1.FareedKhan-dev / kimi-k3-in-c
A 2.78-trillion-parameter Kimi K3 running inference on a single CPU in 8.24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.
+470 stars
from 8,805 · score 6.15
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2.datawhalechina / zero-to-sglang
Official SGLang x Datawhale course on LLM inference: understand inference, build a mini-sglang from scratch, then read the real SGLang source and land your first PR. Available in English and Chinese.
+321 stars
from 1,354 · score 5.77
3.carloslfu / slotstream
Run a 105 GB AI model on a Mac that can't hold it. Qwen3.8-Flash-Next 4-bit, streamed from SSD on 16–64 GB Apple Silicon Macs. Fully native Swift, MLX and Metal. Offline, no Python. CLI, Swift library, and Ollama/OpenAI/Anthropic APIs. Works with Claude Code and Codex.
+247 stars
from 393 · score 5.51
4.nobodywho-ooo / nobodywho
NobodyWho is an inference engine that lets you run LLMs locally and efficiently on any device.
+160 stars
from 1,506 · score 5.08
5.halfrost / Halfrost-Field
✍🏻 Source Code Deep Dives, System Design & Engineering Blogs | Halfrost-Field 冰霜之地：源码解析、系统设计与工程实践笔记
+20 stars
from 13,233 · score 3.04