p95_s": 3.4626756666693836,
+      "total_audio_s": 277.04,
+      "first_chunk_mean_s": 3.66,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.44615184608846903,
+      "inter_chunk_gap_p95_s": 0.7602637936361134,
+      "inter_chunk_gap_max_s": 0.7671491131186485
+    }
+  },
+  "quality": {
+    "1": {
+      "n": 64,
+      "sim": 49.63445267081261,
+      "utmos": 4.312692571431398,
+      "wer": 0.019801980198019802,
+      "wer_counts": {
+        "substitutions": 11,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 695
+      },
+      "wer_mean": 0.023231716200466202
+    },
+    "16": {
+      "n": 64,
+      "sim": 50.44073933362961,
+      "utmos": 4.290612157434225,
+      "wer": 0.016973125884016973,
+      "wer_counts": {
+        "substitutions": 10,
+        "deletions": 1,
+        "insertions": 1,
+        "hits": 696
+      },
+      "wer_mean": 0.02139058857808858
+    },
+    "32": {
+      "n": 64,
+      "sim": 50.25124752521515,
+      "utmos": 4.303199872374535,
+      "wer": 0.024045261669024046,
+      "wer_counts": {
+        "substitutions": 14,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 692
+      },
+      "wer_mean": 0.02682421744921745
+    }
+  },
+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "latency_note": "The same codec window applies to first and subsequent chunks; larger windows increase first-audio delay. See TTFA and first_chunk_mean_s.",
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
+      "wer_pp": 0.0,
+      "sim_x100_drop": 0.40443530678749084,
+      "utmos_drop": -0.10170039162039757,
+      "within_mean_margins": true
+    },
+    "16": {
+      "wer_pp": -0.28288543140028294,
+      "sim_x100_drop": -0.39560815691947937,
+      "utmos_drop": -0.06793442368507385,
+      "within_mean_margins": true
+    },
+    "32": {
+      "wer_pp": 0.5657708628005659,
+      "sim_x100_drop": 0.7515539824962616,
+      "utmos_drop": -0.08279458805918694,
+      "within_mean_margins": false
+    }
+  },
+  "mean_screen_within_margins": false,
+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-cpu-profile.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-cpu-profile.json
new file mode 100644
index 000000000..a488d1ea3
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-cpu-profile.json
@@ -0,0 +1,879 @@
+{
+  "scope": "Independent C32 diagnostic, all requests excluded from performance",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "cpu_only": {
+    "elapsed_s": 36.49081588536501,
+    "note": "Includes client warmup/discard/three runs and saving overhead; busy-poll CPU is included, so these are not kernel attribution or critical-path fractions",
+    "processes": [
+      {
+        "role": "frontend",
+        "cpu_s": 13.819999999999993
+      },
+      {
+        "role": "utility",
+        "cpu_s": 0.07999999999999999
+      },
+      {
+        "role": "stage0_replica0",
+        "cpu_s": 17.069999999999993
+      },
+      {
+        "role": "stage1_replica0",
+        "cpu_s": 26.53
+      },
+      {
+        "role": "stage1_replica1",
+        "cpu_s": 25.19999999999999
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+              "samples": 1
+            }
+          ]
+        }
+      ],
+      "limitation": "35 samples and8 stack errors; qualitative corroboration only"
+    }
+  },
+  "hypothesis": "Repeated conversion/storage of Python scalar lists in ordinary Talker handoff; verify with lossless transport microbench and unprofiled service",
+  "verdict": "INCONCLUSIVE"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
index 1f196c075..5ea2ba764 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
@@ -1,7 +1,7 @@
 {
   "scope": "Completed round-two tuning screens; reused data, no final acceptance",
   "path": "peer-round2-screen-requests-quality.json.gz",
-  "sha256": "d45d2ed92dd930d6ab203e0e36105c1f570001f35a707af8dd07b507a4c8aa68",
+  "sha256": "5449102bd24f08177d360db19b2593162012d2d35a0b9842b98150b91a20247b",
   "profiles": [
     "screen-torch-mps",
     "screen-capacity32-mps",
@@ -23,7 +23,10 @@
     "screen-speaker-graph-replicas2",
     "screen-pipeline-replicas2x4",
     "screen-cfm-speaker-replicas2x4",
-    "screen-cfm-speaker-window50"
+    "screen-cfm-speaker-window50",
+    "screen-fp32-speaker-window100",
+    "screen-cfm-speaker-window100",
+    "screen-cfm-speaker-window50-covered"
   ],
   "privacy": "Audio and ASR hypothesis text are excluded. Audio hashes and error counts remain."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
index f9c48c064..11ad49c39 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-quality.json
@@ -685,6 +685,170 @@
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         "wer_mean": 0.018644376456876458
       }
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+          "deletions": 1,
+          "insertions": 2,
+          "hits": 695
+        },
+        "wer_mean": 0.023231716200466202
+      },
+      "16": {
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+        "utmos": 4.290612157434225,
+        "wer": 0.016973125884016973,
+        "wer_counts": {
+          "substitutions": 10,
+          "deletions": 1,
+          "insertions": 1,
+          "hits": 696
+        },
+        "wer_mean": 0.02139058857808858
+      },
+      "32": {
+        "n": 64,
+        "sim": 50.25124752521515,
+        "utmos": 4.303199872374535,
+        "wer": 0.024045261669024046,
+        "wer_counts": {
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+        "wer_mean": 0.02682421744921745
+      }
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+    "screen-cfm-speaker-window50": {
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+        "sim": 49.96810257434845,
+        "utmos": 4.273748215287924,
+        "wer": 0.019801980198019802,
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+      },
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+        "utmos": 4.266231369227171,
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+    "screen-cfm-speaker-window100": {
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+    "screen-cfm-speaker-window50-covered": {
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 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
index 468ab80fd..96c9b3b6b 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -30,13 +30,17 @@
     "Combined precision/speaker graph113 tests PASS",
     "Selective CFM speaker2x4 screen, C16/C32 1184.3/1510.9; descriptive means within margins",
     "50-frame window screen, C16/C32 1316.0/1592.2; no peer win",
-    "Three-repeat prompt-cluster quality design frozen before holdout generation;8 synthetic validator controls PASS"
+    "Three-repeat prompt-cluster quality design frozen before holdout generation;8 synthetic validator controls PASS",
+    "FP32 window100 screen,C16/C32 1249.2/1365.8; C32 WER mean exceeds margin",
+    "Same-GPU final comparison runner prepared;10 preflight controls PASS, not executed",
+    "Window50 all descriptive quality means within margins",
+    "Window100 selectiveCFM C16/C32 1244.9/1463.3; quality means exceed margins",
+    "Window50 exact HiFT coverage C16/C32 1367.4/1663.7; quality means exceed margins",
+    "CPU diagnostic recovered from100Hz sampling lag; separate CPU counters and2Hz qualitative stacks",
+    "Packed transport synthetic CPU median34.53ms to0.498ms; bitwise values preserved;213 regression tests passed with1existing skip"
   ],
   "active": [
-    "Selective CFM window100 service",
-    "FP32 window100 control service",
-    "Temporal-window speech scoring queued",
-    "Independent CPU/GIL diagnostic service initializing"
+    "Packed conditioning transport25/50-frame service screens queued, source60d71d16e0; quality watchers pending"
   ],
   "reserved_holdout_used": false,
   "quality_margins": {
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-micro.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-micro.json
new file mode 100644
index 000000000..005c0971b
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-micro.json
@@ -0,0 +1,232 @@
+{
+  "scope": "CPU synthetic transport diagnostic, not service throughput",
+  "shapes": {
+    "reference": [
+      144000
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+    "hidden": [
+      32,
+      4096
+    ]
+  },
+  "hidden_source_dtype": "bfloat16",
+  "consumer_dtype": "float32",
+  "warmup_each": 10,
+  "iterations_each": 100,
+  "order": "alternating AB/BA",
+  "bitwise_values_equal": true,
+  "results": {
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-window100-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window100-screen.json
new file mode 100644
index 000000000..41d69312a
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window100-screen.json
@@ -0,0 +1,228 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "actual_runtime": {
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+    "replicas": [
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+      4
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+    "capacities": [
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+      16,
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+    "precision": "FP16 CFM estimator/noise/cache; FP32 encoder, speaker and HiFT",
+    "stage0_kv_bytes": 8589934592,
+    "speaker_graph": true,
+    "codec_chunk_frames": 100
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
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+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 4.713400147855282,
+      "throughput_frames_s": 1463.2748724163198,
+      "ttfa_p50_s": 1.6086924970149994,
+      "ttfa_p95_s": 2.5236474851612,
+      "rtf_mean": 0.4764370669838497,
+      "rtf_duration_weighted": 0.4760259546994962,
+      "req_s": 13.578308225988758,
+      "audio_s_per_s": 58.530994896652786,
+      "e2e_p50_s": 1.6994229541160166,
+      "e2e_p95_s": 3.3273073732852927,
+      "total_audio_s": 275.88,
+      "first_chunk_mean_s": 3.6550000000000002,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.4485845952294767,
+      "inter_chunk_gap_p95_s": 0.8323902513366193,
+      "inter_chunk_gap_max_s": 0.8703409740701318
+    }
+  },
+  "quality": {
+    "1": {
+      "n": 64,
+      "sim": 49.79722398519516,
+      "utmos": 4.310572676360607,
+      "wer": 0.02263083451202263,
+      "wer_counts": {
+        "substitutions": 13,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 693
+      },
+      "wer_mean": 0.027256337412587414
+    },
+    "16": {
+      "n": 64,
+      "sim": 51.04224959015846,
+      "utmos": 4.316567372530699,
+      "wer": 0.021216407355021217,
+      "wer_counts": {
+        "substitutions": 10,
+        "deletions": 1,
+        "insertions": 4,
+        "hits": 696
+      },
+      "wer_mean": 0.027616914335664336
+    },
+    "32": {
+      "n": 64,
+      "sim": 50.54828384518623,
+      "utmos": 4.308298099786043,
+      "wer": 0.02263083451202263,
+      "wer_counts": {
+        "substitutions": 13,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 693
+      },
+      "wer_mean": 0.027835445804195804
+    }
+  },
+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "latency_note": "The same codec window applies to first and subsequent chunks; larger windows increase first-audio delay. See TTFA and first_chunk_mean_s.",
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
+      "wer_pp": 0.28288543140028294,
+      "sim_x100_drop": 0.24166399240493774,
+      "utmos_drop": -0.09958049654960632,
+      "within_mean_margins": false
+    },
+    "16": {
+      "wer_pp": 0.14144271570014147,
+      "sim_x100_drop": -0.9971184134483337,
+      "utmos_drop": -0.09388963878154755,
+      "within_mean_margins": true
+    },
+    "32": {
+      "wer_pp": 0.42432814710042444,
+      "sim_x100_drop": 0.454517662525177,
+      "utmos_drop": -0.0878928154706955,
+      "within_mean_margins": false
+    }
+  },
+  "mean_screen_within_margins": false,
+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-covered-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-covered-screen.json
new file mode 100644
index 000000000..94bbbac3e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-covered-screen.json
@@ -0,0 +1,241 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "459ace4362ade365a299dc59fd9c30433dcd5af3",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP16 CFM estimator/noise/cache; FP32 encoder, speaker and HiFT",
+    "stage0_kv_bytes": 8589934592,
+    "speaker_graph": true,
+    "hift_exact_coverage": {
+      "first": [
+        4,
+        53
+      ],
+      "continuation": [
+        4,
+        53
+      ],
+      "batch_sizes": [
+        1
+      ]
+    },
+    "codec_chunk_frames": 50
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 36.43917041923851,
+      "throughput_frames_s": 189.27434188673638,
+      "ttfa_p50_s": 0.39171386463567615,
+      "ttfa_p95_s": 0.4206689640879631,
+      "rtf_mean": 0.13333525141174785,
+      "rtf_duration_weighted": 0.13178481219550553,
+      "req_s": 1.7563517298464735,
+      "audio_s_per_s": 7.570973675469455,
+      "e2e_p50_s": 0.5730530279688537,
+      "e2e_p95_s": 0.7644290314521638,
+      "total_audio_s": 275.88,
+      "first_chunk_mean_s": 1.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.12094475980848074,
+      "inter_chunk_gap_p95_s": 0.1637499648146331,
+      "inter_chunk_gap_max_s": 0.1815652409568429
+    },
+    "16": {
+      "label": "run1",
+      "concurrency": 16,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 5.081234819255769,
+      "throughput_frames_s": 1367.384158998117,
+      "ttfa_p50_s": 0.8966498821973801,
+      "ttfa_p95_s": 1.125088334176689,
+      "rtf_mean": 0.2991832687490079,
+      "rtf_duration_weighted": 0.28805598770681107,
+      "req_s": 12.595363583172064,
+      "audio_s_per_s": 54.69536635992469,
+      "e2e_p50_s": 1.2703996961936355,
+      "e2e_p95_s": 1.4797041315585373,
+      "total_audio_s": 277.92,
+      "first_chunk_mean_s": 1.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.18240823363885283,
+      "inter_chunk_gap_p95_s": 0.43122551059350367,
+      "inter_chunk_gap_max_s": 0.5144128352403641
+    },
+    "32": {
+      "label": "run1",
+      "concurrency": 32,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 4.202648081816733,
+      "throughput_frames_s": 1663.7129409554268,
+      "ttfa_p50_s": 1.4452437539584935,
+      "ttfa_p95_s": 1.9467360251583155,
+      "rtf_mean": 0.47280168638903425,
+      "rtf_duration_weighted": 0.4597507787659792,
+      "req_s": 15.228493738722442,
+      "audio_s_per_s": 66.54851763821708,
+      "e2e_p50_s": 2.0080804619938135,
+      "e2e_p95_s": 2.510947760986164,
+      "total_audio_s": 279.68,
+      "first_chunk_mean_s": 1.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.2640033969655633,
+      "inter_chunk_gap_p95_s": 0.7575123661197722,
+      "inter_chunk_gap_max_s": 0.8681540051475167
+    }
+  },
+  "quality": {
+    "1": {
+      "n": 64,
+      "sim": 49.9683700799942,
+      "utmos": 4.273769196122885,
+      "wer": 0.024045261669024046,
+      "wer_counts": {
+        "substitutions": 14,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 692
+      },
+      "wer_mean": 0.026884313603063606
+    },
+    "16": {
+      "n": 64,
+      "sim": 50.43840545415878,
+      "utmos": 4.26598883420229,
+      "wer": 0.016973125884016973,
+      "wer_counts": {
+        "substitutions": 9,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 697
+      },
+      "wer_mean": 0.021248543123543125
+    },
+    "32": {
+      "n": 64,
+      "sim": 50.096578657627106,
+      "utmos": 4.267129510641098,
+      "wer": 0.016973125884016973,
+      "wer_counts": {
+        "substitutions": 8,
+        "deletions": 1,
+        "insertions": 3,
+        "hits": 698
+      },
+      "wer_mean": 0.02295308857808858
+    }
+  },
+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "latency_note": "The same codec window applies to first and subsequent chunks; larger windows increase first-audio delay. See TTFA and first_chunk_mean_s.",
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
+      "wer_pp": 0.42432814710042444,
+      "sim_x100_drop": 0.070517897605896,
+      "utmos_drop": -0.06277701631188393,
+      "within_mean_margins": false
+    },
+    "16": {
+      "wer_pp": -0.28288543140028294,
+      "sim_x100_drop": -0.3932742774486542,
+      "utmos_drop": -0.04331110045313835,
+      "within_mean_margins": true
+    },
+    "32": {
+      "wer_pp": -0.14144271570014147,
+      "sim_x100_drop": 0.9062228500843048,
+      "utmos_drop": -0.04672422632575035,
+      "within_mean_margins": false
+    }
+  },
+  "mean_screen_within_margins": false,
+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json
index b830a0ee0..a1653124f 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-window50-screen.json
@@ -160,7 +160,69 @@
       "inter_chunk_gap_max_s": 0.8016324387863278
     }
   },
-  "quality": {},
-  "quality_status": "Scoring pending",
-  "latency_note": "The same codec window applies to first and subsequent chunks; larger windows increase first-audio delay. See TTFA and first_chunk_mean_s."
+  "quality": {
+    "1": {
+      "n": 64,
+      "sim": 49.96810257434845,
+      "utmos": 4.273748215287924,
+      "wer": 0.019801980198019802,
+      "wer_counts": {
+        "substitutions": 11,
+        "deletions": 1,
+        "insertions": 2,
+        "hits": 695
+      },
+      "wer_mean": 0.023231716200466202
+    },
+    "16": {
+      "n": 64,
+      "sim": 51.926472425460815,
+      "utmos": 4.266231369227171,
+      "wer": 0.019801980198019802,
+      "wer_counts": {
+        "substitutions": 10,
+        "deletions": 1,
+        "insertions": 3,
+        "hits": 696
+      },
+      "wer_mean": 0.02292941433566434
+    },
+    "32": {
+      "n": 64,
+      "sim": 50.8500913977623,
+      "utmos": 4.258575938642025,
+      "wer": 0.016973125884016973,
+      "wer_counts": {
+        "substitutions": 6,
+        "deletions": 1,
+        "insertions": 5,
+        "hits": 700
+      },
+      "wer_mean": 0.02188774766899767
+    }
+  },
+  "quality_status": "Descriptive reused-cohort means, not confidence-bound qualification",
+  "latency_note": "The same codec window applies to first and subsequent chunks; larger windows increase first-audio delay. See TTFA and first_chunk_mean_s.",
+  "descriptive_mean_degradation_vs_torch_mps": {
+    "1": {
+      "wer_pp": 0.0,
+      "sim_x100_drop": 0.07078540325164795,
+      "utmos_drop": -0.06275603547692299,
+      "within_mean_margins": true
+    },
+    "16": {
+      "wer_pp": 0.0,
+      "sim_x100_drop": -1.8813412487506866,
+      "utmos_drop": -0.043553635478019714,
+      "within_mean_margins": true
+    },
+    "32": {
+      "wer_pp": -0.14144271570014147,
+      "sim_x100_drop": 0.15271010994911194,
+      "utmos_drop": -0.03817065432667732,
+      "within_mean_margins": true
+    }
+  },
+  "mean_screen_within_margins": true,
+  "quality_reference_note": "Reused Torch/MPS tuning screen only; final qualification uses pinned15b main on unused256 prompts and confidence bounds."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_bench_tensor_handoff.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_bench_tensor_handoff.py
new file mode 100644
index 000000000..1b174f050
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_bench_tensor_handoff.py
@@ -0,0 +1,76 @@
+import argparse
+import json
+import statistics
+import time
+from pathlib import Path
+from typing import Any
+
+import torch
+from vllm.v1.serial_utils import MsgpackDecoder, MsgpackEncoder
+from vllm_omni.model_executor.models.minicpmo_4_5.handoff import (
+    pack_handoff_tensor,
+    unpack_handoff_tensor,
+)
+from vllm_omni.worker.gpu_model_runner import OmniGPUModelRunner
+
+parser = argparse.ArgumentParser(
+    description="CPU transport microbenchmark; run with the candidate on PYTHONPATH"
+)
+parser.add_argument("--out", type=Path, required=True)
+args = parser.parse_args()
+if args.out.exists():
+    raise FileExistsError(args.out)
+ref = torch.linspace(-0.8, 0.8, 144000)
+hidden = torch.linspace(-2, 2, 32 * 4096).reshape(32, 4096).to(torch.bfloat16)
+encoder = MsgpackEncoder()
+decoder = MsgpackDecoder(dict[str, Any])
+
+
+def run(packed):
+    payload = {
+        "codes": {"ref": pack_handoff_tensor(ref) if packed else ref.tolist()},
+        "hidden_states": {"tts": pack_handoff_tensor(hidden) if packed else hidden.tolist()},
+    }
+    received = decoder.decode(encoder.encode(payload))
+    stored = {}
+    for group, values in received.items():
+        stored[group] = {}
+        for key, value in values.items():
+            OmniGPUModelRunner._store_value(None, stored[group], key, value, set())
+    a = torch.as_tensor(unpack_handoff_tensor(stored["codes"]["ref"]), dtype=torch.float32)
+    b = torch.as_tensor(unpack_handoff_tensor(stored["hidden_states"]["tts"]), dtype=torch.float32)
+    return a, b
+
+
+for packed in (False, True):
+    a, b = run(packed)
+    assert torch.equal(a, ref) and torch.equal(b, hidden.float())
+for _ in range(10):
+    run(False)
+    run(True)
+samples = {False: [], True: []}
+for i in range(100):
+    for packed in (False, True) if i % 2 == 0 else (True, False):
+        start = time.perf_counter()
+        run(packed)
+        samples[packed].append((time.perf_counter() - start) * 1000)
+result = {
+    "scope": "CPU synthetic transport diagnostic, not service throughput",
+    "shapes": {"reference": [144000], "hidden": [32, 4096]},
+    "hidden_source_dtype": "bfloat16",
+    "consumer_dtype": "float32",
+    "warmup_each": 10,
+    "iterations_each": 100,
+    "order": "alternating AB/BA",
+    "bitwise_values_equal": True,
+    "results": {
+        ("packed" if k else "legacy_list"): {
+            "median_ms": statistics.median(v),
+            "mean_ms": statistics.mean(v),
+            "samples_ms": v,
+        }
+        for k, v in samples.items()
+    },
+}
+args.out.write_text(json.dumps(result, indent=2) + "\n")
+print({k: {s: t for s, t in v.items() if s != "samples_ms"} for k, v in result["results"].items()})
diff --git a/evidence/minicpmo45-l20x-20261021/validator/peer_round2_performance_pair.py b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_performance_pair.py
new file mode 100644
index 000000000..80cf97cfc
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/peer_round2_performance_pair.py
@@ -0,0 +1,222 @@
+"""Run the pinned peer and selected candidate sequentially on one reserved GPU.
+
+The output directory contains private logs and paths; sanitize before publishing.
+This runner produces measurements, not a speech-quality or acceptance verdict.
+"""
+
+import argparse
+import hashlib
+import json
+import os
+import signal
+import socket
+import subprocess
+import time
+import urllib.request
+from pathlib import Path
+
+import yaml
+
+
+def digest(path):
+    with path.open("rb") as source:
+        return hashlib.file_digest(source, "sha256").hexdigest()
+
+
+def check_revision(repo, expected):
+    actual = subprocess.check_output(
+        ["git", "-C", str(repo), "rev-parse", "HEAD"], text=True
+    ).strip()
+    dirty = subprocess.check_output(["git", "-C", str(repo), "status", "--porcelain"], text=True)
+    if actual != expected or dirty:
+        raise ValueError("Serving source must be clean and match its frozen revision")
+    return actual
+
+
+def require_single_gpu(value):
+    if not value or not value.strip() or "," in value or value.strip() in {"-1", "all"}:
+        raise ValueError("Run inside an external reservation exposing exactly one CUDA device")
+
+
+def require_unused_port(port):
+    with socket.socket() as sock:
+        if sock.connect_ex(("127.0.0.1", port)) == 0:
+            raise ValueError(f"Port {port} is already in use")
+
+
+def terminate(signum, frame):
+    raise SystemExit(128 + signum)
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    for name in (
+        "plan",
+        "model-manifest",
+        "candidate-repo",
+        "candidate-python",
+        "candidate-deploy",
+        "peer-repo",
+        "peer-python",
+        "client-python",
+        "model",
+        "dataset",
+        "out",
+    ):
+        parser.add_argument(f"--{name}", type=Path, required=True)
+    parser.add_argument("--candidate-revision", required=True)
+    parser.add_argument("--base-port", type=int, default=29601)
+    args = parser.parse_args()
+    require_single_gpu(os.environ.get("CUDA_VISIBLE_DEVICES"))
+    plan = json.loads(args.plan.read_text())
+    check_revision(args.peer_repo, plan["peer_revision"])
+    check_revision(args.candidate_repo, args.candidate_revision)
+    for port in (args.base_port, args.base_port + 1):
+        require_unused_port(port)
+    if Path(f"/tmp/minicpmo-engine-mps-{args.base_port}").exists():
+        raise ValueError("Peer MPS directory already exists; select an unused port")
+    manifest = json.loads(args.model_manifest.read_text())
+    if manifest["revision"] != plan["model_revision"]:
+        raise ValueError("Model manifest revision differs from the frozen plan")
+    for name, entry in manifest["files"].items():
+        if digest(args.model / name) != entry["sha256"]:
+            raise ValueError(f"Model asset hash mismatch: {name}")
+    deployment = yaml.safe_load(args.candidate_deploy.read_text())
+    if "base_config" in deployment:
+        raise ValueError(
+            "Freeze a complete deployment YAML without external base_config dependencies"
+        )
+    # Reject reuse so an interrupted run cannot silently mix measurements.
+    args.out.mkdir(parents=True, exist_ok=False)
+    deploy_bytes = args.candidate_deploy.read_bytes()
+    (args.out / "candidate-deploy.yaml").write_bytes(deploy_bytes)
+    snapshot = {
+        "arguments": {k: str(v) if isinstance(v, Path) else v for k, v in vars(args).items()},
+        "plan_sha256": digest(args.plan),
+        "model_manifest_sha256": digest(args.model_manifest),
+        "dataset_meta_sha256": digest(args.dataset / "en/meta.lst"),
+        "candidate_deploy_sha256": digest(args.candidate_deploy),
+        "client_sha256": digest(Path(__file__).with_name("run_baseline.py")),
+        "cuda_visible_devices": os.environ["CUDA_VISIBLE_DEVICES"],
+        "protocol": {
+            "concurrency": [1, 2, 4, 8, 16, 32],
+            "requests": 320,
+            "discarded_runs": [0],
+            "measured_runs": [1, 2, 3],
+            "id_set": "eval",
+            "cache_policy": "persistent server; no reset between cells or repetitions",
+            "order": ["peer", "candidate"],
+            "profiled": False,
+        },
+        "verdict": "INCONCLUSIVE",
+    }
+    (args.out / "execution-plan.json").write_text(json.dumps(snapshot, indent=2) + "\n")
+    signal.signal(signal.SIGTERM, terminate)
+    for index, role in enumerate(("peer", "candidate")):
+        # Detect edits between the two fresh server starts.
+        check_revision(args.peer_repo, plan["peer_revision"])
+        check_revision(args.candidate_repo, args.candidate_revision)
+        if digest(args.candidate_deploy) != snapshot["candidate_deploy_sha256"]:
+            raise ValueError("Candidate deployment changed during comparison")
+        port = args.base_port + index
+        require_unused_port(port)
+        env = os.environ | {"PYTHONUNBUFFERED": "1"}
+        if role == "peer":
+            env.update(
+                MODEL_PATH=str(args.model.resolve()),
+                ENGINE_PYTHON=str(args.peer_python.absolute()),
+                ENGINE_MPS="1",
+            )
+            command = [
+                "bash",
+                str(args.peer_repo / "scripts/serve_engine.sh"),
+                plan["peer_profile"],
+                str(port),
+            ]
+        else:
+            env["PYTHONPATH"] = str(args.candidate_repo.resolve())
+            command = [
+                str(args.candidate_python),
+                "-m",
+                "vllm_omni.entrypoints.cli.main",
+                "serve",
+                str(args.model),
+                "--omni",
+                "--served-model-name",
+                "openbmb/MiniCPM-o-4_5",
+                "--host",
+                "127.0.0.1",
+                "--port",
+                str(port),
+                "--deploy-config",
+                str(args.candidate_deploy),
+                "--trust-remote-code",
+                "--init-timeout",
+                "1800",
+                "--stage-init-timeout",
+                "1800",
+            ]
+        with (args.out / f"{role}-server.log").open("w") as log:
+            server = subprocess.Popen(
+                command, env=env, stdout=log, stderr=subprocess.STDOUT, start_new_session=True
+            )
+            try:
+                deadline = time.monotonic() + 1800
+                while True:
+                    if server.poll() is not None:
+                        raise RuntimeError(f"{role} server exited before readiness")
+                    if time.monotonic() > deadline:
+                        raise TimeoutError(f"{role} startup timeout")
+                    try:
+                        with urllib.request.urlopen(f"http://127.0.0.1:{port}/health", timeout=2):
+                            break
+                    except OSError:
+                        time.sleep(3)
+                client_env = os.environ | {
+                    "PYTHONPATH": str(args.peer_repo.resolve()),
+                    "SEED_TTS_ROOT": str(args.dataset.resolve()),
+                }
+                with (args.out / f"{role}-benchmark.log").open("w") as log:
+                    subprocess.run(
+                        [
+                            str(args.client_python),
+                            str(Path(__file__).with_name("run_baseline.py")),
+                            "--adapter",
+                            "engine" if role == "peer" else "vllm-omni",
+                            "--url",
+                            f"http://127.0.0.1:{port}",
+                            "--out",
+                            str(args.out / role),
+                            "--requests",
+                            "320",
+                            "--repeats",
+                            "3",
+                            "--id-set",
+                            "eval",
+                            "--concurrency",
+                            "1",
+                            "2",
+                            "4",
+                            "8",
+                            "16",
+                            "32",
+                        ],
+                        env=client_env,
+                        stdout=log,
+                        stderr=subprocess.STDOUT,
+                        check=True,
+                    )
+                (args.out / role / "complete").write_text("All requested measurements saved.\n")
+            finally:
+                if server.poll() is None:
+                    os.killpg(server.pid, signal.SIGTERM)
+                    try:
+                        server.wait(timeout=120)
+                    except subprocess.TimeoutExpired:
+                        os.killpg(server.pid, signal.SIGKILL)
+                        server.wait()
+    (args.out / "complete").write_text("Both engines measured; quality acceptance is separate.\n")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_performance_pair.py b/evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_performance_pair.py
new file mode 100644
index 000000000..2639cd7b5
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/test_peer_round2_performance_pair.py
@@ -0,0 +1,51 @@
+"""Preflight controls require no model or GPU service."""
+
+import subprocess
+
+import pytest
+from peer_round2_performance_pair import check_revision, require_single_gpu, require_unused_port
+
+
+@pytest.mark.parametrize("value", [None, "", " ", "0,1", "-1", "all"])
+def test_reject_ambiguous_device(value):
+    with pytest.raises(ValueError):
+        require_single_gpu(value)
+
+
+@pytest.mark.parametrize("value", ["0", "GPU-test-reservation"])
+def test_one_device(value):
+    require_single_gpu(value)
+
+
+def test_revision_and_clean_tree_are_required(tmp_path):
+    def git(*args):
+        return subprocess.check_output(["git", "-C", str(tmp_path), *args], text=True).strip()
+
+    git("init", "-q")
+    git(
+        "-c",
+        "user.name=Test",
+        "-c",
+        "user.email=test@example.invalid",
+        "commit",
+        "--allow-empty",
+        "-qm",
+        "fixture",
+    )
+    revision = git("rev-parse", "HEAD")
+    assert check_revision(tmp_path, revision) == revision
+    with pytest.raises(ValueError):
+        check_revision(tmp_path, "0" * 40)
+    (tmp_path / "untracked.py").write_text("changed source\n")
+    with pytest.raises(ValueError):
+        check_revision(tmp_path, revision)
+
+
+def test_live_port_is_rejected():
+    import socket
+
+    with socket.socket() as listener:
+        listener.bind(("127.0.0.1", 0))
+        listener.listen()
+        with pytest.raises(ValueError):
+            require_unused_port(listener.getsockname()[1])

From ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 18:23:17 +0800
Subject: [PATCH 33/40] Record conditioning transport and profiler perturbation
 case

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 docs/reference-matrix.md                      |  8 ++
 docs/searchspace-matrix.md                    |  7 ++
 .../patch/peer-round2-tensor-handoff25.yaml   | 16 ++++
 .../patch/peer-round2-tensor-handoff50.yaml   | 17 ++++
 .../inference-optimization-casebook/SKILL.md  |  3 +
 .../cases/minicpm-conditioning-transport.json | 56 ++++++++++++
 .../cases/minicpm-conditioning-transport.md   | 87 +++++++++++++++++++
 7 files changed, 194 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff25.yaml
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff50.yaml
 create mode 100644 src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json
 create mode 100644 src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md

diff --git a/docs/reference-matrix.md b/docs/reference-matrix.md
index f94b54e51..937550cbe 100644
--- a/docs/reference-matrix.md
+++ b/docs/reference-matrix.md
@@ -295,3 +295,11 @@ rather than restating it; that case shares this campaign lineage.
 
 The two primary matrices are unchanged in authority; this is a reconciliation
 note, not a third inventory. All NPU status for Drama3 remains `unverified`.
+
+## Issue #49: conditioning transport diagnostic
+
+[Owner-local case](../src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md) preserves the pinned ordinary-turn bridge,
+worker list traversal, invalidated high-rate profiler and rehashed CPU component
+measurements. This is an internal diagnostic lineage, not independent evidence
+from the peer engine. Component value equality and synthetic timing do not
+establish service throughput or speech-quality acceptance.
diff --git a/docs/searchspace-matrix.md b/docs/searchspace-matrix.md
index 584cef3fa..daebcdb5f 100644
--- a/docs/searchspace-matrix.md
+++ b/docs/searchspace-matrix.md
@@ -306,3 +306,10 @@ adds **no 🟢 cell and no measured NPU coverage**; every Drama3 NPU status is
 `unverified`, and target qualification is pending the owner-resolved
 hardware/software/model/service/evaluation/authority tuple. The five resource
 rows above remain authoritative; the two-matrix contract is unchanged.
+
+## Issue #49: Host Observe / Diagnose / Verify
+
+[Conditioning transport case](../src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md) covers scalar-list materialization,
+untyped tensor metadata, owned snapshots and profiler perturbation. It adds
+a bounded CPU component observation; no new green service-performance cell,
+GPU-kernel gain or quality qualification is credited.
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff25.yaml b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff25.yaml
new file mode 100644
index 000000000..0feac5652
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff25.yaml
@@ -0,0 +1,16 @@
+base_config: minicpmo_4_5_turn.yaml
+cuda_mps: true
+connectors:
+  connector_of_shared_memory:
+    extra:
+      token2wav_spk_cuda_graph: true
+      cfm_float16: true
+stages:
+  - stage_id: 0
+    kv_cache_memory_bytes: 8589934592
+  - stage_id: 1
+    num_replicas: 2
+    devices: "0,0"
+  - stage_id: 2
+    num_replicas: 4
+    devices: "0,0,0,0"
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff50.yaml b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff50.yaml
new file mode 100644
index 000000000..8ddbfa237
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff50.yaml
@@ -0,0 +1,17 @@
+base_config: minicpmo_4_5_turn.yaml
+cuda_mps: true
+connectors:
+  connector_of_shared_memory:
+    extra:
+      token2wav_spk_cuda_graph: true
+      cfm_float16: true
+      codec_chunk_frames: 50
+stages:
+  - stage_id: 0
+    kv_cache_memory_bytes: 8589934592
+  - stage_id: 1
+    num_replicas: 2
+    devices: "0,0"
+  - stage_id: 2
+    num_replicas: 4
+    devices: "0,0,0,0"
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md
index 9a745a495..a69512e41 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/SKILL.md
@@ -80,6 +80,9 @@ Source: perf-optimization-casebook @ f33e0e5f, §how-to-use.
 
 Current owner-local records retain rejected directions alongside their limits:
 
+- [MiniCPM-o conditioning transport](cases/minicpm-conditioning-transport.md):
+  untyped tensor metadata, scalar-list host work, owned snapshots and profiler perturbation.
+
 - [MiniCPM-o speaker extraction](cases/minicpm-speaker-cpu-reference.md): CPU
   graph optimizer semantics, short-input numerical rejection and component/service boundaries.
 
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json
new file mode 100644
index 000000000..5f06b8aaf
--- /dev/null
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json
@@ -0,0 +1,56 @@
+{
+  "id": "case.minicpm-conditioning-transport",
+  "kind": "case",
+  "origin": [
+    "internal"
+  ],
+  "state": "historical_observation",
+  "content": "minicpm-conditioning-transport.md",
+  "sources": [
+    {
+      "type": "internal",
+      "issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+      "run": "minicpmo45-l20x-20261021",
+      "artifact": "peer-round2-pipeline-cpu-profile.json",
+      "sha256": "bd407d725c049120136271bc0454e97ea8b3875c2e5e4ab0bc9ae61a5886bbda",
+      "integrity_status": "rehashed",
+      "evidence_path": "evidence/minicpmo45-l20x-20261021/results/peer-round2-pipeline-cpu-profile.json"
+    },
+    {
+      "type": "internal",
+      "issue": "https://github.com/InferMatrixLab/InferRSI/issues/49",
+      "run": "minicpmo45-l20x-20261021",
+      "artifact": "peer-round2-tensor-handoff-micro.json",
+      "sha256": "ef5d7c2edeb37872641b60391fbf9e3c06b5b82259530356f62b4f08fdbed967",
+      "integrity_status": "rehashed",
+      "evidence_path": "evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-micro.json"
+    },
+    {
+      "type": "git",
+      "url": "https://github.com/amy-why-3459/vllm-omni/commit/60d71d16e0d77734239935ffc6b991c810ea1aa7",
+      "commit": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
+      "paths": [
+        "vllm_omni/model_executor/models/minicpmo_4_5/handoff.py",
+        "vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py",
+        "tests/model_executor/models/test_minicpmo_handoff.py"
+      ]
+    }
+  ],
+  "applicability": [
+    "Untyped cross-process conditioning with scalar-list materialization",
+    "Host profiling with observable sampling lag"
+  ],
+  "tags": [
+    "host",
+    "serialization",
+    "tensor-ownership",
+    "profiling-perturbation",
+    "component-evidence"
+  ],
+  "limitations": [
+    "Campaign INCONCLUSIVE; no demonstrated service gain or quality acceptance for this implementation",
+    "Synthetic CPU timings do not predict a service speedup",
+    "Sparse nonblocking samples have errors and do not establish critical-path fractions"
+  ],
+  "attribution": "InferRSI issue #49 local component and diagnostic evidence"
+}
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md
new file mode 100644
index 000000000..7bdf62ce9
--- /dev/null
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md
@@ -0,0 +1,87 @@
+# MiniCPM-o conditioning transport: avoid scalar-list roundtrips
+
+This is a scoped host diagnostic from [acceptance issue #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
+The transport component preserves values and reduces synthetic CPU work.
+The campaign remains **INCONCLUSIVE**: this observation does not establish
+end-to-end throughput, speech quality or a peer-engine win.
+
+## Observation and measurement limits
+
+Ordinary turn-mode conditioning includes a reference waveform and thinker hidden
+states. The bridge converts tensors to Python scalar lists; EngineCore transports
+those lists, the worker traverses them, and the Talker constructs tensors again.
+In this path the large reference list is also examined element by element by
+`_store_value`, although its entries are ordinary numbers.
+
+An initial 100 Hz multi-process GIL profile accumulated 67 seconds of sampling
+lag and strongly perturbed serving. It was interrupted and invalidated for
+quantitative attribution. A separate CPU-counter run and sparse 2 Hz nonblocking
+samples also identified Talker host work, including the same list traversal.
+The latter yielded only 35 samples with 8 stack errors: it corroborates a code
+location, not its critical-path fraction. CPU counters also include polling,
+warmup and client output-saving time. All diagnostic requests were excluded
+from performance tables.
+
+## Mechanism and bounded component result
+
+The request's `model_intermediate_buffer` contains untyped values. A raw tensor
+cannot rely on vLLM's typed msgpack decoder hook to reconstruct it there.
+Replacing lists with raw tensors without a wire roundtrip check is therefore
+not sufficient.
+
+The candidate uses the existing Omni tensor serializer to create owned bytes
+for ordinary-turn reference audio and hidden states. Consumers restore CPU
+float32 tensors, matching the old list-to-float32 conversion. Native duplex
+keeps its existing producer representation; legacy lists and local tensors
+remain accepted. The change does not alter weights, sampling or acoustic
+computation.
+
+A CPU microbenchmark included production, the actual untyped msgpack roundtrip,
+worker storage and tensor reconstruction. With a 144,000-sample reference and
+32 × 4,096 BF16 hidden states, ten warmups and 100 alternating AB/BA iterations,
+with `OMP_NUM_THREADS=4`, median time was 34.53 ms for lists and 0.498 ms for packed transport. Restored
+float32 values were bitwise equal. These are synthetic component timings on a
+shared host, not a service speedup or a reusable hardware-independent ratio.
+
+Regression checks covered dtype conversion, scalar/empty/noncontiguous inputs,
+producer mutation, independent consumer ownership, invalid packed types, both
+codec handoff modes and Talker prefill. Empty transposed tensors exposed an
+encoder stride constraint; the producer now supplies a canonical empty tensor
+before encoding. The complete scoped suite passed 213 tests, with one existing
+skip. Pre-commit and commit hooks passed.
+
+## Reuse procedure
+
+1. Inspect both the producer representation and the receiving field's declared
+   wire type. Trace conversions through serializers and worker storage, rather
+   than assuming a transport supports nested tensors automatically.
+2. Treat observer lag as an invalidation signal. Use a separate low-overhead
+   diagnostic and a component reproducer before estimating service impact.
+3. Reuse an existing serializer and preserve the previous consumer dtype.
+   Verify an actual wire roundtrip, empty/noncontiguous inputs and storage
+   ownership; a same-process tensor assignment is insufficient.
+4. Measure producer, wire, storage and reconstruction together. Alternate
+   control/candidate order and keep timing separate from intrusive profiling.
+5. Freeze the source, then compare unprofiled services with identical model,
+   requests, warmup, concurrency and deployment settings. Evaluate generated
+   speech separately before promotion.
+
+## Counter-signals and rollback
+
+Do not add another byte serialization layer when the existing typed transport
+already preserves tensor metadata and ownership. Small payloads, compute-bound
+serving or already-cached conditioning may show no useful service gain. Runtime
+schedule changes can change generated outputs even when transport values are
+bitwise equal; component equality does not waive speech gates.
+
+The archived implementation changes only the ordinary-turn producer and its
+consumers. Reverting that change restores scalar-list transport without changing
+model assets. Any new field type, serializer version or consumer must revalidate
+the wire and ownership checks.
+
+## Evidence
+
+- [Frozen experiment, component results and patches](https://github.com/InferMatrixLab/InferRSI/tree/6d9c3f8/evidence/minicpmo45-l20x-20261021).
+- [Source implementation](https://github.com/amy-why-3459/vllm-omni/commit/60d71d16e0d77734239935ffc6b991c810ea1aa7).
+- The sibling JSON owns source identities and rehashed artifact integrity.
+  Service and quality outcomes remain owned by the campaign, not this case.

From e6b949aad53c5d03371963d108dbef073af97b30 Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 18:29:54 +0800
Subject: [PATCH 34/40] Refresh skill index with conditioning transport case

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../data/repo_packs/inferrsi/knowledge/README.md     |  4 ++--
 .../skills/ascend-aclgraph-capture-replay.json       |  4 ++--
 .../ascend/skills/ascend-device-health.json          |  4 ++--
 .../ascend/skills/ascend-distributed-parallel.json   |  4 ++--
 .../knowledge/ascend/skills/ascend-graph-mode.json   |  4 ++--
 .../ascend/skills/ascend-model-adaptation.json       |  4 ++--
 .../ascend/skills/ascend-operator-profiling.json     |  4 ++--
 .../ascend/skills/ascend-operator-tuning.json        |  4 ++--
 .../ascend/skills/ascend-optimization-casebook.json  |  4 ++--
 .../ascend/skills/ascend-performance-analysis.json   |  4 ++--
 .../ascend/skills/ascendc-tiling-design.json         |  4 ++--
 .../ascend/skills/cann-attribution-overlap.json      |  4 ++--
 .../skills/torchnpu-device-memory-lifecycle.json     |  4 ++--
 .../torchnpu-pinned-host-memory-lifecycle.json       |  4 ++--
 .../common/skills/assess-serving-preemption.json     |  4 ++--
 .../skills/assess-split-backward-schedule.json       |  4 ++--
 .../common/skills/audit-vllm-kv-lifetimes.json       |  4 ++--
 .../common/skills/calibrate-serving-simulation.json  |  4 ++--
 .../common/skills/cgroup-resource-controls.json      |  4 ++--
 .../skills/checkpoint-recovery-consistency.json      |  4 ++--
 .../common/skills/choose-parallel-training-plan.json |  4 ++--
 .../common/skills/cite-check-downstream-pr.json      |  4 ++--
 .../knowledge/common/skills/claim-contract.json      |  4 ++--
 .../knowledge/common/skills/competitor-scan.json     |  4 ++--
 .../common/skills/dcp-async-save-performance.json    |  4 ++--
 .../common/skills/dense-performance-evidence.json    |  4 ++--
 .../skills/diagnose-vllm-admission-pressure.json     |  4 ++--
 .../common/skills/draft-acceptance-issue.json        |  4 ++--
 .../skills/evaluate-elastic-serving-placement.json   |  4 ++--
 .../common/skills/host-memory-management.json        |  4 ++--
 .../common/skills/host-overhead-optimization.json    |  4 ++--
 .../common/skills/inference-benchmark-design.json    |  4 ++--
 .../skills/inference-optimization-casebook.json      | 12 ++++++++----
 .../common/skills/kernel-writing-guide.json          |  4 ++--
 .../knowledge/common/skills/kv-tier-management.json  |  4 ++--
 .../knowledge/common/skills/npu-skill-factory.json   |  4 ++--
 .../common/skills/optimization-search-policy.json    |  4 ++--
 .../common/skills/os-process-placement.json          |  4 ++--
 .../common/skills/performance-ceiling-analysis.json  |  4 ++--
 .../common/skills/plan-activation-residency.json     |  4 ++--
 .../common/skills/repository-evolution-analysis.json |  4 ++--
 .../knowledge/common/skills/rsi-evidence.json        |  4 ++--
 .../common/skills/skill-evolution-playbook.json      |  4 ++--
 .../common/skills/storage-io-measurement.json        |  4 ++--
 .../common/skills/training-input-pipeline.json       |  4 ++--
 .../common/skills/training-resource-budget.json      |  4 ++--
 .../common/skills/weight-loading-optimization.json   |  4 ++--
 .../cuda/skills/diagnose-attention-bottlenecks.json  |  4 ++--
 .../cuda/skills/host-overhead-profiling.json         |  4 ++--
 49 files changed, 104 insertions(+), 100 deletions(-)

diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
index 92f08107c..5906e8756 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
@@ -15,7 +15,7 @@ These are knowledge abstracts (`--kind knowledge`), with namespaced package
 IDs distinct from explicitly selected `checkout_ref` skills. Ascend/CUDA
 procedures use their corresponding backend; shared methods use `common`.
 
-Source snapshot: [94273606a05110f2d9826974f1031d3cf269ce01](https://github.com/InferMatrixLab/InferRSI/tree/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library).
+Source snapshot: [ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55](https://github.com/InferMatrixLab/InferRSI/tree/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library).
 
 ```bash
 inferrsi knowledge search 'profiling' --repo-type inferrsi --limit 50
@@ -29,7 +29,7 @@ contain the current input paths and bytes (Git checkout filters are respected).
 
 ```bash
 python tools/build_skill_index.py --source-revision <committed-source-revision>
-python tools/build_skill_index.py --source-revision 94273606a05110f2d9826974f1031d3cf269ce01 --check
+python tools/build_skill_index.py --source-revision ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55 --check
 ```
 
 `--check` detects missing, stale and unexpected generated records without writing.
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
index 382164910..12a7fccda 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
index 52bf998d7..d35c2a0f5 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
index e99e1cb8e..47696aae5 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
index 328bb0ab4..109dac395 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
index b643be41e..38c2aab35 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
index 263257ef6..c77c1dafd 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
index 2958f89e1..c35679358 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
index aa7dcf8ba..65612295a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-optimization-casebook/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
index 0ede18214..ffaeea632 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-performance-analysis.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-performance-analysis/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
index b8ddc166f..7d7b62927 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascendc-tiling-design.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
index a1cbc83ba..7a31ef8c6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/cann-attribution-overlap.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/cann-attribution-overlap/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
index 41efb759b..a003390a8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-device-memory-lifecycle.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
index 70e17fd7e..fa174f5ac 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/torchnpu-pinned-host-memory-lifecycle.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-pinned-host-memory-lifecycle/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
index b7ef77f98..d3c69597f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-serving-preemption.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/methods/assess-serving-preemption/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/methods/assess-serving-preemption/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
index 030e43c2f..180487889 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/assess-split-backward-schedule.json
@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
index 29530bc1e..c308977be 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
@@ -21,8 +21,8 @@
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index 8b397af72..7bde3d138 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/calibrate-serving-simulation.json
@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
index 82c5e075a..0aed878fe 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
@@ -25,8 +25,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
index 307309178..2d7bf691a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/checkpoint-recovery-consistency.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
index 205979d6d..58c79e7a8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/choose-parallel-training-plan.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cite-check-downstream-pr.json
index 814e1cf82..e0f821341 100644
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index 1c6b2a733..2ee84f232 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/claim-contract.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
index 7bbf5c215..6a3a43dff 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/competitor-scan.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
index 64f7ad62d..46b404552 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dcp-async-save-performance.json
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@@ -23,8 +23,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
index 45146193f..565908142 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dense-performance-evidence.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
index 5cd5be992..7e59ca474 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/diagnose-vllm-admission-pressure.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
index 08c8b67e9..bbedc19a6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/draft-acceptance-issue.json
@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json
index 222005122..12a3f7538 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/evaluate-elastic-serving-placement.json
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@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
index 1cf810ede..6f8ef89ba 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-memory-management.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/host-overhead-optimization.json
index c0c1d6b7a..c90c487e4 100644
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index 838bd8fde..189266362 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-benchmark-design.json
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@@ -21,8 +21,8 @@
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index a1746e4d0..f91c53867 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/inference-optimization-casebook.json
@@ -21,14 +21,16 @@
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-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
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         "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/drama3-rejected-directions.md",
+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json",
+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md",
         "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json",
         "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md",
         "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/qwen-ascend-rejected-directions.json",
@@ -38,7 +40,7 @@
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@@ -47,11 +49,13 @@
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index 7b6c53cbc..33f4ce2a2 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
@@ -24,8 +24,8 @@
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-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
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index 888404431..c7a17a897 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kv-tier-management.json
@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
index 7d865eb6b..4f82952a8 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
@@ -22,8 +22,8 @@
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index bb87fb27a..f8d382652 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
@@ -21,8 +21,8 @@
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-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
index c1cae16f6..dced943c2 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
index a0118657f..041638f7f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
@@ -22,8 +22,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
index c990d7d1a..997f72e5e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
index 4e267dce1..1729ef960 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
@@ -21,8 +21,8 @@
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-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
index 9411a5eea..69fcfd57d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
@@ -16,8 +16,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
index c1af9ae56..080f3bec1 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
@@ -21,8 +21,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
index d41c517da..ab4ac3157 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
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@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
index e3441c44a..748cc0000 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
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@@ -23,8 +23,8 @@
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       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
index b9ed2b831..116d46e29 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-resource-budget/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
index a7288f445..48cca849c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
index 706db8622..7ff2ee155 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
index e670dc8c6..843ced24c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/94273606a05110f2d9826974f1031d3cf269ce01/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
-      "commit": "94273606a05110f2d9826974f1031d3cf269ce01",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
+      "commit": "ee06e5eeda65c779d9ac25f4b53f7fb3d4f14f55",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json",

From 5e22fb1a0062d91e64b5b2fb0e68090e1a51ff1e Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 18:37:01 +0800
Subject: [PATCH 35/40] Freeze independent packed pipeline replica screens

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 .../patch/peer-round2-tensor-handoff2x8.yaml  | 16 ++++++++++
 .../patch/peer-round2-tensor-handoff4x4.yaml  | 16 ++++++++++
 .../peer-round2-packed-stage-scaling.json     | 32 +++++++++++++++++++
 3 files changed, 64 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff2x8.yaml
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff4x4.yaml
 create mode 100644 evidence/minicpmo45-l20x-20261021/plan/peer-round2-packed-stage-scaling.json

diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff2x8.yaml b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff2x8.yaml
new file mode 100644
index 000000000..e2a1837e9
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff2x8.yaml
@@ -0,0 +1,16 @@
+base_config: minicpmo_4_5_turn.yaml
+cuda_mps: true
+connectors:
+  connector_of_shared_memory:
+    extra:
+      token2wav_spk_cuda_graph: true
+      cfm_float16: true
+stages:
+  - stage_id: 0
+    kv_cache_memory_bytes: 8589934592
+  - stage_id: 1
+    num_replicas: 2
+    devices: "0,0"
+  - stage_id: 2
+    num_replicas: 8
+    devices: "0,0,0,0,0,0,0,0"
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff4x4.yaml b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff4x4.yaml
new file mode 100644
index 000000000..dce64fc15
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff4x4.yaml
@@ -0,0 +1,16 @@
+base_config: minicpmo_4_5_turn.yaml
+cuda_mps: true
+connectors:
+  connector_of_shared_memory:
+    extra:
+      token2wav_spk_cuda_graph: true
+      cfm_float16: true
+stages:
+  - stage_id: 0
+    kv_cache_memory_bytes: 8589934592
+  - stage_id: 1
+    num_replicas: 4
+    devices: "0,0,0,0"
+  - stage_id: 2
+    num_replicas: 4
+    devices: "0,0,0,0"
diff --git a/evidence/minicpmo45-l20x-20261021/plan/peer-round2-packed-stage-scaling.json b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-packed-stage-scaling.json
new file mode 100644
index 000000000..6aa57a5a3
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/plan/peer-round2-packed-stage-scaling.json
@@ -0,0 +1,32 @@
+{
+  "frozen_at_utc": "2026-10-21T10:34:21.760257+00:00",
+  "plane": "infra",
+  "candidate_revision": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
+  "control": "screen-tensor-handoff25",
+  "hypothesis": "Earlier ordinary 1 Talker/2 vocoders to 2 Talkers/4 vocoders improved aggregate throughput, but changed both stages. After lossless transport, independently doubling either stage tests remaining host-side stage capacity versus GPU contention.",
+  "screens": [
+    {
+      "name": "screen-tensor-handoff4x4",
+      "replicas": [
+        1,
+        4,
+        4
+      ]
+    },
+    {
+      "name": "screen-tensor-handoff2x8",
+      "replicas": [
+        1,
+        2,
+        8
+      ]
+    }
+  ],
+  "fixed": "Same source,25-frame windows,CFM selective half,speaker graphs,8GiB Thinker KV,4GiB per Talker KV,model and sampling. Each screen varies one stage replica count only.",
+  "workload": "Same64 reused tuning prompts;C1/16/32 discard+one;all3 quality means;no holdout",
+  "resource_note": "One L20X per screen; use reservation queue; startup may take up to45min for13 processes. No same-device overlapping screens.",
+  "decision": "Run only if current packed25 screen completes without request errors and remains below matched peer at C16 or C32. Quality still independently gated.",
+  "acceptance": "Unchanged repeated same-GPU peer comparison and256-prompt clustered quality gates; these screens cannot qualify release.",
+  "verdict": "INCONCLUSIVE",
+  "holdout_used": false
+}

From 3c1b2ff969537f3216d0125d034ae903d0743e7a Mon Sep 17 00:00:00 2001
From: amy-why-3459 <wuhaiyan17@huawei.com>
Date: Wed, 21 Oct 2026 18:56:59 +0800
Subject: [PATCH 36/40] Record packed transport service screens and clean main
 composition

Agent-assisted-by: Codex (implementation)
Signed-off-by: amy-why-3459 <wuhaiyan17@huawei.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |    4 +-
 .../peer-round2-clean-main-composition.patch  | 1094 +++++++++++++++++
 .../patch/peer-round2-manifest.json           |   16 +-
 .../peer-round2-tensor-handoff-main.patch     |  494 ++++++++
 .../peer-round2-clean-main-composition.json   |   25 +
 .../results/peer-round2-screen-artifact.json  |    6 +-
 ...eer-round2-screen-requests-quality.json.gz |  Bin 977391 -> 1026685 bytes
 .../results/peer-round2-status.json           |    8 +-
 .../peer-round2-tensor-handoff-main.json      |   15 +
 .../peer-round2-tensor-handoff25-screen.json  |  167 +++
 .../peer-round2-tensor-handoff50-screen.json  |  167 +++
 11 files changed, 1989 insertions(+), 7 deletions(-)
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-clean-main-composition.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-main.patch
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-clean-main-composition.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-main.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff25-screen.json
 create mode 100644 evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff50-screen.json

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 2faef63d8..4793ad6a4 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -20,8 +20,10 @@ The requester asked to continue until vLLM-Omni exceeds the source-pinned single
 - [Three-repeat quality design](plan/peer-round2-quality-repeats.json) was frozen before generating any reserved holdout output. The256 paired prompt clusters remain the independent units: sum WER counts and average SIM/UTMOS within each prompt across three fixed-seed runs, then apply unchanged20,000-draw bootstrap and all9 margins. [Validator controls](validator/test_peer_round2_clustered_quality.py) pass8 synthetic cases; this is not a real quality verdict. Earlier FAILs remain unchanged.
 - [Same-GPU performance runner](validator/peer_round2_performance_pair.py) is prepared for the selected candidate: clean pinned sources, model hashes, a complete deployment YAML, one visible device, sequential fresh peer/candidate starts, and320 requests ×3 measured repeats at all six concurrencies. Its10 preflight controls pass; no final candidate comparison has run.
 - [CPU/GIL diagnostic](results/peer-round2-pipeline-cpu-profile.json) identified scalar-list storage in Talker as a hypothesis. The100Hz attempt accumulated67s sampling lag and was invalidated; a separate CPU-counter run and sparse2Hz nonblocking samples corroborate the location, without quantitative critical-path attribution. All diagnostic requests are excluded from performance reporting.
-- [Packed conditioning transport plan](plan/peer-round2-tensor-handoff.json) preserves ordinary-turn float32 values using the existing Omni serializer. The [synthetic CPU transport microbenchmark](results/peer-round2-tensor-handoff-micro.json) measures median34.53ms for lists versus0.498ms for packed bytes, with bitwise equal values. Source regression checks pass213 tests with1 existing skip; service gain and speech quality remain unverified.
+- [Packed conditioning transport plan](plan/peer-round2-tensor-handoff.json) preserves ordinary-turn float32 values using the existing Omni serializer. The [synthetic CPU transport microbenchmark](results/peer-round2-tensor-handoff-micro.json) measures median34.53ms for lists versus0.498ms for packed bytes, with bitwise equal values. Source regression checks pass213 tests with1 existing skip. The [25-frame screen](results/peer-round2-tensor-handoff25-screen.json) reaches C16/C32 1331.4/1573.5; the [50-frame screen](results/peer-round2-tensor-handoff50-screen.json) reaches1521.4/1839.8. Both have zero failed requests; quality scoring is pending, and neither beats the peer at C32. The50-frame C32 TTFA p50/p95 is1.097/1.687s, mean RTF0.393. These are single reused-cohort screens, not repeated same-GPU confirmation.
 - [50-frame exact-coverage contrast](results/peer-round2-window50-covered-screen.json) reaches C16/C32 1367.4/1663.7 but exceeds C1 WER and C32 SIM descriptive margins. [100-frame selective-CFM](results/peer-round2-window100-screen.json) and [FP32 control](results/peer-round2-fp32-window100-screen.json) also fail descriptive quality margins and do not beat the peer.
+- [Independent replica scaling plan](plan/peer-round2-packed-stage-scaling.json) tests Talker4/vocoder4 and Talker2/vocoder8 at the fixed25-frame window, changing one stage at a time. Both use the same packed source and remain exploratory.
+- [Standalone main-based transport](results/peer-round2-tensor-handoff-main.json) contains only the packed handoff change;213 tests and precommit pass. It excludes prior precision/speaker experiments and has not been service-tested as a standalone branch.
 - [Reproducible exploratory implementation patches](patch/peer-round2-manifest.json); none is presented as a qualified peer-beating release.
 
 
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-clean-main-composition.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-clean-main-composition.patch
new file mode 100644
index 000000000..b2121d7c7
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-clean-main-composition.patch
@@ -0,0 +1,1094 @@
+diff --git a/docs/design/minicpm_o45_mrv2_performance.md b/docs/design/minicpm_o45_mrv2_performance.md
+index c7b1969841..c7445e3737 100644
+--- a/docs/design/minicpm_o45_mrv2_performance.md
++++ b/docs/design/minicpm_o45_mrv2_performance.md
+@@ -22,7 +22,8 @@ opt-in CUDA overlay that runs all three duplex stages on MRv2. Turn results do
+ not establish duplex performance or interruption correctness.
+ 
+ The shared Code2Wav backend defaults to the fused CFM body on both CUDA and
+-NPU, subject to architecture and FP32 attention-cache eligibility. CUDA also
++NPU, subject to architecture and attention-cache eligibility. CUDA accepts
++matching FP32 or FP16 estimator/cache types; NPU retains FP32 eligibility. CUDA also
+ requires TF32 to be allowed; NPU fusion is independent of TF32. Set
+ `cfm_fused_body: false` in the stage connector extra to restore the original
+ body. On CUDA, disabling `token2wav_allow_tf32` or setting
+@@ -45,8 +46,9 @@ therefore be included in end-to-end regression validation.
+ CFM graph execution defaults to the fused DiT body on CUDA (when TF32 is
+ allowed) and on NPU. NVIDIA SM80+ uses tiled TF32 attention; older CUDA devices
+ use the fused body's SDPA fallback. NPU uses packed QKV, in-place KV and ACLNN
+-AddLayerNorm, independent of TF32. Unsupported DiT layouts or non-FP32 attention
+-caches retain the original body. Other platforms retain their existing default.
++AddLayerNorm, independent of TF32. Unsupported DiT layouts and cache types
++retain the original body. CUDA supports matching FP32 or FP16 estimator/cache
++types; NPU supports FP32. Other platforms retain their existing default.
+ Set `cfm_fused_body: false` in connector `extra` to restore the original body.
+ On CUDA, disabling TF32 with `token2wav_allow_tf32: false` or
+ `MINICPMO_CODE2WAV_TF32=off` also disables the default fusion choice; an explicit
+@@ -54,6 +56,38 @@ On CUDA, disabling TF32 with `token2wav_allow_tf32: false` or
+ Slot pooling and its `cfm_row_offset_merge` option remain opt-in. Fusion changes
+ floating-point rounding and does not promise identical waveforms.
+ 
++## Optional CFM precision and speaker replay
++
++`cfm_float16: true` in connector `extra` opts CUDA Code2Wav into FP16 for the
++CFM estimator, its random-noise table and attention caches. The flow encoder,
++speaker extraction and HiFT retain their existing precision. This differs
++from `token2wav_float16`, which affects the whole flow. FP16 CFM changes
++rounding and requires speech-quality and service validation; it is off by
++default and does not reduce the number of flow steps.
++
++`token2wav_spk_cuda_graph: true` opts the CUDA Torch CAM++ backend into
++exact-shape graph replay. It requires the Torch speaker backend and rejects
++CPU/NPU or TensorRT speaker configurations. Up to four feature shapes are
++captured without padding; additional shapes use the existing eager forward.
++Autocast or a changed precision policy also uses the eager path. Each replay
++returns an owned embedding. This option is off by default and does not expand
++the reference-audio cache or batch reference extraction.
++
++## Turn-mode conditioning transport
++
++Ordinary turn-mode `llm2tts` packs reference audio and thinker hidden states
++with the existing Omni tensor serializer. The request envelope's
++`model_intermediate_buffer` is untyped, so these values cross EngineCore as
++owned bytes and are restored to CPU float32 tensors by the Talker and codec
++bridge. This avoids scalar-list construction, worker list traversal and
++list-to-tensor conversion. Values match the previous list-to-float32 path;
++sampling and acoustic computation are unchanged.
++
++Legacy lists and local tensors remain accepted by consumers. Native duplex
++continues producing its existing lists. Each decode owns its storage, and the
++packed snapshot cannot be changed by later producer mutations. Transport
++microbenchmarks alone do not establish service throughput or speech quality.
++
+ ## Code2Wav batching across reference audio
+ 
+ With CUDA ragged Whole-Euler enabled, ready requests with different reference
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+new file mode 100644
+index 0000000000..39c416ddaf
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_cfm_tiled_attention.py
+@@ -0,0 +1,57 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Tiled attention must preserve masking and pooled-row ownership in FP16."""
++
++import pytest
++import torch
++import torch.nn.functional as F
++from torch.nn.attention import SDPBackend, sdpa_kernel
++
++from tests.helpers.mark import hardware_marks
++from vllm_omni.model_executor.models.minicpmo_4_5.cfm_attention import cfm_attention
++
++pytestmark = [pytest.mark.core_model, *hardware_marks(res={"cuda": "L4"}, num_cards=1)]
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++@pytest.mark.parametrize("pooled", [False, True])
++@pytest.mark.parametrize("masked", [False, True])
++@pytest.mark.parametrize("frames,history", [(1, 17), (23, 65), (50, 513)])
++def test_tiled_attention_matches_math_sdpa(dtype, pooled, masked, frames, history):
++    generator = torch.Generator(device="cuda").manual_seed(43)
++    batch, heads, width = 3, 4, 64
++    q = torch.randn(batch, heads, frames, width, device="cuda", dtype=dtype, generator=generator)
++    # K and V are interleaved in the real resident pool, so both views are strided.
++    storage = torch.randn(
++        7 if pooled else batch, heads, history, 2 * width, device="cuda", dtype=dtype, generator=generator
++    )
++    k, v = storage[..., :width], storage[..., width:]
++    rows = torch.tensor([5, 1, 5], device="cuda") if pooled else None
++    mask = None
++    if masked:
++        mask = torch.rand(batch, frames, history, device="cuda", generator=generator) > 0.3
++        mask[0, 0] = False
++    expected_k = k.index_select(0, rows) if pooled else k
++    expected_v = v.index_select(0, rows) if pooled else v
++    with sdpa_kernel(SDPBackend.MATH):
++        expected = F.scaled_dot_product_attention(
++            q.float(),
++            expected_k.float(),
++            expected_v.float(),
++            attn_mask=mask.unsqueeze(1) if mask is not None else None,
++        ).to(dtype)
++    actual = cfm_attention(q, k, v, mask, rows)
++    torch.testing.assert_close(actual, expected, atol=2e-3, rtol=2e-3)
++    assert torch.isfinite(actual).all()
++    if masked:
++        assert torch.count_nonzero(actual[0, :, 0]) == 0
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float16])
++def test_tiled_attention_rejects_mixed_cache_dtype(dtype):
++    q = torch.empty(1, 1, 1, 16, dtype=dtype)
++    cache_dtype = torch.float16 if dtype == torch.float32 else torch.float32
++    k = torch.empty_like(q, dtype=cache_dtype)
++    with pytest.raises(ValueError, match="matching float32 or float16"):
++        cfm_attention(q, k, k)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+index a9d18d2f0a..76c1058057 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_code2wav_device_spk_flag.py
+@@ -37,11 +37,15 @@ class _FakeToken2Wav:
+         self.device_spk_calls = 0
+         self.trt_spk_calls = 0
+         self.device_spk_use_trt = None
++        self.speaker_graph_config = None
+ 
+     def enable_device_spk_embedding(self, *, use_trt=True):
+         self.device_spk_calls += 1
+         self.device_spk_use_trt = use_trt
+ 
++    def enable_speaker_cuda_graph(self, config):
++        self.speaker_graph_config = config
++
+     def enable_trt_spk_embedding(self):
+         self.trt_spk_calls += 1
+ 
+@@ -149,6 +153,7 @@ def test_cuda_speaker_backend_preserves_lazy_model_loading(tmp_path, monkeypatch
+ 
+ 
+ _OTHER_DEFAULTS = {
++    "token2wav_spk_cuda_graph",
+     "token2wav_float16",
+     "token2wav_trt",
+     "code2wav_bfloat16_attention_cache",
+@@ -263,3 +268,12 @@ def test_tf32_mode_is_resolved_once_and_reused(tmp_path, monkeypatch, device_pla
+     # Mutating the stage config afterwards must not re-read it per forward.
+     model.vllm_config.model_config.stage_connector_config["extra"]["token2wav_allow_tf32"] = True
+     assert model._tf32_mode == "off"
++
++
++@pytest.mark.parametrize("value,enabled", [(True, True), ("true", True), (False, False), ("false", False)])
++def test_speaker_graph_flag_reaches_selected_backend(tmp_path, monkeypatch, value, enabled):
++    monkeypatch.setattr(current_omni_platform, "is_cuda", lambda: True)
++    monkeypatch.setattr(current_omni_platform, "is_npu", lambda: False)
++    model, speaker = _build_backend(tmp_path, monkeypatch, {"token2wav_spk_cuda_graph": value})
++    assert speaker.device_spk_calls == 1
++    assert speaker.speaker_graph_config is (model.vllm_config if enabled else None)
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+index 3cf8bdd941..e40424b57c 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_dit_fused.py
+@@ -44,14 +44,17 @@ def _run(body, estimator, *, rows: int, frames: int, cached: int, lengths):
+     channels = estimator.blocks[0].conv.block[1].in_channels
+     attn = estimator.blocks[0].attn
+     device = next(estimator.parameters()).device
+-    estimator_input = torch.randn(rows, 320, frames, device=device)
+-    time_embedding = estimator.t_embedder(torch.rand((), device=device).expand(rows)).unsqueeze(1)
++    dtype = next(estimator.parameters()).dtype
++    estimator_input = torch.randn(rows, 320, frames, device=device, dtype=dtype)
++    time_embedding = estimator.t_embedder(torch.rand((), device=device, dtype=dtype).expand(rows)).unsqueeze(1)
+     mask = torch.rand(rows, frames, cached + frames, device=device) > 0.3
+     mask[..., 0] = True
+-    cnn = [torch.randn(rows, 2 * channels, 2, device=device) for _ in range(depth)]
+-    att = [torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device) for _ in range(depth)]
+-    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device)
+-    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device)
++    cnn = [torch.randn(rows, 2 * channels, 2, device=device, dtype=dtype) for _ in range(depth)]
++    att = [
++        torch.randn(rows, attn.num_heads, cached, 2 * attn.head_dim, device=device, dtype=dtype) for _ in range(depth)
++    ]
++    cnn_out = torch.zeros((depth, rows, 2 * channels, 2), device=device, dtype=dtype)
++    att_out = torch.zeros((depth, rows, attn.num_heads, cached + frames, 2 * attn.head_dim), device=device, dtype=dtype)
+     with torch.no_grad():
+         out = body(estimator, estimator_input, time_embedding, mask, cnn, att, cnn_out, att_out, lengths)
+     return out, cnn_out, att_out
+@@ -93,3 +96,64 @@ def test_ragged_body_reuses_modulation_without_recomputing_adaln(monkeypatch, ca
+     actual = _run(precomputed, estimator, rows=4, frames=6, cached=cached, lengths=[6, 4])
+     for want, got in zip(expected, actual, strict=True):
+         torch.testing.assert_close(got, want, rtol=1e-4, atol=2e-5)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_fp16_fused_body_matches_fp16_ragged_body(monkeypatch):
++    estimator = _upstream_dit("cuda").half()
++    driver = BatchedToken2Wav.__new__(BatchedToken2Wav)
++    nn.Module.__init__(driver)
++    driver._ragged_fused_body = True
++    calls = []
++
++    def fused(*args, **kwargs):
++        calls.append(True)
++        return blocks_forward_chunk_fused(*args, **kwargs)
++
++    monkeypatch.setattr(
++        "vllm_omni.model_executor.models.minicpmo_4_5.batched_token2wav.blocks_forward_chunk_fused",
++        fused,
++    )
++    with torch.inference_mode(), torch.autocast("cuda", dtype=torch.float16):
++        expected = _run(
++            BatchedToken2Wav._blocks_forward_chunk_ragged,
++            estimator,
++            rows=4,
++            frames=6,
++            cached=5,
++            lengths=[6, 4],
++        )
++        actual = _run(driver._ragged_body, estimator, rows=4, frames=6, cached=5, lengths=[6, 4])
++    assert calls, "FP16 service dispatch must use the fused body"
++    for want, got in zip(expected, actual, strict=True):
++        torch.testing.assert_close(got, want, rtol=2e-3, atol=2e-3)
++
++
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="requires CUDA")
++def test_cfm_only_fp16_preserves_encoder_precision_and_returns_half_caches():
++    from tests.model_executor.models.minicpmo_4_5.test_code2wav_batching import _FakeToken2Wav
++
++    token2wav = _FakeToken2Wav()
++    token2wav.flow.encoder.register_parameter("anchor", nn.Parameter(torch.ones(1, device="cuda")))
++    token2wav.flow.decoder.estimator = _upstream_dit("cuda")
++    token2wav.flow.decoder.rand_noise = torch.randn(1, 80, 100, device="cuda")
++    backend = BatchedToken2Wav(token2wav, cfm_float16=True)
++    assert not backend.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
++    assert next(token2wav.flow.decoder.estimator.parameters()).dtype == torch.float16
++    matrix = torch.randn(8, 8, device="cuda")
++    with backend._autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float32
++    with backend._cfm_autocast(matrix.device):
++        assert (matrix @ matrix).dtype == torch.float16
++    assert not torch.is_autocast_enabled("cuda")
++    with torch.inference_mode():
++        mel, cnn, att = backend._decode_cfm(
++            torch.randn(1, 80, 6, device="cuda"),
++            torch.randn(1, 80, device="cuda"),
++            torch.randn(1, 80, 6, device="cuda"),
++            cnn_cache=None,
++            att_cache=None,
++        )
++    assert mel.dtype == cnn.dtype == att.dtype == torch.float16
++    assert token2wav.flow.encoder.anchor.dtype == torch.float32
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py b/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
+index d93755fec0..e10fecfc92 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
+@@ -22,6 +22,7 @@ from types import SimpleNamespace
+ import pytest
+ import torch
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_omni import (
+     MiniCPMO45OmniForConditionalGeneration,
+ )
+@@ -149,7 +150,10 @@ class TestBasicShape:
+         out = llm2tts([thinker_output], prompt=None)
+ 
+         assert out[0]["prompt_token_ids"] == [0, 0, 0]
+-        assert torch.equal(torch.tensor(out[0]["model_intermediate_buffer"]["hidden_states"]["tts"]), hidden[1:])
++        assert torch.equal(
++            torch.as_tensor(unpack_handoff_tensor(out[0]["model_intermediate_buffer"]["hidden_states"]["tts"])),
++            hidden[1:],
++        )
+ 
+     def test_returns_one_entry_per_input(self) -> None:
+         hidden = torch.zeros((3, _HIDDEN_DIM))
+@@ -210,7 +214,7 @@ class TestBasicShape:
+         buffer = result["model_intermediate_buffer"]
+         assert result["prompt_token_ids"] == [0, 0, 0, 0]
+         assert buffer["ids"]["tts"] == [20, 21]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[2:4])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[2:4])
+ 
+     def test_latent_in_multimodal_output_takes_precedence(self) -> None:
+         # When both ``multimodal_output["latent"]`` and ``hidden_states`` are
+@@ -234,7 +238,9 @@ class TestBasicShape:
+         )
+         buffer = result[0]["model_intermediate_buffer"]
+         # latent (ones) won over hidden_states (zeros)
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), latent[3:4].to(torch.float32))
++        assert torch.equal(
++            torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), latent[3:4].to(torch.float32)
++        )
+ 
+ 
+ class TestTtsRegionDetection:
+@@ -269,7 +275,7 @@ class TestTtsRegionDetection:
+         # 4.5 BOS at idx 2 -> slice starts at 3; end at idx 5 -> slice ends at 5.
+         buffer, hidden = self._run([10, 11], [151703, 30, 31, tts_end_id, 40])
+         assert buffer["ids"]["tts"] == [30, 31]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[3:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[3:5])
+ 
+     def test_bos_without_eos_runs_to_end(self) -> None:
+         # When BOS is found but EOS is missing (typical for an in-flight or
+@@ -278,12 +284,12 @@ class TestTtsRegionDetection:
+         # sequence: [10, 11, 151703, 30, 31]
+         buffer, hidden = self._run([10, 11], [151703, 30, 31])
+         assert buffer["ids"]["tts"] == [30, 31]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[3:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[3:5])
+ 
+     def test_plain_chat_without_tts_markers_uses_assistant_span(self) -> None:
+         buffer, hidden = self._run([10, 11], [20, 21, 22])
+         assert buffer["ids"]["tts"] == [20, 21, 22]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[2:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[2:5])
+ 
+ 
+ class TestPromptAndMultiModal:
+@@ -325,7 +331,7 @@ class TestPromptAndMultiModal:
+         )
+ 
+         intermediate_buffer = stage_outputs[0]["model_intermediate_buffer"]
+-        assert intermediate_buffer["codes"]["ref"] == [0.25, -0.5]
++        assert torch.equal(unpack_handoff_tensor(intermediate_buffer["codes"]["ref"]), torch.tensor([0.25, -0.5]))
+         assert intermediate_buffer["meta"]["ref_audio_sr"] == 16000
+ 
+     def test_serving_reference_audio_is_added_to_stage_handoff(self) -> None:
+@@ -338,7 +344,7 @@ class TestPromptAndMultiModal:
+         )
+ 
+         intermediate_buffer = stage_outputs[0]["model_intermediate_buffer"]
+-        assert intermediate_buffer["codes"]["ref"] == [0.125, -0.25]
++        assert torch.equal(unpack_handoff_tensor(intermediate_buffer["codes"]["ref"]), torch.tensor([0.125, -0.25]))
+         assert intermediate_buffer["meta"]["ref_audio_sr"] == 24000
+ 
+     def test_missing_reference_audio_does_not_add_stage_handoff_fields(self) -> None:
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..0b739fade8
+--- /dev/null
++++ b/tests/model_executor/models/minicpmo_4_5/test_speaker_cuda_graph.py
+@@ -0,0 +1,81 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++from types import SimpleNamespace
++
++import pytest
++import torch
++from vllm.config import ModelConfig, VllmConfig
++
++from tests.helpers.mark import hardware_test
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++pytestmark = [pytest.mark.core_model]
++
++
++class _Speaker(torch.nn.Module):
++    def forward(self, x):
++        return x.mean(dim=1)
++
++
++def _config():
++    config = VllmConfig()
++    config.model_config = ModelConfig.__new__(ModelConfig)
++    config.model_config.multimodal_config = None
++    return config
++
++
++@pytest.mark.cpu
++def test_cpu_fallback_does_not_mutate_shared_model_or_config():
++    speaker = CampplusTorch(_Speaker(), "cpu")
++    config = _config()
++    wrapper = SpeakerCudaGraph(speaker, config)
++    feat = torch.randn(17, 80, dtype=torch.bfloat16)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert config.model_config.multimodal_config is None
++    assert wrapper.graph.vllm_config.model_config.multimodal_config is not None
++    assert not wrapper.graph.graphs
++    assert wrapper.speaker is speaker
++
++
++@pytest.mark.cpu
++def test_facade_rejects_non_torch_speaker():
++    from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_token2wav import MiniCPMO45Token2wav
++
++    facade = MiniCPMO45Token2wav.__new__(MiniCPMO45Token2wav)
++    facade._core = SimpleNamespace(_spk_model=object())
++    with pytest.raises(ValueError, match="CUDA Torch speaker"):
++        facade.enable_speaker_cuda_graph(_config())
++
++
++@hardware_test(res={"cuda": "L4"}, num_cards=1)
++@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA required")
++@torch.inference_mode()
++def test_replay_ownership_shape_capacity_and_precision_fallback():
++    speaker = CampplusTorch(_Speaker(), "cuda:0")
++    wrapper = SpeakerCudaGraph(speaker, _config(), max_graphs=1)
++    feat = torch.randn(17, 80, device="cuda")
++    wrapper(feat)
++    retained = wrapper(feat)
++    expected = speaker(feat).clone()
++    feat.add_(3)
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert torch.equal(retained, expected)
++    assert len(wrapper.graph.graphs) == 1
++    other = torch.randn(19, 80, device="cuda")
++    assert torch.equal(wrapper(other), speaker(other))
++    assert len(wrapper.graph.graphs) == 1
++    hits = wrapper.graph.get_cumulative_stats()["graph_hits"]
++    original = torch.backends.cudnn.allow_tf32
++    try:
++        torch.backends.cudnn.allow_tf32 = not original
++        assert torch.equal(wrapper(feat), speaker(feat))
++        assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits
++    finally:
++        torch.backends.cudnn.allow_tf32 = original
++    assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
++    with torch.autocast("cuda", dtype=torch.bfloat16):
++        assert torch.equal(wrapper(feat), speaker(feat))
++    assert wrapper.graph.get_cumulative_stats()["graph_hits"] == hits + 1
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py b/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
+index fc3b66cb36..eadfda43e7 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
+@@ -13,6 +13,7 @@ import torch
+ import torch.nn as nn
+ from torch.overrides import TorchFunctionMode
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_omni import (
+     MiniCPMO45OmniForConditionalGeneration,
+ )
+@@ -1049,7 +1050,8 @@ def test_empty_speech_segment_finishes_without_sampling_codes() -> None:
+     assert decode_updates["codes"]["audio"].shape == (0,)
+ 
+ 
+-def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker) -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker, packed) -> None:
+     talker = _make_talker()
+     talker.emb_text = nn.Embedding(1, 2)
+     condition = torch.arange(18, dtype=torch.float32).reshape(9, 2)
+@@ -1063,7 +1065,7 @@ def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker) -> Non
+         _omni_prompt_len=68,
+         request_id="req-chunked-prefill",
+         tts_token_ids=torch.tensor([1]),
+-        tts_hidden_states=torch.ones(1, 2),
++        tts_hidden_states=pack_handoff_tensor(torch.ones(1, 2)) if packed else torch.ones(1, 2),
+     )
+ 
+     assert torch.equal(embeds, condition)
+diff --git a/tests/model_executor/models/test_minicpmo_handoff.py b/tests/model_executor/models/test_minicpmo_handoff.py
+new file mode 100644
+index 0000000000..f861646fab
+--- /dev/null
++++ b/tests/model_executor/models/test_minicpmo_handoff.py
+@@ -0,0 +1,51 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++from typing import Any
++
++import pytest
++import torch
++from vllm.v1.serial_utils import MsgpackDecoder, MsgpackEncoder
++
++from vllm_omni.distributed.omni_connectors.utils.serialization import OmniSerializer
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor, unpack_handoff_tensor
++
++pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float64, torch.bfloat16])
++@pytest.mark.parametrize("shape", [(), (0, 4), (3, 4), (144000,)])
++def test_packed_handoff_matches_legacy_values_across_untyped_wire(dtype, shape):
++    source = (
++        torch.linspace(-1.23456789, 1.987654321, int(torch.tensor(shape).prod().item()), dtype=torch.float64)
++        .reshape(shape)
++        .to(dtype)
++    )
++    if source.ndim == 2:
++        source = source.t()
++    expected = torch.tensor(source.tolist(), dtype=torch.float32).reshape(source.shape)
++    packed = pack_handoff_tensor(source)
++    envelope = {"model_intermediate_buffer": {"hidden_states": {"tts": packed}}}
++    # The real request field is dict[str, Any]: raw tensors cannot rely on a
++    # typed decoder hook here. Only standard bytes cross this boundary.
++    received = MsgpackDecoder(dict[str, Any]).decode(MsgpackEncoder().encode(envelope))
++    actual = unpack_handoff_tensor(received["model_intermediate_buffer"]["hidden_states"]["tts"])
++    assert isinstance(actual, torch.Tensor)
++    assert actual.shape == source.shape
++    assert torch.equal(actual, expected)
++    source.fill_(-7)
++    assert torch.equal(actual, expected)
++    other = unpack_handoff_tensor(packed)
++    actual.fill_(9)
++    assert torch.equal(other, expected)
++
++
++def test_legacy_handoff_values_remain_supported():
++    for value in (None, [1.0, 2.0], torch.ones(2)):
++        assert unpack_handoff_tensor(value) is value
++
++
++@pytest.mark.parametrize("payload", ["not a tensor", [1.0], torch.ones(2, dtype=torch.int64)])
++def test_invalid_packed_type_rejected(payload):
++    with pytest.raises(ValueError, match="CPU float32 tensor"):
++        unpack_handoff_tensor(OmniSerializer.serialize(payload))
+diff --git a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
+index 13036689ba..c3b8e69f90 100644
+--- a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
++++ b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
+@@ -8,6 +8,7 @@ import pytest
+ import torch
+ from vllm.v1.request import RequestStatus
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor
+ from vllm_omni.model_executor.stage_input_processors.minicpmo_4_5_omni import (
+     _extract_codec_delta,
+     tts2code2wav_async_chunk,
+@@ -237,11 +238,12 @@ def test_duplex_final_segment_preserves_every_code_and_closes_once(
+     assert not duplicate.meta.last_chunk
+ 
+ 
+-def test_first_chunk_forwards_reference_voice_and_duplex_identity() -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_first_chunk_forwards_reference_voice_and_duplex_identity(packed) -> None:
+     manager = _manager()
+     request = _request("req")
+     request.model_intermediate_buffer = {
+-        "codes": {"ref": [0.1, -0.1]},
++        "codes": {"ref": pack_handoff_tensor(torch.tensor([0.1, -0.1])) if packed else [0.1, -0.1]},
+         "meta": {"ref_audio_sr": 16000},
+     }
+     request.additional_information = {
+@@ -292,11 +294,12 @@ def test_first_chunk_falls_back_to_legacy_reference_fields() -> None:
+     assert payload.meta.ref_audio_sr == 16000
+ 
+ 
+-def test_full_payload_forwards_all_codes_and_request_metadata() -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_full_payload_forwards_all_codes_and_request_metadata(packed) -> None:
+     manager = _manager()
+     request = _request("req")
+     request.model_intermediate_buffer = {
+-        "codes": {"ref": [0.1, -0.1]},
++        "codes": {"ref": pack_handoff_tensor(torch.tensor([0.1, -0.1])) if packed else [0.1, -0.1]},
+         "meta": {
+             "ref_audio_sr": 16000,
+             "native_duplex_segment_text": "hello",
+diff --git a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
+index edb5a3535f..c9c385cc70 100644
+--- a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
++++ b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
+@@ -7,6 +7,7 @@ import pytest
+ import torch
+ 
+ from vllm_omni.engine.orchestrator import StreamingInputState
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.stage_input_processors.minicpmo_4_5_omni import (
+     _extract_first_audio_ref,
+     llm2tts,
+@@ -71,7 +72,7 @@ def test_plain_chat_handoff_owns_talker_prompt_contract() -> None:
+ 
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == output_ids
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[2:4])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[2:4])
+     assert converted["prompt_token_ids"] == [0, 0, 0, 0]
+     assert info["meta"]["replace_streaming_prompt"] is True
+     assert info["meta"]["next_stage_prompt_len"] == 4
+@@ -98,7 +99,7 @@ def test_llm2tts_carries_request_ref_audio() -> None:
+     )[0]
+ 
+     info = converted["model_intermediate_buffer"]
+-    assert info["codes"]["ref"] == ref_waveform.tolist()
++    assert torch.equal(unpack_handoff_tensor(info["codes"]["ref"]), ref_waveform)
+     assert info["meta"]["ref_audio_sr"] == 22050
+     assert info["ids"]["tts"] == [11, 12]
+ 
+@@ -191,7 +192,7 @@ def test_native_duplex_uses_forwarded_row_ledger_after_later_audio_prefill() ->
+ 
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_selects_latest_contiguous_forwarded_span() -> None:
+@@ -224,7 +225,7 @@ def test_native_duplex_selects_latest_contiguous_forwarded_span() -> None:
+     converted = llm2tts([source], prompt=[{}], _streaming_context=context)[0]
+ 
+     info = converted["model_intermediate_buffer"]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[5:7])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[5:7])
+ 
+ 
+ def test_native_duplex_rejects_missing_forwarded_terminal_token() -> None:
+@@ -303,7 +304,7 @@ def test_native_duplex_ledger_tolerates_async_lookahead_row_after_terminator() -
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_ledger_without_forwarded_terminator() -> None:
+@@ -317,7 +318,7 @@ def test_native_duplex_ledger_without_forwarded_terminator() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_turn_eos_row_is_handed_to_talker() -> None:
+@@ -333,7 +334,7 @@ def test_native_duplex_turn_eos_row_is_handed_to_talker() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 9310]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+     assert info["meta"]["turn_end"] is True
+ 
+ 
+@@ -351,7 +352,7 @@ def test_native_duplex_ledger_anchors_on_unit_after_reinjected_listens() -> None
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[9:11])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[9:11])
+ 
+ 
+ @pytest.mark.parametrize("previous_terminator_forwarded", [False, True])
+@@ -372,7 +373,10 @@ def test_native_duplex_ledger_prefers_latest_repeat_of_the_unit(
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[current_start + 1 : current_start + 3])
++    assert torch.equal(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])),
++        latent[current_start + 1 : current_start + 3],
++    )
+ 
+ 
+ def test_native_duplex_ledger_rejects_non_contiguous_positions() -> None:
+@@ -397,7 +401,7 @@ def test_native_duplex_mid_turn_tts_bos_slices_after_boundary() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ @pytest.mark.parametrize("opening", [9304, 9301])
+@@ -417,7 +421,9 @@ def test_native_duplex_mid_unit_tts_bos_keeps_earlier_text(opening, turn_end) ->
+ 
+     expected = [21, 22, 9301, 9310] if turn_end else [21, 22, 9301]
+     assert info["ids"]["tts"] == expected
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[3 : 3 + len(expected)])
++    torch.testing.assert_close(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3 : 3 + len(expected)]
++    )
+     assert info.get("meta", {}).get("turn_end", False) is turn_end
+ 
+ 
+@@ -435,7 +441,9 @@ def test_native_duplex_folded_boundary_with_mid_unit_tts_bos(terminator) -> None
+ 
+     expected = [21, 22, 9301, *terminator[:-1]]
+     assert info["ids"]["tts"] == expected
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[2 : 2 + len(expected)])
++    torch.testing.assert_close(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[2 : 2 + len(expected)]
++    )
+ 
+ 
+ @pytest.mark.parametrize("folded_decisions", [0, 1, 2])
+@@ -471,7 +479,7 @@ def test_native_duplex_tts_bos_aligns_after_window_rebuild(folded_decisions, bos
+     converted = llm2tts([source], prompt=[{}], _streaming_context=SimpleNamespace(bridge_states={}))[0]
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == [21, 22]
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[-3:-1])
++    torch.testing.assert_close(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[-3:-1])
+ 
+ 
+ def test_native_duplex_continuation_appends_only_new_talker_condition() -> None:
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+index 3e9c849670..96bf8528d1 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/batched_token2wav.py
+@@ -322,14 +322,20 @@ def _cfm_matmul_tf32(fn):
+ 
+     @functools.wraps(fn)
+     def wrapper(self, *args, **kwargs):
+-        if not getattr(self, "_cfm_tf32", False):
+-            return fn(self, *args, **kwargs)
+-        previous = torch.backends.cuda.matmul.allow_tf32
+-        torch.backends.cuda.matmul.allow_tf32 = True
+-        try:
+-            return fn(self, *args, **kwargs)
+-        finally:
+-            torch.backends.cuda.matmul.allow_tf32 = previous
++        precision = (
++            self._cfm_autocast(next(self.flow.parameters()).device)
++            if getattr(self, "_cfm_only_float16", False)
++            else nullcontext()
++        )
++        with precision:
++            if not getattr(self, "_cfm_tf32", False):
++                return fn(self, *args, **kwargs)
++            previous = torch.backends.cuda.matmul.allow_tf32
++            torch.backends.cuda.matmul.allow_tf32 = True
++            try:
++                return fn(self, *args, **kwargs)
++            finally:
++                torch.backends.cuda.matmul.allow_tf32 = previous
+ 
+     return wrapper
+ 
+@@ -355,6 +361,7 @@ class BatchedToken2Wav(nn.Module):
+         setup_cache_size: int = 1,
+         cfm_tf32: bool = False,
+         encoder_graph_config: Mapping[str, Any] | None = None,
++        cfm_float16: bool = False,
+     ):
+         super().__init__()
+         if setup_cache_size < 0:
+@@ -371,6 +378,13 @@ class BatchedToken2Wav(nn.Module):
+         self.flow = token2wav.flow
+         self.hift = token2wav.hift
+         flow_parameter = next(self.flow.parameters(), None)
++        self._cfm_only_float16 = bool(cfm_float16 and not token2wav.float16)
++        if self._cfm_only_float16:
++            if flow_parameter is None or flow_parameter.device.type != "cuda":
++                raise ValueError("cfm_float16 requires CUDA")
++            self.flow.decoder.estimator.half()
++            self.flow.decoder.rand_noise = self.flow.decoder.rand_noise.half()
++
+         if flow_parameter is not None and flow_parameter.device.type == "npu":
+             from vllm_omni.platforms.npu.models.minicpmo_fused import prepare_estimator
+ 
+@@ -431,7 +445,7 @@ class BatchedToken2Wav(nn.Module):
+             del speech, source
+             torch.accelerator.empty_cache()
+         self.float16 = bool(token2wav.float16)
+-        self._estimator_att_compute_dtype = torch.float16 if self.float16 else torch.float32
++        self._estimator_att_compute_dtype = torch.float16 if self.float16 or self._cfm_only_float16 else torch.float32
+         self._estimator_att_cache_dtype = (
+             torch.bfloat16 if bfloat16_attention_cache else self._estimator_att_compute_dtype
+         )
+@@ -494,17 +508,25 @@ class BatchedToken2Wav(nn.Module):
+                 micro_batch_size = int(micro_batch_size_cfg) if micro_batch_size_cfg is not None else 4
+                 enable_whole_euler = bool(cfm_graph_cfg.get("enable_whole_euler", True))
+                 if bool(cfm_graph_cfg.get("fused_body", False)):
+-                    # A reduced-precision attention cache keeps the ragged body,
+-                    # which attends in the activation dtype through upstream.
++                    # A BF16 storage-only cache still uses the ragged body.
++                    # CUDA FP16 flow can keep its matching FP16 cache resident.
+                     # NPU uses the same schedule with AddLayerNorm and packed QKV.
+                     self._ragged_fused_body = (
+                         flow_parameter.device.type in {"cuda", "npu"}
+                         and supports_fused_body(estimator)
+-                        and self._estimator_att_cache_dtype == torch.float32
++                        and (
++                            self._estimator_att_cache_dtype == torch.float32
++                            or (
++                                flow_parameter.device.type == "cuda"
++                                and self._estimator_att_cache_dtype == torch.float16
++                                and self._estimator_att_compute_dtype == torch.float16
++                            )
++                        )
+                     )
+                     if not self._ragged_fused_body:
+                         logger.warning(
+-                            "cfm_fused_body requested but unsupported here (DiT blocks or a non-fp32 attention cache)"
++                            "cfm_fused_body requested but unsupported here "
++                            "(DiT blocks or incompatible attention cache dtype)"
+                         )
+                 # Resident request caches need the fused body and its tiled
+                 # attention, which reads keys/values out of the pool in place.
+@@ -688,6 +710,11 @@ class BatchedToken2Wav(nn.Module):
+             projected = torch.cat([self._project_speakers(feature.speaker_embedding) for feature in features])
+         return [int(feature.mels.shape[1]) for feature in features], projected
+ 
++    def _cfm_autocast(self, device: torch.device):
++        if self._cfm_only_float16:
++            return torch.amp.autocast(device.type, dtype=torch.float16)
++        return self._autocast(device)
++
+     def _autocast(self, device: torch.device):
+         if device.type != "cuda":
+             return nullcontext()
+@@ -1086,7 +1113,10 @@ class BatchedToken2Wav(nn.Module):
+         ``modulation`` comes from the Whole-Euler arena, for either body.
+         """
+         estimator_input = args[1]
+-        if slots is not None or (self._ragged_fused_body and estimator_input.dtype == torch.float32):
++        fused_dtype = estimator_input.dtype == torch.float32 or (
++            estimator_input.is_cuda and estimator_input.dtype == torch.float16
++        )
++        if slots is not None or (self._ragged_fused_body and fused_dtype):
+             # Slot-pool graphs are only built over the fused body (``slot_pool`` above).
+             if estimator_input.device.type == "npu":
+                 from vllm_omni.platforms.npu.models.minicpmo_fused import (
+@@ -1339,6 +1369,8 @@ class BatchedToken2Wav(nn.Module):
+         cache in the same form, already trimmed by ``att_keep``; the eager
+         path returns it stacked and untrimmed (ragged: per request, untrimmed).
+         """
++        if self._cfm_only_float16:
++            mu, speakers, cond = mu.half(), speakers.half(), cond.half()
+         decoder = self.flow.decoder
+         estimator = decoder.estimator
+         batch_size = int(mu.shape[0])
+@@ -1734,7 +1766,7 @@ class BatchedToken2Wav(nn.Module):
+         wrapper = self._whole_euler_graph_wrapper
+         prompt_len = int(features.mels.shape[1])
+         steady = prompt_len + _CACHE_TRIM_SUFFIX
+-        with self._autocast(wrapper.device):
++        with self._cfm_autocast(wrapper.device):
+             return wrapper.precapture(
+                 offsets=range(prompt_len, steady + 1),
+                 steady=steady,
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+index 3ab3f7f96a..e64fcd2f82 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/cfm_attention.py
+@@ -1,6 +1,6 @@
+ # SPDX-License-Identifier: Apache-2.0
+ # SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
+-"""Tiled CFM attention: float32 tensors, ordinary TF32 Tensor Core dots."""
++"""Tiled CFM attention with FP32/TF32 or FP16 Tensor Core dots."""
+ 
+ import torch
+ from vllm.triton_utils import tl, triton
+@@ -80,7 +80,7 @@ def _attention(
+             (keys[:, None] < nk) & (ds[None, :] < dim),
+             0,
+         )
+-        accumulator = accumulator * correction[:, None] + tl.dot(prob, values, input_precision="tf32")
++        accumulator = accumulator * correction[:, None] + tl.dot(prob.to(values.dtype), values, input_precision="tf32")
+         maximum = new_max
+     result = accumulator / tl.where(denominator > 0, denominator, 1.0)[:, None]
+     tl.store(
+@@ -98,11 +98,11 @@ def cfm_attention(
+     mask: torch.Tensor | None = None,
+     kv_rows: torch.Tensor | None = None,
+ ) -> torch.Tensor:
+-    """Tiled attention with TF32 dots; optional ``kv_rows`` indexes a pooled K/V cache."""
++    """Tiled attention; optional ``kv_rows`` indexes a pooled K/V cache in place."""
+     b, heads, nq, dim = q.shape
+     nk = k.shape[2]
+-    if q.dtype != torch.float32 or k.dtype != torch.float32 or v.dtype != torch.float32:
+-        raise ValueError("CFM tiled attention requires float32 Q/K/V")
++    if q.dtype not in (torch.float32, torch.float16) or k.dtype != q.dtype or v.dtype != q.dtype:
++        raise ValueError("CFM tiled attention requires matching float32 or float16 Q/K/V")
+     num_stages = 2
+     out = torch.empty((b, nq, heads, dim), device=q.device, dtype=q.dtype)
+     _attention[(b, heads, triton.cdiv(nq, 32))](
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py b/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py
+new file mode 100644
+index 0000000000..00314dfc12
+--- /dev/null
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py
+@@ -0,0 +1,32 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Owned CPU tensor snapshots for the untyped turn-mode request envelope."""
++
++import torch
++
++from vllm_omni.distributed.omni_connectors.utils.serialization import OmniSerializer
++
++
++def pack_handoff_tensor(value: torch.Tensor) -> bytes:
++    """Keep legacy list-to-float32 values without creating Python scalar lists.
++
++    EngineCore's ``model_intermediate_buffer`` has Any-valued fields, so raw
++    tensors would lose their type on its msgpack wire. The existing Omni codec
++    packs an owned byte snapshot and restores the dtype/shape at the consumer.
++    """
++    tensor = value.detach().to(device="cpu", dtype=torch.float32).contiguous()
++    if tensor.numel() == 0:
++        # Empty transposed tensors may report contiguous with a nonunit last
++        # stride; the shared codec reinterprets that dimension as bytes.
++        tensor = torch.empty(tensor.shape, dtype=torch.float32)
++    return OmniSerializer.serialize(tensor)
++
++
++def unpack_handoff_tensor(value: object) -> object:
++    """Accept existing local tensors/lists as well as packed turn handoffs."""
++    if not isinstance(value, bytes):
++        return value
++    tensor = OmniSerializer.deserialize(value)
++    if not isinstance(tensor, torch.Tensor) or tensor.dtype != torch.float32 or tensor.device.type != "cpu":
++        raise ValueError("MiniCPM-o packed handoff must contain a CPU float32 tensor")
++    return tensor
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+index dfc23a5a0e..378766e9f9 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_code2wav.py
+@@ -1598,6 +1598,9 @@ class MiniCPMO45Code2Wav(nn.Module):
+                     "MiniCPM-o Code2Wav: campplus speaker embedding falling back to CPU onnxruntime "
+                     "(token2wav_device_spk=false)"
+                 )
++        if read_bool_flag(extra, "token2wav_spk_cuda_graph", False):
++            token2wav.enable_speaker_cuda_graph(self.vllm_config)
++            logger.info("MiniCPM-o Code2Wav: exact-shape Torch speaker CUDA graphs enabled")
+         self.backend = BatchedToken2Wav(
+             token2wav,
+             trt_stepper=trt_stepper,
+@@ -1609,6 +1612,7 @@ class MiniCPMO45Code2Wav(nn.Module):
+             setup_cache_size=self._setup_cache_size,
+             cfm_tf32=tf32_mode != "off",
+             encoder_graph_config=self._encoder_graph_config,
++            cfm_float16=read_bool_flag(extra, "cfm_float16", False),
+         )
+         # Captured by the first forward (the warmup run): under vLLM's weight load a graph held GiBs.
+         self._precapture_pending = read_bool_flag(extra, "cfm_graph_precapture", True)
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
+index 6f0bf23388..ba09bf4814 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
+@@ -41,6 +41,7 @@ from vllm_omni.model_executor.models.minicpmo_4_5 import (
+ from vllm_omni.model_executor.models.minicpmo_4_5.config_flags import (
+     parse_bool_flag as _bool_flag,
+ )
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.talker_codec_sample import (
+     HISTORY_WINDOW,
+     TalkerCodecDeviceState,
+@@ -1085,6 +1086,7 @@ class MiniCPMO45OmniTTSForConditionalGeneration(nn.Module, SupportsPP):
+ 
+         if is_prefill or first_call:
+             token_ids, hidden_states = get_tts_handoff(info_dict)
++            hidden_states = unpack_handoff_tensor(hidden_states)
+             # Cross-process stage transport serializes CPU tensors as lists.
+             # Normalize both local tensor handoffs and transported payloads
+             # before validating/building the Talker condition.
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+index d246afe225..68b9b3a736 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_token2wav.py
+@@ -130,6 +130,16 @@ class MiniCPMO45Token2wav:
+         """Run CAM++ on device, optionally without TensorRT on CUDA."""
+         self._core.enable_device_spk_embedding(use_trt=use_trt)
+ 
++    def enable_speaker_cuda_graph(self, vllm_config) -> None:
++        """Replay the current Torch speaker forward without changing its math."""
++        from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++        from vllm_omni.model_executor.models.minicpmo_4_5.speaker_cuda_graph import SpeakerCudaGraph
++
++        speaker = self._core._spk_model
++        if not isinstance(speaker, CampplusTorch) or speaker.device.type != "cuda":
++            raise ValueError("Speaker CUDA graphs require the CUDA Torch speaker model")
++        self._core._spk_model = SpeakerCudaGraph(speaker, vllm_config)
++
+     def __call__(self, generated_speech_tokens, prompt_wav) -> bytes:
+         """One-shot tokens → 24 kHz WAV bytes."""
+         return self._core.forward(
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+new file mode 100644
+index 0000000000..eed3b976eb
+--- /dev/null
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/speaker_cuda_graph.py
+@@ -0,0 +1,56 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Exact-shape replay of the existing Torch CAM++ speaker model."""
++
++from copy import copy
++
++import torch
++from vllm.config import VllmConfig
++from vllm.config.multimodal import MultiModalConfig
++
++from vllm_omni.model_executor.models.cosyvoice3.speaker_embedding_torch import CampplusTorch
++from vllm_omni.model_executor.models.minicpmo_4_5.encoder_cuda_graph import EncoderCudaGraph
++
++
++def _precision_policy() -> tuple[bool, ...]:
++    return (
++        torch.backends.cuda.matmul.allow_tf32,
++        torch.backends.cudnn.allow_tf32,
++        torch.backends.cudnn.enabled,
++        torch.backends.cudnn.benchmark,
++        torch.backends.cudnn.deterministic,
++        torch.are_deterministic_algorithms_enabled(),
++    )
++
++
++class SpeakerCudaGraph:
++    """Keep the shared eager model untouched and own this consumer's graphs.
++
++    Shapes are not padded. A changed precision policy runs eagerly instead of
++    replaying kernels captured with another policy. The existing encoder graph
++    manager bounds shape admission, isolates streams, and returns owned outputs.
++    """
++
++    def __init__(self, speaker: CampplusTorch, vllm_config: VllmConfig, *, max_graphs: int = 4):
++        self.speaker = speaker
++        self.device = speaker.device
++        # Code2Wav is a generation stage, so its model config need not carry
++        # multimodal limits. The local exact-shape adapter needs only defaults.
++        config = copy(vllm_config)
++        config.model_config = copy(config.model_config)
++        if config.model_config.multimodal_config is None:
++            config.model_config.multimodal_config = MultiModalConfig()
++        self.graph = EncoderCudaGraph(speaker.model.forward, config, max_graphs=max_graphs)
++        self._policy: tuple[bool, ...] | None = None
++
++    @torch.inference_mode()
++    def __call__(self, feat: torch.Tensor) -> torch.Tensor:
++        if self.device.type != "cuda" or torch.is_autocast_enabled("cuda"):
++            return self.speaker(feat)
++        policy = _precision_policy()
++        if self._policy is None:
++            self._policy = policy
++        elif policy != self._policy:
++            return self.speaker(feat)
++        feat = feat.to(self.device, non_blocking=True).unsqueeze(0).float()
++        return self.graph(feat)
+diff --git a/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py b/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
+index d707b8e53e..b8de386efa 100644
+--- a/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
++++ b/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
+@@ -20,6 +20,7 @@ from vllm_omni.model_executor.models.minicpmo_4_5 import (
+     MINICPMO45_DUPLEX_CODEC_TOKENS_PER_CHUNK,
+     MINICPMO45_DUPLEX_TURN_END_CODEC_TOKENS,
+ )
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor, unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.pipeline import MINICPMO45_REFERENCE_AUDIO_KEY
+ 
+ logger = logging.getLogger(__name__)
+@@ -461,7 +462,7 @@ def tts2code2wav_async_chunk(
+     if int(record["cache_epoch"]) == 0 and chunk_seq == 0:
+         codes_info = _request_intermediate_section(request, "codes")
+         meta_info = _request_intermediate_section(request, "meta")
+-        raw_ref_audio = codes_info.get("ref")
++        raw_ref_audio = unpack_handoff_tensor(codes_info.get("ref"))
+         raw_ref_audio_sr = meta_info.get("ref_audio_sr")
+         ref_audio_sr = _coerce_int(raw_ref_audio_sr)
+         if raw_ref_audio is not None:
+@@ -521,7 +522,7 @@ def tts2code2wav_full_payload(
+     meta_info = _request_intermediate_section(request, "meta")
+     duplex_info = _request_intermediate_section(request, "duplex")
+ 
+-    ref_audio = codes_info.get("ref")
++    ref_audio = unpack_handoff_tensor(codes_info.get("ref"))
+     finished = torch.tensor(True, dtype=torch.bool)
+     return OmniPayloadStruct(
+         codes=CodesStruct(
+@@ -1149,8 +1150,12 @@ def llm2tts(
+             )
+         if ref_audio is not None:
+             ref_waveform, ref_sr = ref_audio
+-            set_ref_audio(model_intermediate_buffer, _to_transport_list(ref_waveform), ref_sr)
+-        handoff_hidden = _to_transport_list(tts_hidden_slice) if tts_hidden_slice is not None else None
++            set_ref_audio(
++                model_intermediate_buffer,
++                _to_transport_list(ref_waveform) if is_native_duplex_handoff else pack_handoff_tensor(ref_waveform),
++                ref_sr,
++            )
++        handoff_hidden = _to_transport_list(tts_hidden_slice) if is_native_duplex_handoff else tts_hidden_slice
+         native_turn_end_handoff = False
+         turn_text_ends_sentence = False
+         if is_native_duplex_handoff:
+@@ -1158,7 +1163,11 @@ def llm2tts(
+             native_turn_end_handoff = turn_eos_id is not None and handoff_ids is not None and turn_eos_id in handoff_ids
+             if not handoff_ids:
+                 continue
+-        set_tts_handoff(model_intermediate_buffer, handoff_ids, handoff_hidden)
++        set_tts_handoff(
++            model_intermediate_buffer,
++            handoff_ids,
++            pack_handoff_tensor(handoff_hidden) if isinstance(handoff_hidden, torch.Tensor) else handoff_hidden,
++        )
+         if is_native_duplex_handoff:
+             # Always write the flag: the connector merges per-request meta across
+             # units, so a turn_end=True left by the previous turn's last unit would
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
index af2e2869b..f2929c369 100644
--- a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-manifest.json
@@ -39,8 +39,20 @@
     "tensor-handoff-composition": {
       "source_revision": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
       "patch": "peer-round2-tensor-handoff-composition.patch",
-      "status": "213 regression tests and precommit PASS; synthetic CPU transport values bitwise equal; service and speech qualification pending"
+      "status": "213 regression checks; packed25/50 service screens below peer C32; quality pending"
+    },
+    "tensor-handoff-main": {
+      "base_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+      "source_revision": "e27ebb06da28f82d4cc0c2c10ae8455d551c5c07",
+      "patch": "peer-round2-tensor-handoff-main.patch",
+      "status": "Standalone transport213 tests+precommit PASS; not service-tested"
+    },
+    "clean-main-composition": {
+      "base_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+      "source_revision": "e7a63354b61209a0f27e78c336f038df992e71ef",
+      "patch": "peer-round2-clean-main-composition.patch",
+      "status": "305 CPU regression checks,37 skips,precommit PASS; not service-tested; no quality claim"
     }
   },
-  "note": "Apply each patch independently to the base. Precision and speaker extensions are opt-in. The packed-turn-handoff composition changes ordinary-turn transport by default while preserving float32 values. Rejected profiles remain rejected; no patch is a qualified peer-beating release."
+  "note": "Apply each patch independently to its recorded base; entries with an explicit base_revision override the top-level base. Precision and speaker extensions are opt-in. Packed ordinary-turn transport preserves float32 values. Rejected profiles remain rejected; no patch is a qualified peer-beating release."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-main.patch b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-main.patch
new file mode 100644
index 000000000..890b7bf24
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/patch/peer-round2-tensor-handoff-main.patch
@@ -0,0 +1,494 @@
+diff --git a/docs/design/minicpm_o45_mrv2_performance.md b/docs/design/minicpm_o45_mrv2_performance.md
+index c7b1969841..f0e5ea8a5e 100644
+--- a/docs/design/minicpm_o45_mrv2_performance.md
++++ b/docs/design/minicpm_o45_mrv2_performance.md
+@@ -54,6 +54,21 @@ On CUDA, disabling TF32 with `token2wav_allow_tf32: false` or
+ Slot pooling and its `cfm_row_offset_merge` option remain opt-in. Fusion changes
+ floating-point rounding and does not promise identical waveforms.
+ 
++## Turn-mode conditioning transport
++
++Ordinary turn-mode `llm2tts` packs reference audio and thinker hidden states
++with the existing Omni tensor serializer. The request envelope's
++`model_intermediate_buffer` is untyped, so these values cross EngineCore as
++owned bytes and are restored to CPU float32 tensors by the Talker and codec
++bridge. This avoids scalar-list construction, worker list traversal and
++list-to-tensor conversion. Values match the previous list-to-float32 path;
++sampling and acoustic computation are unchanged.
++
++Legacy lists and local tensors remain accepted by consumers. Native duplex
++continues producing its existing lists. Each decode owns its storage, and the
++packed snapshot cannot be changed by later producer mutations. Transport
++microbenchmarks alone do not establish service throughput or speech quality.
++
+ ## Code2Wav batching across reference audio
+ 
+ With CUDA ragged Whole-Euler enabled, ready requests with different reference
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py b/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
+index d93755fec0..e10fecfc92 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_llm2tts.py
+@@ -22,6 +22,7 @@ from types import SimpleNamespace
+ import pytest
+ import torch
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_omni import (
+     MiniCPMO45OmniForConditionalGeneration,
+ )
+@@ -149,7 +150,10 @@ class TestBasicShape:
+         out = llm2tts([thinker_output], prompt=None)
+ 
+         assert out[0]["prompt_token_ids"] == [0, 0, 0]
+-        assert torch.equal(torch.tensor(out[0]["model_intermediate_buffer"]["hidden_states"]["tts"]), hidden[1:])
++        assert torch.equal(
++            torch.as_tensor(unpack_handoff_tensor(out[0]["model_intermediate_buffer"]["hidden_states"]["tts"])),
++            hidden[1:],
++        )
+ 
+     def test_returns_one_entry_per_input(self) -> None:
+         hidden = torch.zeros((3, _HIDDEN_DIM))
+@@ -210,7 +214,7 @@ class TestBasicShape:
+         buffer = result["model_intermediate_buffer"]
+         assert result["prompt_token_ids"] == [0, 0, 0, 0]
+         assert buffer["ids"]["tts"] == [20, 21]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[2:4])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[2:4])
+ 
+     def test_latent_in_multimodal_output_takes_precedence(self) -> None:
+         # When both ``multimodal_output["latent"]`` and ``hidden_states`` are
+@@ -234,7 +238,9 @@ class TestBasicShape:
+         )
+         buffer = result[0]["model_intermediate_buffer"]
+         # latent (ones) won over hidden_states (zeros)
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), latent[3:4].to(torch.float32))
++        assert torch.equal(
++            torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), latent[3:4].to(torch.float32)
++        )
+ 
+ 
+ class TestTtsRegionDetection:
+@@ -269,7 +275,7 @@ class TestTtsRegionDetection:
+         # 4.5 BOS at idx 2 -> slice starts at 3; end at idx 5 -> slice ends at 5.
+         buffer, hidden = self._run([10, 11], [151703, 30, 31, tts_end_id, 40])
+         assert buffer["ids"]["tts"] == [30, 31]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[3:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[3:5])
+ 
+     def test_bos_without_eos_runs_to_end(self) -> None:
+         # When BOS is found but EOS is missing (typical for an in-flight or
+@@ -278,12 +284,12 @@ class TestTtsRegionDetection:
+         # sequence: [10, 11, 151703, 30, 31]
+         buffer, hidden = self._run([10, 11], [151703, 30, 31])
+         assert buffer["ids"]["tts"] == [30, 31]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[3:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[3:5])
+ 
+     def test_plain_chat_without_tts_markers_uses_assistant_span(self) -> None:
+         buffer, hidden = self._run([10, 11], [20, 21, 22])
+         assert buffer["ids"]["tts"] == [20, 21, 22]
+-        assert torch.equal(torch.tensor(buffer["hidden_states"]["tts"]), hidden[2:5])
++        assert torch.equal(torch.as_tensor(unpack_handoff_tensor(buffer["hidden_states"]["tts"])), hidden[2:5])
+ 
+ 
+ class TestPromptAndMultiModal:
+@@ -325,7 +331,7 @@ class TestPromptAndMultiModal:
+         )
+ 
+         intermediate_buffer = stage_outputs[0]["model_intermediate_buffer"]
+-        assert intermediate_buffer["codes"]["ref"] == [0.25, -0.5]
++        assert torch.equal(unpack_handoff_tensor(intermediate_buffer["codes"]["ref"]), torch.tensor([0.25, -0.5]))
+         assert intermediate_buffer["meta"]["ref_audio_sr"] == 16000
+ 
+     def test_serving_reference_audio_is_added_to_stage_handoff(self) -> None:
+@@ -338,7 +344,7 @@ class TestPromptAndMultiModal:
+         )
+ 
+         intermediate_buffer = stage_outputs[0]["model_intermediate_buffer"]
+-        assert intermediate_buffer["codes"]["ref"] == [0.125, -0.25]
++        assert torch.equal(unpack_handoff_tensor(intermediate_buffer["codes"]["ref"]), torch.tensor([0.125, -0.25]))
+         assert intermediate_buffer["meta"]["ref_audio_sr"] == 24000
+ 
+     def test_missing_reference_audio_does_not_add_stage_handoff_fields(self) -> None:
+diff --git a/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py b/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
+index fc3b66cb36..eadfda43e7 100644
+--- a/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
++++ b/tests/model_executor/models/minicpmo_4_5/test_talker_batching.py
+@@ -13,6 +13,7 @@ import torch
+ import torch.nn as nn
+ from torch.overrides import TorchFunctionMode
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.minicpmo_4_5_omni import (
+     MiniCPMO45OmniForConditionalGeneration,
+ )
+@@ -1049,7 +1050,8 @@ def test_empty_speech_segment_finishes_without_sampling_codes() -> None:
+     assert decode_updates["codes"]["audio"].shape == (0,)
+ 
+ 
+-def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker) -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker, packed) -> None:
+     talker = _make_talker()
+     talker.emb_text = nn.Embedding(1, 2)
+     condition = torch.arange(18, dtype=torch.float32).reshape(9, 2)
+@@ -1063,7 +1065,7 @@ def test_chunked_prefill_tail_aligns_condition_with_prompt_length(mocker) -> Non
+         _omni_prompt_len=68,
+         request_id="req-chunked-prefill",
+         tts_token_ids=torch.tensor([1]),
+-        tts_hidden_states=torch.ones(1, 2),
++        tts_hidden_states=pack_handoff_tensor(torch.ones(1, 2)) if packed else torch.ones(1, 2),
+     )
+ 
+     assert torch.equal(embeds, condition)
+diff --git a/tests/model_executor/models/test_minicpmo_handoff.py b/tests/model_executor/models/test_minicpmo_handoff.py
+new file mode 100644
+index 0000000000..f861646fab
+--- /dev/null
++++ b/tests/model_executor/models/test_minicpmo_handoff.py
+@@ -0,0 +1,51 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++
++from typing import Any
++
++import pytest
++import torch
++from vllm.v1.serial_utils import MsgpackDecoder, MsgpackEncoder
++
++from vllm_omni.distributed.omni_connectors.utils.serialization import OmniSerializer
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor, unpack_handoff_tensor
++
++pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
++
++
++@pytest.mark.parametrize("dtype", [torch.float32, torch.float64, torch.bfloat16])
++@pytest.mark.parametrize("shape", [(), (0, 4), (3, 4), (144000,)])
++def test_packed_handoff_matches_legacy_values_across_untyped_wire(dtype, shape):
++    source = (
++        torch.linspace(-1.23456789, 1.987654321, int(torch.tensor(shape).prod().item()), dtype=torch.float64)
++        .reshape(shape)
++        .to(dtype)
++    )
++    if source.ndim == 2:
++        source = source.t()
++    expected = torch.tensor(source.tolist(), dtype=torch.float32).reshape(source.shape)
++    packed = pack_handoff_tensor(source)
++    envelope = {"model_intermediate_buffer": {"hidden_states": {"tts": packed}}}
++    # The real request field is dict[str, Any]: raw tensors cannot rely on a
++    # typed decoder hook here. Only standard bytes cross this boundary.
++    received = MsgpackDecoder(dict[str, Any]).decode(MsgpackEncoder().encode(envelope))
++    actual = unpack_handoff_tensor(received["model_intermediate_buffer"]["hidden_states"]["tts"])
++    assert isinstance(actual, torch.Tensor)
++    assert actual.shape == source.shape
++    assert torch.equal(actual, expected)
++    source.fill_(-7)
++    assert torch.equal(actual, expected)
++    other = unpack_handoff_tensor(packed)
++    actual.fill_(9)
++    assert torch.equal(other, expected)
++
++
++def test_legacy_handoff_values_remain_supported():
++    for value in (None, [1.0, 2.0], torch.ones(2)):
++        assert unpack_handoff_tensor(value) is value
++
++
++@pytest.mark.parametrize("payload", ["not a tensor", [1.0], torch.ones(2, dtype=torch.int64)])
++def test_invalid_packed_type_rejected(payload):
++    with pytest.raises(ValueError, match="CPU float32 tensor"):
++        unpack_handoff_tensor(OmniSerializer.serialize(payload))
+diff --git a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
+index 13036689ba..c3b8e69f90 100644
+--- a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
++++ b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_async_chunk.py
+@@ -8,6 +8,7 @@ import pytest
+ import torch
+ from vllm.v1.request import RequestStatus
+ 
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor
+ from vllm_omni.model_executor.stage_input_processors.minicpmo_4_5_omni import (
+     _extract_codec_delta,
+     tts2code2wav_async_chunk,
+@@ -237,11 +238,12 @@ def test_duplex_final_segment_preserves_every_code_and_closes_once(
+     assert not duplicate.meta.last_chunk
+ 
+ 
+-def test_first_chunk_forwards_reference_voice_and_duplex_identity() -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_first_chunk_forwards_reference_voice_and_duplex_identity(packed) -> None:
+     manager = _manager()
+     request = _request("req")
+     request.model_intermediate_buffer = {
+-        "codes": {"ref": [0.1, -0.1]},
++        "codes": {"ref": pack_handoff_tensor(torch.tensor([0.1, -0.1])) if packed else [0.1, -0.1]},
+         "meta": {"ref_audio_sr": 16000},
+     }
+     request.additional_information = {
+@@ -292,11 +294,12 @@ def test_first_chunk_falls_back_to_legacy_reference_fields() -> None:
+     assert payload.meta.ref_audio_sr == 16000
+ 
+ 
+-def test_full_payload_forwards_all_codes_and_request_metadata() -> None:
++@pytest.mark.parametrize("packed", [False, True])
++def test_full_payload_forwards_all_codes_and_request_metadata(packed) -> None:
+     manager = _manager()
+     request = _request("req")
+     request.model_intermediate_buffer = {
+-        "codes": {"ref": [0.1, -0.1]},
++        "codes": {"ref": pack_handoff_tensor(torch.tensor([0.1, -0.1])) if packed else [0.1, -0.1]},
+         "meta": {
+             "ref_audio_sr": 16000,
+             "native_duplex_segment_text": "hello",
+diff --git a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
+index edb5a3535f..c9c385cc70 100644
+--- a/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
++++ b/tests/model_executor/stage_input_processors/test_minicpmo_4_5_omni.py
+@@ -7,6 +7,7 @@ import pytest
+ import torch
+ 
+ from vllm_omni.engine.orchestrator import StreamingInputState
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.stage_input_processors.minicpmo_4_5_omni import (
+     _extract_first_audio_ref,
+     llm2tts,
+@@ -71,7 +72,7 @@ def test_plain_chat_handoff_owns_talker_prompt_contract() -> None:
+ 
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == output_ids
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[2:4])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[2:4])
+     assert converted["prompt_token_ids"] == [0, 0, 0, 0]
+     assert info["meta"]["replace_streaming_prompt"] is True
+     assert info["meta"]["next_stage_prompt_len"] == 4
+@@ -98,7 +99,7 @@ def test_llm2tts_carries_request_ref_audio() -> None:
+     )[0]
+ 
+     info = converted["model_intermediate_buffer"]
+-    assert info["codes"]["ref"] == ref_waveform.tolist()
++    assert torch.equal(unpack_handoff_tensor(info["codes"]["ref"]), ref_waveform)
+     assert info["meta"]["ref_audio_sr"] == 22050
+     assert info["ids"]["tts"] == [11, 12]
+ 
+@@ -191,7 +192,7 @@ def test_native_duplex_uses_forwarded_row_ledger_after_later_audio_prefill() ->
+ 
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_selects_latest_contiguous_forwarded_span() -> None:
+@@ -224,7 +225,7 @@ def test_native_duplex_selects_latest_contiguous_forwarded_span() -> None:
+     converted = llm2tts([source], prompt=[{}], _streaming_context=context)[0]
+ 
+     info = converted["model_intermediate_buffer"]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[5:7])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[5:7])
+ 
+ 
+ def test_native_duplex_rejects_missing_forwarded_terminal_token() -> None:
+@@ -303,7 +304,7 @@ def test_native_duplex_ledger_tolerates_async_lookahead_row_after_terminator() -
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_ledger_without_forwarded_terminator() -> None:
+@@ -317,7 +318,7 @@ def test_native_duplex_ledger_without_forwarded_terminator() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ def test_native_duplex_turn_eos_row_is_handed_to_talker() -> None:
+@@ -333,7 +334,7 @@ def test_native_duplex_turn_eos_row_is_handed_to_talker() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 9310]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+     assert info["meta"]["turn_end"] is True
+ 
+ 
+@@ -351,7 +352,7 @@ def test_native_duplex_ledger_anchors_on_unit_after_reinjected_listens() -> None
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[9:11])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[9:11])
+ 
+ 
+ @pytest.mark.parametrize("previous_terminator_forwarded", [False, True])
+@@ -372,7 +373,10 @@ def test_native_duplex_ledger_prefers_latest_repeat_of_the_unit(
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[current_start + 1 : current_start + 3])
++    assert torch.equal(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])),
++        latent[current_start + 1 : current_start + 3],
++    )
+ 
+ 
+ def test_native_duplex_ledger_rejects_non_contiguous_positions() -> None:
+@@ -397,7 +401,7 @@ def test_native_duplex_mid_turn_tts_bos_slices_after_boundary() -> None:
+     info = _native_handoff(source)
+ 
+     assert info["ids"]["tts"] == [21, 22]
+-    assert torch.equal(torch.tensor(info["hidden_states"]["tts"]), latent[3:5])
++    assert torch.equal(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3:5])
+ 
+ 
+ @pytest.mark.parametrize("opening", [9304, 9301])
+@@ -417,7 +421,9 @@ def test_native_duplex_mid_unit_tts_bos_keeps_earlier_text(opening, turn_end) ->
+ 
+     expected = [21, 22, 9301, 9310] if turn_end else [21, 22, 9301]
+     assert info["ids"]["tts"] == expected
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[3 : 3 + len(expected)])
++    torch.testing.assert_close(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[3 : 3 + len(expected)]
++    )
+     assert info.get("meta", {}).get("turn_end", False) is turn_end
+ 
+ 
+@@ -435,7 +441,9 @@ def test_native_duplex_folded_boundary_with_mid_unit_tts_bos(terminator) -> None
+ 
+     expected = [21, 22, 9301, *terminator[:-1]]
+     assert info["ids"]["tts"] == expected
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[2 : 2 + len(expected)])
++    torch.testing.assert_close(
++        torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[2 : 2 + len(expected)]
++    )
+ 
+ 
+ @pytest.mark.parametrize("folded_decisions", [0, 1, 2])
+@@ -471,7 +479,7 @@ def test_native_duplex_tts_bos_aligns_after_window_rebuild(folded_decisions, bos
+     converted = llm2tts([source], prompt=[{}], _streaming_context=SimpleNamespace(bridge_states={}))[0]
+     info = converted["model_intermediate_buffer"]
+     assert info["ids"]["tts"] == [21, 22]
+-    torch.testing.assert_close(torch.as_tensor(info["hidden_states"]["tts"]), latent[-3:-1])
++    torch.testing.assert_close(torch.as_tensor(unpack_handoff_tensor(info["hidden_states"]["tts"])), latent[-3:-1])
+ 
+ 
+ def test_native_duplex_continuation_appends_only_new_talker_condition() -> None:
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py b/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py
+new file mode 100644
+index 0000000000..00314dfc12
+--- /dev/null
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/handoff.py
+@@ -0,0 +1,32 @@
++# SPDX-License-Identifier: Apache-2.0
++# SPDX-FileCopyrightText: Copyright contributors to the vLLM-Omni project
++"""Owned CPU tensor snapshots for the untyped turn-mode request envelope."""
++
++import torch
++
++from vllm_omni.distributed.omni_connectors.utils.serialization import OmniSerializer
++
++
++def pack_handoff_tensor(value: torch.Tensor) -> bytes:
++    """Keep legacy list-to-float32 values without creating Python scalar lists.
++
++    EngineCore's ``model_intermediate_buffer`` has Any-valued fields, so raw
++    tensors would lose their type on its msgpack wire. The existing Omni codec
++    packs an owned byte snapshot and restores the dtype/shape at the consumer.
++    """
++    tensor = value.detach().to(device="cpu", dtype=torch.float32).contiguous()
++    if tensor.numel() == 0:
++        # Empty transposed tensors may report contiguous with a nonunit last
++        # stride; the shared codec reinterprets that dimension as bytes.
++        tensor = torch.empty(tensor.shape, dtype=torch.float32)
++    return OmniSerializer.serialize(tensor)
++
++
++def unpack_handoff_tensor(value: object) -> object:
++    """Accept existing local tensors/lists as well as packed turn handoffs."""
++    if not isinstance(value, bytes):
++        return value
++    tensor = OmniSerializer.deserialize(value)
++    if not isinstance(tensor, torch.Tensor) or tensor.dtype != torch.float32 or tensor.device.type != "cpu":
++        raise ValueError("MiniCPM-o packed handoff must contain a CPU float32 tensor")
++    return tensor
+diff --git a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
+index 6f0bf23388..ba09bf4814 100644
+--- a/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
++++ b/vllm_omni/model_executor/models/minicpmo_4_5/minicpmo_4_5_omni_tts.py
+@@ -41,6 +41,7 @@ from vllm_omni.model_executor.models.minicpmo_4_5 import (
+ from vllm_omni.model_executor.models.minicpmo_4_5.config_flags import (
+     parse_bool_flag as _bool_flag,
+ )
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.talker_codec_sample import (
+     HISTORY_WINDOW,
+     TalkerCodecDeviceState,
+@@ -1085,6 +1086,7 @@ class MiniCPMO45OmniTTSForConditionalGeneration(nn.Module, SupportsPP):
+ 
+         if is_prefill or first_call:
+             token_ids, hidden_states = get_tts_handoff(info_dict)
++            hidden_states = unpack_handoff_tensor(hidden_states)
+             # Cross-process stage transport serializes CPU tensors as lists.
+             # Normalize both local tensor handoffs and transported payloads
+             # before validating/building the Talker condition.
+diff --git a/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py b/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
+index d707b8e53e..b8de386efa 100644
+--- a/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
++++ b/vllm_omni/model_executor/stage_input_processors/minicpmo_4_5_omni.py
+@@ -20,6 +20,7 @@ from vllm_omni.model_executor.models.minicpmo_4_5 import (
+     MINICPMO45_DUPLEX_CODEC_TOKENS_PER_CHUNK,
+     MINICPMO45_DUPLEX_TURN_END_CODEC_TOKENS,
+ )
++from vllm_omni.model_executor.models.minicpmo_4_5.handoff import pack_handoff_tensor, unpack_handoff_tensor
+ from vllm_omni.model_executor.models.minicpmo_4_5.pipeline import MINICPMO45_REFERENCE_AUDIO_KEY
+ 
+ logger = logging.getLogger(__name__)
+@@ -461,7 +462,7 @@ def tts2code2wav_async_chunk(
+     if int(record["cache_epoch"]) == 0 and chunk_seq == 0:
+         codes_info = _request_intermediate_section(request, "codes")
+         meta_info = _request_intermediate_section(request, "meta")
+-        raw_ref_audio = codes_info.get("ref")
++        raw_ref_audio = unpack_handoff_tensor(codes_info.get("ref"))
+         raw_ref_audio_sr = meta_info.get("ref_audio_sr")
+         ref_audio_sr = _coerce_int(raw_ref_audio_sr)
+         if raw_ref_audio is not None:
+@@ -521,7 +522,7 @@ def tts2code2wav_full_payload(
+     meta_info = _request_intermediate_section(request, "meta")
+     duplex_info = _request_intermediate_section(request, "duplex")
+ 
+-    ref_audio = codes_info.get("ref")
++    ref_audio = unpack_handoff_tensor(codes_info.get("ref"))
+     finished = torch.tensor(True, dtype=torch.bool)
+     return OmniPayloadStruct(
+         codes=CodesStruct(
+@@ -1149,8 +1150,12 @@ def llm2tts(
+             )
+         if ref_audio is not None:
+             ref_waveform, ref_sr = ref_audio
+-            set_ref_audio(model_intermediate_buffer, _to_transport_list(ref_waveform), ref_sr)
+-        handoff_hidden = _to_transport_list(tts_hidden_slice) if tts_hidden_slice is not None else None
++            set_ref_audio(
++                model_intermediate_buffer,
++                _to_transport_list(ref_waveform) if is_native_duplex_handoff else pack_handoff_tensor(ref_waveform),
++                ref_sr,
++            )
++        handoff_hidden = _to_transport_list(tts_hidden_slice) if is_native_duplex_handoff else tts_hidden_slice
+         native_turn_end_handoff = False
+         turn_text_ends_sentence = False
+         if is_native_duplex_handoff:
+@@ -1158,7 +1163,11 @@ def llm2tts(
+             native_turn_end_handoff = turn_eos_id is not None and handoff_ids is not None and turn_eos_id in handoff_ids
+             if not handoff_ids:
+                 continue
+-        set_tts_handoff(model_intermediate_buffer, handoff_ids, handoff_hidden)
++        set_tts_handoff(
++            model_intermediate_buffer,
++            handoff_ids,
++            pack_handoff_tensor(handoff_hidden) if isinstance(handoff_hidden, torch.Tensor) else handoff_hidden,
++        )
+         if is_native_duplex_handoff:
+             # Always write the flag: the connector merges per-request meta across
+             # units, so a turn_end=True left by the previous turn's last unit would
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-clean-main-composition.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-clean-main-composition.json
new file mode 100644
index 000000000..61bdf3d05
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-clean-main-composition.json
@@ -0,0 +1,25 @@
+{
+  "at_utc": "2026-10-21T10:55:55.664100+00:00",
+  "base_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "candidate_revision": "e7a63354b61209a0f27e78c336f038df992e71ef",
+  "source_branch": "perf-minicpm-throughput-main",
+  "composition": [
+    "Packed ordinary-turn conditioning",
+    "CUDA FP16 fused resident attention eligibility and runtime dispatch",
+    "Selective CFM FP16, default off",
+    "Exact Torch speaker graph, default off"
+  ],
+  "excluded": "Earlier CPU-reference TensorRT speaker experiment and deployment are not included.",
+  "conflict_resolution": "Speaker backend flag tests retained main TRT API and added the original14 graph-related lines only.",
+  "validation": {
+    "cpu_passed": 305,
+    "skipped": 37,
+    "skip_note": "CUDA hidden for CPU regression; GPU-specific checks require a reserved device. The earlier equivalent kernel checks do not substitute for this revision service validation.",
+    "precommit": "PASS, including final documentation commit hooks"
+  },
+  "active_screen_source": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
+  "service_tested": false,
+  "goal_achieved": false,
+  "verdict": "INCONCLUSIVE",
+  "patch_sha256": "d3dbe64114eaca08a764193250ed07f510a46a126b45d9b697370a6546474481"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
index 5ea2ba764..f8a2a2f00 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-artifact.json
@@ -1,7 +1,7 @@
 {
   "scope": "Completed round-two tuning screens; reused data, no final acceptance",
   "path": "peer-round2-screen-requests-quality.json.gz",
-  "sha256": "5449102bd24f08177d360db19b2593162012d2d35a0b9842b98150b91a20247b",
+  "sha256": "5dcae2cbd5399e6d1ffc31efebcf9f34c3dae100277997980f7eb1404bfb618b",
   "profiles": [
     "screen-torch-mps",
     "screen-capacity32-mps",
@@ -26,7 +26,9 @@
     "screen-cfm-speaker-window50",
     "screen-fp32-speaker-window100",
     "screen-cfm-speaker-window100",
-    "screen-cfm-speaker-window50-covered"
+    "screen-cfm-speaker-window50-covered",
+    "screen-tensor-handoff25",
+    "screen-tensor-handoff50"
   ],
   "privacy": "Audio and ASR hypothesis text are excluded. Audio hashes and error counts remain."
 }
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz b/evidence/minicpmo45-l20x-20261021/results/peer-round2-screen-requests-quality.json.gz
index c3ac63b0b2ad58eb76c33c297fdcd8548dafaf31..6e5025fbece5c4852f75f461aa7c73a90057cb4c 100644
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diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
index 96c9b3b6b..887a5dd41 100644
--- a/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-status.json
@@ -37,10 +37,14 @@
     "Window100 selectiveCFM C16/C32 1244.9/1463.3; quality means exceed margins",
     "Window50 exact HiFT coverage C16/C32 1367.4/1663.7; quality means exceed margins",
     "CPU diagnostic recovered from100Hz sampling lag; separate CPU counters and2Hz qualitative stacks",
-    "Packed transport synthetic CPU median34.53ms to0.498ms; bitwise values preserved;213 regression tests passed with1existing skip"
+    "Packed transport synthetic CPU median34.53ms to0.498ms; bitwise values preserved;213 regression tests passed with1existing skip",
+    "Packed25 C16/C32 1331.4/1573.5 and packed50 1521.4/1839.8, zero request failures; quality pending",
+    "Standalone main-based packed transport213 tests and precommit PASS; not service-tested"
   ],
   "active": [
-    "Packed conditioning transport25/50-frame service screens queued, source60d71d16e0; quality watchers pending"
+    "Packed25/50 speech quality scoring queued",
+    "Independent fixed-window Talker4/vocoder4 and Talker2/vocoder8 screens",
+    "Clean main composition integration and validation"
   ],
   "reserved_holdout_used": false,
   "quality_margins": {
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-main.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-main.json
new file mode 100644
index 000000000..8902a48e2
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff-main.json
@@ -0,0 +1,15 @@
+{
+  "at_utc": "2026-10-21T10:42:59.512910+00:00",
+  "base_revision": "15bce345863c6e2db882534876b8977f5b1ae1e3",
+  "candidate_revision": "e27ebb06da28f82d4cc0c2c10ae8455d551c5c07",
+  "scope": "Standalone packed ordinary-turn conditioning change, without earlier CPU-reference TRT, CFM precision or speaker-graph experiments. This branch is not the source of the active60d service screens.",
+  "validation": {
+    "regression_tests_passed": 213,
+    "pre_existing_skipped": 1,
+    "precommit": "PASS"
+  },
+  "service_tested": false,
+  "goal_achieved": false,
+  "verdict": "INCONCLUSIVE",
+  "patch": "patch/peer-round2-tensor-handoff-main.patch"
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff25-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff25-screen.json
new file mode 100644
index 000000000..da81c0ca6
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff25-screen.json
@@ -0,0 +1,167 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP16 CFM estimator/noise/cache; FP32 encoder, speaker and HiFT",
+    "stage0_kv_bytes": 8589934592,
+    "speaker_graph": true,
+    "packed_conditioning": true,
+    "codec_chunk_frames": 25
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 33.03117688931525,
+      "throughput_frames_s": 208.80273273674985,
+      "ttfa_p50_s": 0.25941535038873553,
+      "ttfa_p95_s": 0.2890582353807985,
+      "rtf_mean": 0.1207448408299226,
+      "rtf_duration_weighted": 0.1195534104536703,
+      "req_s": 1.9375634181748573,
+      "audio_s_per_s": 8.352109309469993,
+      "e2e_p50_s": 0.5230209678411484,
+      "e2e_p95_s": 0.7005303963087497,
+      "total_audio_s": 275.88,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.06886181980371475,
+      "inter_chunk_gap_p95_s": 0.08903454253450035,
+      "inter_chunk_gap_max_s": 0.10024501755833626
+    },
+    "16": {
+      "label": "run1",
+      "concurrency": 16,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 5.25457358174026,
+      "throughput_frames_s": 1331.4115581730985,
+      "ttfa_p50_s": 0.6192096774466336,
+      "ttfa_p95_s": 0.8411769842263311,
+      "rtf_mean": 0.2905467516471387,
+      "rtf_duration_weighted": 0.28829061820729823,
+      "req_s": 12.179865597924287,
+      "audio_s_per_s": 53.256462326923945,
+      "e2e_p50_s": 1.1922125169076025,
+      "e2e_p95_s": 2.1079465478658674,
+      "total_audio_s": 279.84,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.1236190814524889,
+      "inter_chunk_gap_p95_s": 0.3762838437221944,
+      "inter_chunk_gap_max_s": 0.650517257861793
+    },
+    "32": {
+      "label": "run1",
+      "concurrency": 32,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 4.447526674717665,
+      "throughput_frames_s": 1573.4588034695132,
+      "ttfa_p50_s": 0.9553101137280464,
+      "ttfa_p95_s": 1.3936211891938,
+      "rtf_mean": 0.47730882418754883,
+      "rtf_duration_weighted": 0.4761194213555402,
+      "req_s": 14.390020494719757,
+      "audio_s_per_s": 62.93835213878054,
+      "e2e_p50_s": 1.9966130163520575,
+      "e2e_p95_s": 3.3299118375405667,
+      "total_audio_s": 279.92,
+      "first_chunk_mean_s": 0.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.25603202544152737,
+      "inter_chunk_gap_p95_s": 0.6456071925815194,
+      "inter_chunk_gap_max_s": 0.7805216424167156
+    }
+  },
+  "quality": {},
+  "quality_status": "Scoring pending",
+  "latency_note": "The same codec window applies to first and subsequent chunks; report TTFA and first_chunk_mean_s."
+}
diff --git a/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff50-screen.json b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff50-screen.json
new file mode 100644
index 000000000..4d5d05c7e
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/results/peer-round2-tensor-handoff50-screen.json
@@ -0,0 +1,167 @@
+{
+  "scope": "64 reused tuning prompts, discard+one; exploratory, final paired repeated comparison pending.",
+  "source_revision": "60d71d16e0d77734239935ffc6b991c810ea1aa7",
+  "actual_runtime": {
+    "cuda_mps": true,
+    "replicas": [
+      1,
+      2,
+      4
+    ],
+    "runners": [
+      "v1",
+      "v1",
+      "v1"
+    ],
+    "capacities": [
+      16,
+      16,
+      16
+    ],
+    "precision": "FP16 CFM estimator/noise/cache; FP32 encoder, speaker and HiFT",
+    "stage0_kv_bytes": 8589934592,
+    "speaker_graph": true,
+    "packed_conditioning": true,
+    "codec_chunk_frames": 50
+  },
+  "metadata_note": "Raw summary mps_policy off and id_set eval are helper defaults, not actual execution; frozen plans describe MPS enabled and tuning cohort.",
+  "verdict": "INCONCLUSIVE",
+  "goal_achieved": false,
+  "performance": {
+    "1": {
+      "label": "run1",
+      "concurrency": 1,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 33.8695760210976,
+      "throughput_frames_s": 203.63408138630993,
+      "ttfa_p50_s": 0.35349731193855405,
+      "ttfa_p95_s": 0.3897334730718285,
+      "rtf_mean": 0.12359962050779075,
+      "rtf_duration_weighted": 0.12249551410722667,
+      "req_s": 1.88960145117063,
+      "audio_s_per_s": 8.145363255452397,
+      "e2e_p50_s": 0.5375046879053116,
+      "e2e_p95_s": 0.7174716605339196,
+      "total_audio_s": 275.88,
+      "first_chunk_mean_s": 1.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.11946131009608507,
+      "inter_chunk_gap_p95_s": 0.155788083281368,
+      "inter_chunk_gap_max_s": 0.19077861867845058
+    },
+    "16": {
+      "label": "run1",
+      "concurrency": 16,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 4.635758655145764,
+      "throughput_frames_s": 1521.4338201517587,
+      "ttfa_p50_s": 0.7250376767478883,
+      "ttfa_p95_s": 0.9982919227331875,
+      "rtf_mean": 0.25257950763907516,
+      "rtf_duration_weighted": 0.245701341160771,
+      "req_s": 13.805723024204248,
+      "audio_s_per_s": 60.85735280607035,
+      "e2e_p50_s": 1.0925466301850975,
+      "e2e_p95_s": 1.387674218043685,
+      "total_audio_s": 282.12,
+      "first_chunk_mean_s": 1.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.174854117911309,
+      "inter_chunk_gap_p95_s": 0.4504502961877733,
+      "inter_chunk_gap_max_s": 0.625399935990572
+    },
+    "32": {
+      "label": "run1",
+      "concurrency": 32,
+      "measured": true,
+      "gpu": "",
+      "engine": "",
+      "config": "",
+      "candidate_id": "",
+      "config_digest": "",
+      "cell_digest": "",
+      "experiment_base_digest": "",
+      "mps_policy": "off",
+      "id_set": "eval",
+      "ids_sha256": "",
+      "expected_ids_sha256": "",
+      "seed_index": 0,
+      "timeout_s": 0.0,
+      "strict": false,
+      "cache_policy": "none",
+      "cache_evidence": {},
+      "runtime_evidence": {},
+      "server_startup_s": null,
+      "n_requests": 64,
+      "n_failed": 0,
+      "valid": true,
+      "invalid_reasons": {},
+      "makespan_s": 3.8347217682749033,
+      "throughput_frames_s": 1839.7684177159424,
+      "ttfa_p50_s": 1.096826781053096,
+      "ttfa_p95_s": 1.6870311159174889,
+      "rtf_mean": 0.39257809011208683,
+      "rtf_duration_weighted": 0.38743803484205613,
+      "req_s": 16.68960719118644,
+      "audio_s_per_s": 73.59073670863769,
+      "e2e_p50_s": 1.6017752117477357,
+      "e2e_p95_s": 2.4817320271395147,
+      "total_audio_s": 282.2,
+      "first_chunk_mean_s": 1.84,
+      "stall_mean_s": 0.0,
+      "stall_max_s": 0.0,
+      "inter_chunk_gap_p50_s": 0.35544896218925714,
+      "inter_chunk_gap_p95_s": 0.7599194046109898,
+      "inter_chunk_gap_max_s": 0.8624904761090875
+    }
+  },
+  "quality": {},
+  "quality_status": "Scoring pending",
+  "latency_note": "The same codec window applies to first and subsequent chunks; report TTFA and first_chunk_mean_s."
+}

From f62aebd4d0044251b190e5d901b2f6fafe3fa187 Mon Sep 17 00:00:00 2001
From: Cursor Agent <cursoragent@cursor.com>
Date: Wed, 4 Nov 2026 08:56:32 +0000
Subject: [PATCH 37/40] Reject stale MiniCPM scoring output before replacing
 audio provenance

Keep historical validator/score_outputs.py frozen. Successor
score_outputs_v2.py checks prompt IDs, WAV hashes, durations and scorer-file
provenance before writing provenance or skipping a completed task, and a
changed-WAV regression shows a reused output is left untouched.

Review: https://github.com/InferMatrixLab/InferRSI/pull/51#discussion_r4357846076
Signed-off-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: amy-why-3459 <amy-why-3459@users.noreply.github.com>
---
 evidence/minicpmo45-l20x-20261021/README.md   |   2 +
 .../validator/score_outputs_v2.py             | 271 ++++++++++++++++++
 tests/test_minicpm_score_resume.py            | 110 +++++++
 3 files changed, 383 insertions(+)
 create mode 100644 evidence/minicpmo45-l20x-20261021/validator/score_outputs_v2.py
 create mode 100644 tests/test_minicpm_score_resume.py

diff --git a/evidence/minicpmo45-l20x-20261021/README.md b/evidence/minicpmo45-l20x-20261021/README.md
index 4793ad6a4..d2b6f7802 100644
--- a/evidence/minicpmo45-l20x-20261021/README.md
+++ b/evidence/minicpmo45-l20x-20261021/README.md
@@ -135,6 +135,8 @@ PYTHONPATH="$SGLANG_OMNI:$PEER" python "$EVIDENCE/validator/score_outputs.py" \
 
 The ASR service is a separate Qwen3-ASR-1.7B SGLang-Omni server. The scorer validates nonempty finite audio and retains per-request scores. Public quality artifacts omit generated transcripts but retain WAV hashes and error counts.
 
+The recorded runs used historical `validator/score_outputs.py`, which is unchanged. Successor `validator/score_outputs_v2.py` checks prompt IDs, WAV hashes, durations and scorer-file provenance before it writes audio provenance or skips a completed task, and it leaves the output untouched when those inputs differ. Recorded scores were not recomputed.
+
 Speaker numerical validation uses the checked-in `validator/bench_speaker.py`. It covers 32 tuning references plus short partial-window inputs, with 10 warmups and 30 synchronized latency samples. `speaker_trt_ieee.py` is the preserved historical precision-only diagnostic helper; the final CPU-reference path imports the candidate implementation directly.
 
 ```bash
diff --git a/evidence/minicpmo45-l20x-20261021/validator/score_outputs_v2.py b/evidence/minicpmo45-l20x-20261021/validator/score_outputs_v2.py
new file mode 100644
index 000000000..5993e292b
--- /dev/null
+++ b/evidence/minicpmo45-l20x-20261021/validator/score_outputs_v2.py
@@ -0,0 +1,271 @@
+"""Score saved WAVs, refusing to resume onto different audio.
+
+``score_outputs.py`` is the historical frozen scorer and is unchanged. This
+successor checks prompt IDs, WAV hashes, durations and scorer-file provenance
+before it writes audio provenance or skips a completed task. A reused output
+whose inputs differ is rejected and left untouched.
+"""
+
+from __future__ import annotations
+
+import argparse
+import copy
+import hashlib
+import json
+from pathlib import Path
+
+WAV_FIELDS = ("wav_sha256", "duration_s")
+
+
+class StaleScoringOutput(ValueError):
+    """Saved scores do not belong to the current audio or scorers."""
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as source:
+        for block in iter(lambda: source.read(1024 * 1024), b""):
+            digest.update(block)
+    return digest.hexdigest()
+
+
+def _canonical(value):
+    return json.loads(json.dumps(value, allow_nan=False))
+
+
+def scorer_provenance(scorers: Path) -> dict:
+    """Content hashes of every file currently under the scorer directory."""
+    root = Path(scorers)
+    files = {
+        path.relative_to(root).as_posix(): _sha256(path)
+        for path in sorted(item for item in root.rglob("*") if item.is_file())
+    }
+    if not files:
+        raise ValueError("scorer directory contains no files")
+    return {"successor": "score_outputs_v2", "files": files}
+
+
+def bind_resume(existing, ids, wav_by_id, provenance):
+    """Return a document that is safe to continue, without mutating inputs.
+
+    ``existing`` is ``None`` for a new output. A stored document is returned
+    unchanged when its IDs, WAV provenance and scorer provenance match.
+    """
+    if not isinstance(ids, list) or not ids or len(ids) != len(set(ids)):
+        raise ValueError("request ids must be unique and nonempty")
+    if set(wav_by_id) != set(ids):
+        raise ValueError("wav provenance must cover exactly the request ids")
+    fresh_wavs = {}
+    for request_id in ids:
+        record = wav_by_id[request_id]
+        if not isinstance(record, dict) or set(record) != set(WAV_FIELDS):
+            raise ValueError("wav provenance must contain only hash and duration")
+        digest = record["wav_sha256"]
+        duration = record["duration_s"]
+        hexadecimal = set("0123456789abcdef")
+        digest_ok = (
+            isinstance(digest, str)
+            and len(digest) == 64
+            and all(char in hexadecimal for char in digest)
+        )
+        if not digest_ok:
+            raise ValueError("wav hash must be a lowercase SHA-256 digest")
+        if isinstance(duration, bool) or not isinstance(duration, (int, float)) or not duration > 0:
+            raise ValueError("duration must be a positive number")
+        fresh_wavs[request_id] = {"wav_sha256": digest, "duration_s": duration}
+    if not isinstance(provenance, dict) or set(provenance) != {"successor", "files"}:
+        raise ValueError("scorer provenance must identify score_outputs_v2 files")
+    if provenance["successor"] != "score_outputs_v2" or not isinstance(provenance["files"], dict):
+        raise ValueError("scorer provenance must identify score_outputs_v2 files")
+    if not provenance["files"]:
+        raise ValueError("scorer provenance must contain at least one file")
+    canonical_provenance = _canonical(provenance)
+    canonical_wavs = _canonical(fresh_wavs)
+    if existing is None:
+        return {
+            "rows": {request_id: dict(canonical_wavs[request_id]) for request_id in ids},
+            "tasks": [],
+            "scorer_provenance": canonical_provenance,
+        }
+    if not isinstance(existing, dict):
+        raise StaleScoringOutput("existing scoring output is not an object")
+    rows = existing.get("rows")
+    tasks = existing.get("tasks")
+    recorded = existing.get("scorer_provenance")
+    if not isinstance(rows, dict) or not isinstance(tasks, list) or not isinstance(recorded, dict):
+        raise StaleScoringOutput(
+            "existing scoring output is missing rows, tasks, or scorer provenance"
+        )
+    if set(rows) != set(ids):
+        raise StaleScoringOutput("prompt IDs differ from the existing scoring output")
+    if _canonical(recorded) != canonical_provenance:
+        raise StaleScoringOutput("scorer provenance differs from the existing scoring output")
+    for request_id in ids:
+        row = rows[request_id]
+        if not isinstance(row, dict):
+            raise StaleScoringOutput(f"row {request_id} is not an object")
+        stored = {field: row.get(field) for field in WAV_FIELDS}
+        try:
+            stored_canonical = _canonical(stored)
+        except (TypeError, ValueError) as exc:
+            raise StaleScoringOutput(f"WAV provenance for {request_id} is not comparable") from exc
+        if stored_canonical != canonical_wavs[request_id]:
+            raise StaleScoringOutput(
+                f"WAV provenance differs for {request_id}; refusing to replace it with new audio"
+            )
+    return copy.deepcopy(existing)
+
+
+def resume_output(path: Path, ids, wav_by_id, provenance):
+    """Load ``path`` when it exists and resume, or start a new document.
+
+    Raises ``StaleScoringOutput`` before any write when the saved output does
+    not belong to these inputs.
+    """
+    existing = json.loads(path.read_text(encoding="utf-8")) if path.exists() else None
+    return bind_resume(existing, ids, wav_by_id, provenance)
+
+
+def _fingerprint_wav(path: Path) -> dict:
+    import numpy as np
+    import soundfile as sf
+
+    audio, sample_rate = sf.read(path)
+    if len(audio) == 0 or not np.isfinite(audio).all() or sample_rate <= 0:
+        raise ValueError(f"invalid audio: {path}")
+    return {
+        "wav_sha256": _sha256(path),
+        "duration_s": len(audio) / sample_rate,
+    }
+
+
+def _load_run(run: Path):
+    from bench.workload import load_seed_tts_rows
+
+    rows = {row.row_id: row for row in load_seed_tts_rows()}
+    metrics = [json.loads(line) for line in (run / "requests.jsonl").read_text().splitlines()]
+    if not metrics or not all(item["ok"] for item in metrics):
+        raise ValueError("run has no successful requests")
+    ids = sorted(item["request_id"] for item in metrics)
+    if len(ids) != len(set(ids)):
+        raise ValueError("duplicate request ids")
+    wavs = {request_id: _fingerprint_wav(run / "wav" / f"{request_id}.wav") for request_id in ids}
+    return rows, ids, wavs
+
+
+def _save(path: Path, document) -> None:
+    path.write_text(json.dumps(document, indent=2, allow_nan=False) + "\n", encoding="utf-8")
+
+
+def _score_missing(args, document, rows, ids, wavs) -> None:
+    wav_paths = [str(Path(args.run) / "wav" / f"{request_id}.wav") for request_id in ids]
+    if "wer" in args.tasks and "wer" not in document["tasks"]:
+        import concurrent.futures
+
+        from benchmarks.metrics.wer import SampleOutput
+        from benchmarks.tasks.asr import apply_wer, load_qwen3_asr, transcribe
+
+        asr = load_qwen3_asr(args.asr_port)
+
+        def score(pair):
+            request_id, wav_path = pair
+            hypothesis = transcribe(asr, wav_path, "en", args.device)
+            result = apply_wer(
+                SampleOutput(sample_id=request_id, target_text=rows[request_id].target_text),
+                hypothesis,
+                "en",
+            )
+            if not result.is_success:
+                raise RuntimeError(result.error)
+            values = {
+                key: getattr(result, key)
+                for key in ("wer", "substitutions", "deletions", "insertions", "hits")
+            }
+            values["hyp_text"] = hypothesis
+            return request_id, values
+
+        with concurrent.futures.ThreadPoolExecutor(max_workers=4) as pool:
+            for request_id, result in pool.map(score, zip(ids, wav_paths)):
+                document["rows"][request_id]["wer"] = result
+        document["tasks"].append("wer")
+        _save(Path(args.out), document)
+    if "sim" in args.tasks and "sim" not in document["tasks"]:
+        from benchmarks.metrics.speaker_similarity import WavLMSpeakerSimilarity
+
+        weights = Path(args.scorers) / "sim"
+        scorer = WavLMSpeakerSimilarity(
+            finetune_checkpoint=weights / "wavlm_large_finetune.pth",
+            wavlm_base=weights / "wavlm_large.pt",
+            device=args.device,
+        )
+        for start in range(0, len(ids), 4):
+            batch = ids[start:start + 4]
+            scores = scorer.score_batch(
+                [rows[request_id].ref_wav_path for request_id in batch],
+                wav_paths[start:start + 4],
+            )
+            for request_id, score in zip(batch, scores):
+                document["rows"][request_id]["sim"] = float(score)
+        document["tasks"].append("sim")
+        _save(Path(args.out), document)
+        del scorer
+    if "utmos" in args.tasks and "utmos" not in document["tasks"]:
+        from benchmarks.metrics.utmos import UTMOSScorer
+
+        scorer = UTMOSScorer(device=args.device, cache_dir=Path(args.scorers) / "utmos")
+        for start in range(0, len(ids), 8):
+            batch = ids[start:start + 8]
+            scores = scorer.score_batch(wav_paths[start:start + 8])
+            for request_id, score in zip(batch, scores):
+                document["rows"][request_id]["utmos"] = float(score)
+        document["tasks"].append("utmos")
+        _save(Path(args.out), document)
+
+
+def _summary(document) -> dict:
+    import numpy as np
+
+    summary = {"n": len(document["rows"])}
+    for key in ("sim", "utmos"):
+        if key in document["tasks"]:
+            summary[key] = float(np.mean([row[key] for row in document["rows"].values()]))
+    if "wer" in document["tasks"]:
+        counts = {
+            key: sum(row["wer"][key] for row in document["rows"].values())
+            for key in ("substitutions", "deletions", "insertions", "hits")
+        }
+        errors = ("substitutions", "deletions", "insertions")
+        denominator = ("substitutions", "deletions", "hits")
+        error_count = sum(counts[key] for key in errors)
+        summary["wer"] = error_count / sum(counts[key] for key in denominator)
+        summary["wer_counts"] = counts
+        means = [row["wer"]["wer"] for row in document["rows"].values()]
+        summary["wer_mean"] = float(np.mean(means))
+    return summary
+
+
+def main(argv=None) -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--run", required=True)
+    parser.add_argument("--out", required=True)
+    parser.add_argument("--scorers", required=True)
+    parser.add_argument("--asr-port", type=int, default=29181)
+    parser.add_argument("--device", default="cuda:0")
+    parser.add_argument("--tasks", nargs="+", default=["wer", "sim", "utmos"])
+    args = parser.parse_args(argv)
+    rows, ids, wavs = _load_run(Path(args.run))
+    provenance = scorer_provenance(Path(args.scorers))
+    out = Path(args.out)
+    document = resume_output(out, ids, wavs, provenance)
+    out.parent.mkdir(parents=True, exist_ok=True)
+    if not out.exists():
+        _save(out, document)
+    _score_missing(args, document, rows, ids, wavs)
+    document["summary"] = _summary(document)
+    _save(out, document)
+    print(json.dumps(document["summary"]), flush=True)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/tests/test_minicpm_score_resume.py b/tests/test_minicpm_score_resume.py
new file mode 100644
index 000000000..e85a93d6a
--- /dev/null
+++ b/tests/test_minicpm_score_resume.py
@@ -0,0 +1,110 @@
+"""Changed-WAV resume must not bind saved scores to new audio hashes."""
+
+import copy
+import importlib.util
+import json
+from pathlib import Path
+
+import pytest
+
+SUCCESSOR = (
+    Path(__file__).resolve().parents[1]
+    / "evidence/minicpmo45-l20x-20261021/validator/score_outputs_v2.py"
+)
+
+
+def load_successor():
+    spec = importlib.util.spec_from_file_location("score_outputs_v2", SUCCESSOR)
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+def provenance(digest="a" * 64):
+    return {"successor": "score_outputs_v2", "files": {"sim/wavlm_large.pt": digest}}
+
+
+def wavs(*digests):
+    return {
+        f"prompt-{index}": {"wav_sha256": digest, "duration_s": 1.25}
+        for index, digest in enumerate(digests)
+    }
+
+
+def completed(module, audio, scorer):
+    document = module.bind_resume(None, list(audio), audio, scorer)
+    document["tasks"].append("wer")
+    document["rows"]["prompt-0"]["wer"] = {"wer": 0.1, "hits": 10}
+    return document
+
+
+def test_changed_wav_resume_does_not_rebind_scores(tmp_path):
+    module = load_successor()
+    scorer = provenance()
+    original_audio = wavs("1" * 64, "2" * 64)
+    document = completed(module, original_audio, scorer)
+    out = tmp_path / "scores.json"
+    out.write_text(json.dumps(document, indent=2), encoding="utf-8")
+    before = out.read_bytes()
+    loaded = json.loads(out.read_text(encoding="utf-8"))
+    snapshot = copy.deepcopy(loaded)
+    changed = wavs("3" * 64, "4" * 64)
+    with pytest.raises(module.StaleScoringOutput, match="WAV provenance differs"):
+        module.resume_output(out, list(changed), changed, scorer)
+    assert out.read_bytes() == before
+    assert loaded == snapshot
+    assert loaded["rows"]["prompt-0"]["wer"]["wer"] == 0.1
+    assert loaded["rows"]["prompt-0"]["wav_sha256"] == "1" * 64
+
+
+def test_duration_id_and_scorer_mismatches_are_rejected(tmp_path):
+    module = load_successor()
+    scorer = provenance()
+    audio = wavs("a" * 64)
+    document = completed(module, audio, scorer)
+    out = tmp_path / "scores.json"
+    out.write_text(json.dumps(document), encoding="utf-8")
+    longer = {"prompt-0": {"wav_sha256": "a" * 64, "duration_s": 2.5}}
+    other_ids = wavs("b" * 64)
+    other_ids["prompt-1"] = other_ids.pop("prompt-0")
+    other_scorer = provenance("b" * 64)
+    historical = copy.deepcopy(document)
+    del historical["scorer_provenance"]
+    cases = (
+        (list(longer), longer, scorer, "WAV provenance differs"),
+        (["prompt-1"], other_ids, scorer, "prompt IDs differ"),
+        (list(audio), audio, other_scorer, "scorer provenance differs"),
+    )
+    for ids, candidate, candidate_scorer, message in cases:
+        with pytest.raises(module.StaleScoringOutput, match=message):
+            module.bind_resume(document, ids, candidate, candidate_scorer)
+    with pytest.raises(module.StaleScoringOutput, match="scorer provenance"):
+        module.bind_resume(historical, list(audio), audio, scorer)
+    assert out.read_bytes()  # the rejected checks never receive this path
+
+
+def test_matching_resume_preserves_completed_scores():
+    module = load_successor()
+    scorer = provenance()
+    audio = wavs("c" * 64, "d" * 64)
+    document = completed(module, audio, scorer)
+    resumed = module.bind_resume(document, list(audio), audio, scorer)
+    assert resumed["tasks"] == ["wer"]
+    assert resumed["rows"]["prompt-0"]["wer"] == {"wer": 0.1, "hits": 10}
+    assert resumed["rows"]["prompt-1"]["wav_sha256"] == "d" * 64
+    assert "wer" not in resumed["rows"]["prompt-1"]
+    assert document == completed(module, audio, scorer)
+
+
+def test_scorer_provenance_changes_when_weight_bytes_change(tmp_path):
+    module = load_successor()
+    weight = tmp_path / "sim" / "wavlm_large.pt"
+    weight.parent.mkdir()
+    weight.write_bytes(b"weight-a")
+    first = module.scorer_provenance(tmp_path)
+    weight.write_bytes(b"weight-b")
+    second = module.scorer_provenance(tmp_path)
+    assert first["files"]["sim/wavlm_large.pt"] != second["files"]["sim/wavlm_large.pt"]
+    audio = wavs("e" * 64)
+    with pytest.raises(module.StaleScoringOutput, match="scorer provenance differs"):
+        module.bind_resume(completed(module, audio, first), list(audio), audio, second)

From 5d43495275b26a2a43c397977de74ccf790b4ee4 Mon Sep 17 00:00:00 2001
From: Cursor Agent <cursoragent@cursor.com>
Date: Wed, 4 Nov 2026 09:06:24 +0000
Subject: [PATCH 38/40] Register the MiniCPM campaign without inventing a
 freeze hash

Classify minicpmo45-l20x-20261021 as a campaign. Its manifest-named
records are descriptive rather than digest maps, so inventory does not
forge or recheck embedded hashes. The installed catalog counts 128
knowledge records once the peer card is kept. The two MiniCPM cases cite
their typed records so the merged knowledge contract can resolve them.

Review: https://github.com/InferMatrixLab/InferRSI/pull/51#pullrequestreview-5626090253
Signed-off-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: amy-why-3459 <amy-why-3459@users.noreply.github.com>
---
 docs/contributing.md                          |  7 +++--
 .../cases/minicpm-conditioning-transport.json |  1 +
 .../cases/minicpm-conditioning-transport.md   |  2 ++
 .../cases/minicpm-speaker-cpu-reference.json  |  1 +
 .../cases/minicpm-speaker-cpu-reference.md    |  2 ++
 tests/check_installed.py                      |  2 +-
 tests/test_evidence_inventory.py              | 29 ++++++++++++++++++-
 tests/test_knowledge_contract.py              |  2 +-
 tools/evidence_inventory.json                 | 12 ++++++++
 tools/validate_evidence.py                    | 11 +++++++
 10 files changed, 63 insertions(+), 6 deletions(-)

diff --git a/docs/contributing.md b/docs/contributing.md
index fea0281b7..b0c30901b 100644
--- a/docs/contributing.md
+++ b/docs/contributing.md
@@ -159,9 +159,10 @@ campaign, template, source-import, review-summary and external-archive layouts;
 new directories and recognizable manifests require an explicit classification.
 The nightly lane runs this CPU-only check. It verifies available bytes using
 existing bundle SHA-256 maps, historical file mappings or archive SHA-256/size
-records. Historical mappings point only to preserved snapshots, never current
-implementations. Do not invent hashes or update frozen manifests to silence a
-failure.
+records. A descriptive manifest classifies a JSON record that is not a digest
+map; the checker does not invent or verify content hashes for it. Historical
+mappings point only to preserved snapshots, never current implementations. Do
+not invent hashes or update frozen manifests to silence a failure.
 
 The JSON result separates structural/hash errors (nonzero exit) from unavailable
 external dependencies. Remote archives are not downloaded; if supplied at their
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json
index 5f06b8aaf..bd5f70cf1 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json
@@ -6,6 +6,7 @@
   ],
   "state": "historical_observation",
   "content": "minicpm-conditioning-transport.md",
+  "required_resources": ["minicpm-conditioning-transport.json"],
   "sources": [
     {
       "type": "internal",
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md
index 7bdf62ce9..45edc7eed 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md
@@ -1,6 +1,8 @@
 # MiniCPM-o conditioning transport: avoid scalar-list roundtrips
 
 This is a scoped host diagnostic from [acceptance issue #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
+Kind, origin, state and source identities belong to the
+[typed source and scope record](minicpm-conditioning-transport.json).
 The transport component preserves values and reduces synthetic CPU work.
 The campaign remains **INCONCLUSIVE**: this observation does not establish
 end-to-end throughput, speech quality or a peer-engine win.
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
index 9810c05a4..5da31f9e8 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json
@@ -6,6 +6,7 @@
   ],
   "state": "historical_observation",
   "content": "minicpm-speaker-cpu-reference.md",
+  "required_resources": ["minicpm-speaker-cpu-reference.json"],
   "sources": [
     {
       "type": "internal",
diff --git a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
index f295c8608..e4b015f93 100644
--- a/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
+++ b/src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.md
@@ -1,6 +1,8 @@
 # MiniCPM-o speaker extraction: preserve the executed reference graph
 
 This is a scoped diagnostic from [acceptance issue #49](https://github.com/InferMatrixLab/InferRSI/issues/49).
+Kind, origin, state and source identities belong to the
+[typed source and scope record](minicpm-speaker-cpu-reference.json).
 The isolated component gate passed; service and generated-speech qualification
 remain separate. Raw measurements belong to the campaign evidence tree.
 
diff --git a/tests/check_installed.py b/tests/check_installed.py
index d412f14ce..8a6288d63 100644
--- a/tests/check_installed.py
+++ b/tests/check_installed.py
@@ -15,7 +15,7 @@
     "This check requires an installed package"
 )
 records = knowledge_records()
-assert len(records) == 127, "Knowledge is missing from the installation"
+assert len(records) == 128, "Knowledge is missing from the installation"
 assert (
     files("inferrsi")
     .joinpath("data", "repo_packs", "vllm_omni", "knowledge", "README.md")
diff --git a/tests/test_evidence_inventory.py b/tests/test_evidence_inventory.py
index 9edd30863..ea4600d87 100644
--- a/tests/test_evidence_inventory.py
+++ b/tests/test_evidence_inventory.py
@@ -141,10 +141,37 @@ def test_external_archive_is_explicit_then_verified_when_available(bundle):
     assert validate_inventory(repo)["errors"]
 
 
+def test_descriptive_manifest_adds_no_hash(bundle):
+    repo, root, inventory = bundle
+    write_json(root / "plan/dataset-manifest.json", {
+        "meta_sha256": "a" * 64,
+        "rows": [{"id": "row", "ref_sha256": "b" * 64}],
+    })
+    inventory["bundles"]["synthetic"]["manifests"].append(
+        {"path": "plan/dataset-manifest.json", "schema": "descriptive"}
+    )
+    write_json(repo / "tools/evidence_inventory.json", inventory)
+    result = validate_inventory(repo)
+    assert result["errors"] == []
+    assert result["checked_hashes"] == 1
+
+
+def test_digest_map_cannot_use_descriptive_schema(bundle):
+    repo, root, inventory = bundle
+    write_json(root / "plan/hidden-manifest.json", {"validator/check.py": "c" * 64})
+    inventory["bundles"]["synthetic"]["manifests"].append(
+        {"path": "plan/hidden-manifest.json", "schema": "descriptive"}
+    )
+    write_json(repo / "tools/evidence_inventory.json", inventory)
+    assert "hash schema" in str(validate_inventory(repo)["errors"])
+
+
 def test_checked_in_inventory():
     repo = Path(__file__).resolve().parents[1]
     result = validate_inventory(repo)
     assert result["errors"] == []
-    assert len(result["bundles"]) == 21
+    assert len(result["bundles"]) == 22
     assert result["checked_hashes"] == 430
+    kinds = {item["name"]: item["kind"] for item in result["bundles"]}
+    assert kinds["minicpmo45-l20x-20261021"] == "campaign"
     assert result["unavailable"]  # Historical raw artifacts are not in this checkout.
diff --git a/tests/test_knowledge_contract.py b/tests/test_knowledge_contract.py
index f0211a8f3..4245154df 100644
--- a/tests/test_knowledge_contract.py
+++ b/tests/test_knowledge_contract.py
@@ -58,7 +58,7 @@ def _case_records():
 
 def test_case_documents_cite_their_record_without_copying_digests():
     cases = list(_case_records())
-    assert len(cases) == 7
+    assert len(cases) == 9
     for path, record in cases:
         body = (path.parent / record["content"]).read_text(encoding="utf-8")
         # The JSON record is the single home for source identities and digests;
diff --git a/tools/evidence_inventory.json b/tools/evidence_inventory.json
index 6ca2cb388..0f6c0e7aa 100644
--- a/tools/evidence_inventory.json
+++ b/tools/evidence_inventory.json
@@ -151,6 +151,18 @@
     "qwen3-tts-ascend-import": {
       "kind": "import", "manifests": [],
       "external": ["Original campaign validators and artifacts remain at the upstream source described in plan/README.md."]
+    },
+    "minicpmo45-l20x-20261021": {
+      "kind": "campaign",
+      "manifests": [
+        {"path": "plan/dataset-manifest.json", "schema": "descriptive"},
+        {"path": "plan/model-manifest.json", "schema": "descriptive"},
+        {"path": "plan/official-model-manifest.json", "schema": "descriptive"},
+        {"path": "patch/peer-round2-manifest.json", "schema": "descriptive"}
+      ],
+      "external": [
+        "Pinned model weights, Seed-TTS references, generated WAVs, scorer weights and raw server logs named by this campaign stay outside the checkout. Embedded digests are historical records and are not rechecked here; this entry does not add a freeze hash."
+      ]
     }
   }
 }
diff --git a/tools/validate_evidence.py b/tools/validate_evidence.py
index 067a93000..b9aca5a0d 100644
--- a/tools/validate_evidence.py
+++ b/tools/validate_evidence.py
@@ -96,11 +96,22 @@ def validate_manifest(repo, bundle, entry, unavailable):
             checked += 1
         else:
             unavailable.append(f"{bundle.name}/{entry['artifact']}: external archive unavailable")
+    elif schema == "descriptive":
+        if not data:
+            raise ValueError("descriptive manifest is empty")
+        if _digest_map(data):
+            raise ValueError("digest map requires a hash schema")
     else:
         raise ValueError("unknown manifest schema")
     return checked
 
 
+def _digest_map(data):
+    return all(
+        isinstance(value, str) and re.fullmatch(r"[0-9a-f]{64}", value) for value in data.values()
+    )
+
+
 def validate_inventory(repo, inventory=None):
     repo = Path(repo).resolve()
     report = {"errors": [], "unavailable": [], "bundles": [], "checked_hashes": 0}

From cdfcd8822aad69ab46369c81effbca4e3e7ce192 Mon Sep 17 00:00:00 2001
From: Cursor Agent <cursoragent@cursor.com>
Date: Wed, 4 Nov 2026 09:06:30 +0000
Subject: [PATCH 39/40] Refresh the skill index from the merged MiniCPM sources

Regenerate packaged skill abstracts so source revisions and content
hashes match the merge, including the MiniCPM case records.

Review: https://github.com/InferMatrixLab/InferRSI/pull/51#pullrequestreview-5626090253
Signed-off-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: amy-why-3459 <amy-why-3459@users.noreply.github.com>
---
 .../data/repo_packs/inferrsi/knowledge/README.md |  4 ++--
 .../skills/ascend-aclgraph-capture-replay.json   |  4 ++--
 .../ascend/skills/ascend-device-health.json      |  4 ++--
 .../skills/ascend-distributed-parallel.json      |  4 ++--
 .../ascend/skills/ascend-graph-mode.json         |  4 ++--
 .../ascend/skills/ascend-model-adaptation.json   |  4 ++--
 .../ascend/skills/ascend-operator-profiling.json |  4 ++--
 .../ascend/skills/ascend-operator-tuning.json    |  4 ++--
 .../skills/ascend-optimization-casebook.json     |  4 ++--
 .../skills/ascend-performance-analysis.json      |  4 ++--
 .../ascend-video-diffusion-optimization.json     |  4 ++--
 .../ascend/skills/ascendc-tiling-design.json     |  4 ++--
 .../ascend/skills/cann-attribution-overlap.json  |  4 ++--
 .../knowledge/ascend/skills/torch-npu.json       |  4 ++--
 .../skills/torchnpu-device-memory-lifecycle.json |  4 ++--
 .../torchnpu-pinned-host-memory-lifecycle.json   |  4 ++--
 .../common/skills/assess-serving-preemption.json |  4 ++--
 .../skills/assess-split-backward-schedule.json   |  4 ++--
 .../skills/audit-fixed-workload-claim.json       |  4 ++--
 .../skills/audit-h3-metal-fasth3-semantics.json  |  4 ++--
 .../skills/audit-h3-runtime-residency.json       |  4 ++--
 .../common/skills/audit-llama-runtime-state.json |  4 ++--
 .../skills/audit-recurrent-kv-finalization.json  |  4 ++--
 .../common/skills/audit-sd-cpp-residency.json    |  4 ++--
 .../skills/audit-sglang-diffusion-lifetimes.json |  4 ++--
 .../common/skills/audit-vllm-kv-lifetimes.json   |  4 ++--
 .../skills/bound-windowed-attention-replay.json  |  4 ++--
 .../skills/budget-speculative-verification.json  |  4 ++--
 .../skills/calibrate-serving-simulation.json     |  4 ++--
 .../common/skills/cgroup-resource-controls.json  |  4 ++--
 .../skills/checkpoint-recovery-consistency.json  |  4 ++--
 .../skills/choose-parallel-training-plan.json    |  4 ++--
 .../common/skills/cite-check-downstream-pr.json  |  4 ++--
 .../knowledge/common/skills/claim-contract.json  |  4 ++--
 .../knowledge/common/skills/comfy-ui.json        |  4 ++--
 .../knowledge/common/skills/competitor-scan.json |  4 ++--
 .../skills/dcp-async-save-performance.json       |  4 ++--
 .../skills/dense-performance-evidence.json       |  4 ++--
 .../skills/diagnose-vllm-admission-pressure.json |  4 ++--
 .../skills/diffusers-invocation-state.json       |  4 ++--
 .../common/skills/draft-acceptance-issue.json    |  4 ++--
 .../knowledge/common/skills/dwarfstar.json       |  4 ++--
 .../evaluate-elastic-serving-placement.json      |  4 ++--
 .../skills/generation-cache-lifecycle.json       |  4 ++--
 .../common/skills/host-memory-management.json    |  4 ++--
 .../skills/host-overhead-optimization.json       |  4 ++--
 .../inferrsi/knowledge/common/skills/husky.json  |  4 ++--
 .../skills/inference-benchmark-design.json       |  4 ++--
 .../skills/inference-optimization-casebook.json  | 16 ++++++++++++----
 .../common/skills/kernel-writing-guide.json      |  4 ++--
 .../common/skills/kv-tier-management.json        |  4 ++--
 .../skills/lazy-evaluation-stream-lifetimes.json |  4 ++--
 .../inferrsi/knowledge/common/skills/lily.json   |  4 ++--
 .../knowledge/common/skills/lithos-metal.json    |  4 ++--
 .../knowledge/common/skills/local-dream.json     |  4 ++--
 .../knowledge/common/skills/mistral-rs.json      |  4 ++--
 .../knowledge/common/skills/mlc-llm.json         |  4 ++--
 .../knowledge/common/skills/mlx-swift-lm.json    |  4 ++--
 .../common/skills/npu-skill-factory.json         |  4 ++--
 .../skills/optimization-search-policy.json       |  4 ++--
 .../common/skills/os-process-placement.json      |  4 ++--
 .../skills/performance-ceiling-analysis.json     |  4 ++--
 .../common/skills/plan-activation-residency.json |  4 ++--
 .../knowledge/common/skills/project-maya.json    |  4 ++--
 .../knowledge/common/skills/pytorch.json         |  4 ++--
 .../skills/repository-evolution-analysis.json    |  4 ++--
 .../knowledge/common/skills/rsi-evidence.json    |  4 ++--
 .../common/skills/skill-evolution-playbook.json  |  4 ++--
 .../inferrsi/knowledge/common/skills/splash.json |  4 ++--
 .../common/skills/storage-io-measurement.json    |  4 ++--
 .../common/skills/training-input-pipeline.json   |  4 ++--
 .../common/skills/training-resource-budget.json  |  4 ++--
 .../skills/video-diffusion-optimization.json     |  4 ++--
 .../knowledge/common/skills/vllm-metal.json      |  4 ++--
 .../skills/weight-loading-optimization.json      |  4 ++--
 .../cuda/skills/audit-afd-p2p-exchanges.json     |  4 ++--
 .../skills/audit-flare-session-lifecycle.json    |  4 ++--
 .../skills/diagnose-attention-bottlenecks.json   |  4 ++--
 .../cuda/skills/host-overhead-profiling.json     |  4 ++--
 .../cuda/skills/reason-hopper-kernels.json       |  4 ++--
 80 files changed, 170 insertions(+), 162 deletions(-)

diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
index 86ee95d7e..73d1bc93d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/README.md
@@ -15,7 +15,7 @@ These are knowledge abstracts (`--kind knowledge`), with namespaced package
 IDs distinct from explicitly selected `checkout_ref` skills. Ascend/CUDA
 procedures use their corresponding backend; shared methods use `common`.
 
-Source snapshot: [7aa3344bf84c42467f43b3a927e1c7d13642bd55](https://github.com/InferMatrixLab/InferRSI/tree/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library).
+Source snapshot: [5d43495275b26a2a43c397977de74ccf790b4ee4](https://github.com/InferMatrixLab/InferRSI/tree/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library).
 
 ```bash
 inferrsi knowledge search 'profiling' --repo-type inferrsi --limit 50
@@ -29,7 +29,7 @@ contain the current input paths and bytes (Git checkout filters are respected).
 
 ```bash
 python tools/build_skill_index.py --source-revision <committed-source-revision>
-python tools/build_skill_index.py --source-revision 7aa3344bf84c42467f43b3a927e1c7d13642bd55 --check
+python tools/build_skill_index.py --source-revision 5d43495275b26a2a43c397977de74ccf790b4ee4 --check
 ```
 
 `--check` detects missing, stale and unexpected generated records without writing.
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
index d628bdadd..c684280a5 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-aclgraph-capture-replay.json
@@ -21,8 +21,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
index f4b372d19..0e4232187 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-device-health.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-device-health/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
index 4b940539c..74ab0f0d4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-distributed-parallel.json
@@ -27,8 +27,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-distributed-parallel/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
index 5c1c8590b..712cd5198 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-graph-mode.json
@@ -26,8 +26,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-graph-mode/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
index 971e9813a..f5d8e9de5 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-model-adaptation.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-model-adaptation/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
index e8d595cbc..37e44282e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-profiling.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-profiling/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
index 64816a247..9e5d19a20 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-operator-tuning.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/ascend/ascend-operator-tuning/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/ascend/skills/ascend-optimization-casebook.json
index 7521c9f69..aafc0ce67 100644
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index 2a4a0ace2..fbb697539 100644
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index a2d677d4d..60c0f0a66 100644
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index ea618b662..130145603 100644
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index ca740b5b7..333ea72ba 100644
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index 7c1cde5ed..bd4fa413a 100644
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index d6676b490..25d06f8a7 100644
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index d6ea1871c..f92f84538 100644
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index 12aeca1fd..fd08a0ccb 100644
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index 7c6e81473..8a657e316 100644
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index a3b85ccdc..fc5e56ed2 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-metal-fasth3-semantics.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-h3-metal-fasth3-semantics.json
index 50b90d31b..8d279967d 100644
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index c01e0e11f..13a384df0 100644
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index 3adab00f6..90ec66392 100644
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-recurrent-kv-finalization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-recurrent-kv-finalization.json
index d5ab3d293..68a0cdcf0 100644
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index 8b883145a..a47e4b6a5 100644
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index 2dab44411..68ab98333 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-sglang-diffusion-lifetimes.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-sglang-diffusion-lifetimes.json
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index a4074b797..a442ed76c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/audit-vllm-kv-lifetimes.json
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index 3c226dfe4..07de15e47 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/bound-windowed-attention-replay.json
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index bb08f2ed5..e7eae5be9 100644
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index 3e86452fe..33a24fbce 100644
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index a88384b33..374e28ea6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/cgroup-resource-controls.json
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index 3572a1f8c..10777c8ff 100644
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index d5ce0bdbf..5ac902663 100644
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index ded00b5e0..50bcc02f0 100644
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index a7f2bfa5d..0a154dbfb 100644
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index acdc57b97..7157e6d31 100644
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index 0f5b0fb34..acdf97840 100644
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index 064e2ca25..72133d736 100644
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index b20edd811..511232a0e 100644
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index 70fd8e8a5..35a0ca493 100644
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index 3a883cf9a..aed9df642 100644
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index e90c2488d..b912a3e09 100644
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index c456f30e9..67a44e327 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dwarfstar.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/dwarfstar.json
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index 3482d1338..0875919e0 100644
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index 7d68adf8b..ec54f177e 100644
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index bb39eac1d..9288c63c0 100644
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index 9f20ba9d7..73d986d8c 100644
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index 3dee4b666..1abb342d7 100644
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index 3d6372c43..41dfc4a54 100644
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+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.json",
+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-conditioning-transport.md",
+        "src/inferrsi/data/skill_library/methods/inference-optimization-casebook/cases/minicpm-speaker-cpu-reference.json",
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@@ -45,11 +49,15 @@
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index 1040189df..22d5c1955 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/kernel-writing-guide.json
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@@ -39,8 +39,8 @@
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index 1c1f0ac80..0e0299b57 100644
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@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json
index c3b8b61d3..7fc54aae7 100644
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+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lazy-evaluation-stream-lifetimes.json
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json
index 8c592e80d..bc578d533 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lily.json
@@ -25,8 +25,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/lily/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
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         "src/inferrsi/data/skill_library/repositories/lily/NOTICE.md",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lithos-metal.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lithos-metal.json
index 26722f7f4..efbc6a96c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lithos-metal.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/lithos-metal.json
@@ -21,8 +21,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/lithos-metal/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json
index cb94c8a24..c860da639 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/local-dream.json
@@ -29,8 +29,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/local-dream/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mistral-rs.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mistral-rs.json
index 636fbe213..2a5d329d4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mistral-rs.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mistral-rs.json
@@ -26,8 +26,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/mistral-rs/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlc-llm.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlc-llm.json
index b94c5f561..a2f6fc259 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlc-llm.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlc-llm.json
@@ -27,8 +27,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json
index fef01f452..fb6f6f4c6 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/mlx-swift-lm.json
@@ -27,8 +27,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
index 1adcbdc00..52e7e7409 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/npu-skill-factory.json
@@ -22,8 +22,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
index 8965fb642..9d96782d4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/optimization-search-policy.json
@@ -21,8 +21,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
index 8c0cf7b12..79806223f 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/os-process-placement.json
@@ -24,8 +24,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
index ae1810d82..b10af5a20 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/performance-ceiling-analysis.json
@@ -22,8 +22,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
index 5ccb28ffe..34b56f58c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/plan-activation-residency.json
@@ -16,8 +16,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json
index abec7ae74..0f345ce8d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/project-maya.json
@@ -25,8 +25,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/pytorch.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/pytorch.json
index 97d160bec..f0ac7f118 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/pytorch.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/pytorch.json
@@ -24,8 +24,8 @@
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
index 27968f7c8..42a21a2ad 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/repository-evolution-analysis.json
@@ -21,8 +21,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
index 465739baa..016688fd7 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/rsi-evidence.json
@@ -22,8 +22,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
index c470e93b8..dbad1764d 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/skill-evolution-playbook.json
@@ -21,8 +21,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
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diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json
index a9476f7cf..ebdb18891 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/splash.json
@@ -25,8 +25,8 @@
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-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/splash/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/splash/LICENSE",
         "src/inferrsi/data/skill_library/repositories/splash/SKILL.md",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
index fc715e09f..612189d55 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/storage-io-measurement.json
@@ -24,8 +24,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
index 045b18bc4..9145227b4 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-input-pipeline.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-input-pipeline/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
index a2429cac2..10f19c13c 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/training-resource-budget.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/methods/training-resource-budget/SKILL.md",
         "src/inferrsi/data/skill_library/methods/training-resource-budget/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json
index 2fbb6eebc..79e7ca36e 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/video-diffusion-optimization.json
@@ -26,8 +26,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/SKILL.md",
         "src/inferrsi/data/skill_library/methods/video-diffusion-optimization/assets/campaign.template.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json
index 179f342ea..5b676307a 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/vllm-metal.json
@@ -26,8 +26,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/repositories/vllm-metal/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/vllm-metal/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/vllm-metal/LICENSE",
         "src/inferrsi/data/skill_library/repositories/vllm-metal/SKILL.md",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
index 3cc50bdee..b09fe8acf 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/common/skills/weight-loading-optimization.json
@@ -29,8 +29,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md",
         "src/inferrsi/data/skill_library/methods/weight-loading-optimization/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json
index 42b227ef5..c6f5c7353 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-afd-p2p-exchanges.json
@@ -23,8 +23,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/SKILL.md",
         "src/inferrsi/data/skill_library/repositories/afd-plugin/audit-afd-p2p-exchanges/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json
index 0fc99822c..f7c725130 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/audit-flare-session-lifecycle.json
@@ -29,8 +29,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/LICENSE",
         "src/inferrsi/data/skill_library/repositories/flare-local-inference/audit-flare-session-lifecycle/SKILL.md",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
index 19f847d38..a3190e995 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/diagnose-attention-bottlenecks.json
@@ -16,8 +16,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
index 7fac0bc38..a8f6c8f7b 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/host-overhead-profiling.json
@@ -22,8 +22,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/host-overhead-profiling/metadata.json",
diff --git a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json
index 55040913f..375d050fd 100644
--- a/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json
+++ b/src/inferrsi/data/repo_packs/inferrsi/knowledge/cuda/skills/reason-hopper-kernels.json
@@ -36,8 +36,8 @@
   "sources": [
     {
       "type": "git",
-      "url": "https://github.com/InferMatrixLab/InferRSI/blob/7aa3344bf84c42467f43b3a927e1c7d13642bd55/src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/SKILL.md",
-      "commit": "7aa3344bf84c42467f43b3a927e1c7d13642bd55",
+      "url": "https://github.com/InferMatrixLab/InferRSI/blob/5d43495275b26a2a43c397977de74ccf790b4ee4/src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/SKILL.md",
+      "commit": "5d43495275b26a2a43c397977de74ccf790b4ee4",
       "paths": [
         "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/SKILL.md",
         "src/inferrsi/data/skill_library/hardware/cuda/reason-hopper-kernels/metadata.json",

From 772e8c17110b268608f8caee4977eec38bc4e606 Mon Sep 17 00:00:00 2001
From: Cursor Agent <cursoragent@cursor.com>
Date: Wed, 4 Nov 2026 09:19:54 +0000
Subject: [PATCH 40/40] Refresh skill coverage digest after the MiniCPM merge

The merged matrices and case records change the coverage input digest.
Regenerate the view; no coverage row was added or promoted.

Review: https://github.com/InferMatrixLab/InferRSI/pull/51#pullrequestreview-5626090253
Signed-off-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: amy-why-3459 <amy-why-3459@users.noreply.github.com>
---
 docs/skill-coverage.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/skill-coverage.md b/docs/skill-coverage.md
index 50c3f1b6c..6ae84378d 100644
--- a/docs/skill-coverage.md
+++ b/docs/skill-coverage.md
@@ -4,7 +4,7 @@ Generated from the registry, the skill sidecars and the two maintained
 matrices. **Do not edit by hand**; regenerate after any registry, skill,
 matrix or frozen-plan change.
 
-- Input digest: `sha256:7640b171256091efd1514a33d5e434eef3feaed238fc92fe3eeba02fee94e9ff`
+- Input digest: `sha256:98d75f9bad153b6cdfbbaf52be5f63b8feb783110c88fc161bc9fcd2d4c6c8e4`
 - Regenerate: `python tools/build_skill_coverage.py`
 - Verify without writing: `python tools/build_skill_coverage.py --check`