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1. deepseek-v4-flash-0731-in-c deepseek-v4-flash-0731-in-c Public

   Run the native 284B-A13B DeepSeek-V4-Flash-0731 LLM locally on a single laptop CPU: pure C, 8 GB RAM minimum, no GPU, best TPOT 0.892 s/token. ｜ 在笔记本单颗 CPU 上本地运行原生 284B-A13B DeepSeek-V4-Flash-0731 …

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2. qwen3.8-27b-in-c qwen3.8-27b-in-c Public

   Qwen3.8-27B on one laptop CPU: up to 2.52 token/s, 8 GB tested, with no accuracy loss from runtime speedups. Native C, no GPU or Python. | 单颗笔记本 CPU 运行 Qwen3.8-27B：最快 2.52 token/s，最低 8 GB 内存可运行；推理加…

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3. slime slime Public

   Forked from THUDM/slime

   slime is an LLM post-training framework for RL Scaling.

   Python

4. Awesome-LLM-Inference Awesome-LLM-Inference Public

   Forked from xlite-dev/Awesome-LLM-Inference

   📚A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.🎉

   Python

5. Awesome-LLM-Inference-Engine Awesome-LLM-Inference-Engine Public

   Forked from sihyeong/Awesome-LLM-Inference-Engine

6. cpu-native-lm-train cpu-native-lm-train Public

   34.1M LM on a laptop CPU: 215,771 tok/s, 8,529x Qwen. QSELM beats Qwen3.5-0.8B on sealed long-document QA (90.6% vs 45.8%) and Qwen3-0.6B-FC on cross-turn agent memory (69.6% vs 3.2%). No GPU. | 笔记…

   Python