freetoken

I Ran Qwen 3.8 27B on Just 4GB VRAM! (FreeToken Tutorial) - Edge-native MoE serving engine for local LLMs on low VRAM GPUs

Unofficial FreeToken fork: Flash-Next 125B at 38 tok/s on two RTX 3060s with 2-bit experts, gpt-oss-120b on one; a benchmark tunes your settings. Qwen3.8-Flash-Next, 12 GB, MTP, 250k context, image input, WSL2. Runs on Turing: RTX 2060, RTX 20 series, sm_75.

RTX 4060 笔记本本地部署 Qwen3.6-35B-A3B (FreeToken) + Qwen3.5-9B (llama.cpp) 全记录：架构、实测、踩坑

Forked from FlashML-org/FreeToken, with AMD Strix Halo (gfx1151) ROCm support and kernel tuning

Reproducible Apple-Silicon (Apple MLX) deployment and one-token verification kit for the FreeToken edge-native MoE serving API — pinned, loopback-only, schema-validated evidence.

Reproducible FreeToken MoE expert-offload compatibility lab and benchmarks for NVIDIA Turing sm_75.

Top-down browser factory automation game built with a local Qwen coding model. Mine resources, automate production, power your outpost, and craft Engines in the Relay Seven world.

Qwen3.8 Flash Next on RTX 5090: tested 131K-context profile, MTP/PLE fixes, NUMA hardware notes and reproducible client benchmarks