GitHub topic

mixture-of-experts GitHub repositories

Explore 11 tracked GitHub repositories tagged mixture-of-experts. Compare their recorded star activity and implementation languages, then follow related topics to find other projects.

Snapshot: 2026-10-28. The collection gained 235 stars since the previous daily snapshot.

Tracked repositories: 11
Total stars: 70,867
Stars gained · 7 days: +1,387
Stars gained · 30 days: +4,195

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Star activity for mixture-of-experts repositories on this page
Repository	Total stars	Today	7 days	30 days
mw00/project-maya	2.1K	+100	+807	+1,340
bojieli/ai-infra-book	7.1K	+44	+261	+1,644
VecSzn/PolyStrata	574	+33	+74	+74
carloslfu/slotstream	595	+24	+24	+24
peonist-ai/halogen-flash-server	1.1K	+12	+79	+395

Explore repositories

Showing 1–11 of 11 tracked repositories.

mw00/project-maya

Project Maya - run GLM-5.3-Flash (321B MoE), DeepSeek-V4.1-Flash-1017 (748B MoE) and MiniMax-M3.1-Flash (428B MoE) privately on your own GPU(s), from one card to 16, NVIDIA or AMD, Linux or Windows. Engine, server, dashboard, OpenAI- and Anthropic-compatible API, quant tools.

★ 2.1K+100 todayCuda

llm self-hosted

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bojieli/ai-infra-book

《深入理解 AI Infra：量化分析与系统设计》（李博杰著）开源书稿：从硬件约束和模型架构出发，量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验

★ 7.1K+44 todayPython

llm deepseek

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VecSzn/PolyStrata

Run large AI models on your own PC: Qwen3.8-Flash-Next on Strata's engine, and GLM 5.3 Flash, DeepSeek V4 Flash, LFM2.5, Qwen3.6, Ornith 1.5, Gemma 4, Tiel Coder and MiniCPM-V on a second engine written for PolyStrata. One-click install for Windows and Linux, OpenAI/Anthropic API on localhost.

★ 574+33 todayC++

llm self-hosted

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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.

★ 595+24 todaySwift

llm claude-code

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peonist-ai/halogen-flash-server

Local inference that behaves like a frontier API: Qwen3.8-Flash-Next on AMD Strix Halo plus small NPU models, over the OpenAI and Anthropic APIs on one port.

★ 1.1K+12 todayShell

llm qwen

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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.

Helldez/BigMoeOnEdge

Run MoE models bigger than your RAM. Frontier-size MoE on a phone, laptop, edge. Lossless, on stock llama.cpp. An adaptive streaming optimizer. Any hardware, any OS, any model, any quantization, behind a local OpenAI-compatible server.

★ 678+10 todayC++

llm inference

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