head to head · open source

llama.cpp vs claude-context

llama.cpp has 128,880 GitHub stars, 23,468 forks, 2,464 open issues and last shipped today. claude-context has 12,548 stars, 926 forks, 146 open issues and last shipped 2 months ago. llama.cpp leads on adoption by 927% (128,880 vs 12,548 stars). llama.cpp is written in C++ under MIT; claude-context is written in TypeScript under MIT. llama.cpp has attracted 18% as many forks as stars, claude-context 7%. llama.cpp was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

llama.cpp ★ 129K claude-context ★ 13K category AI & Machine Learning

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Side by side

	llama.cpp	claude-context
GitHub stars	★ 129K	★ 13K
License	MIT	MIT
Written in	C++	TypeScript
Last push	2026-09-20	2026-07-14
Forks	⑂ 23K	⑂ 926
Self-hosting	Yes	Yes
Data ownership	Your server	Your server

pick llama.cpp if

You weight community size — 129K stars and counting
You want the MIT license terms
Your stack matches C++
You value the larger contributor base for long-term maintenance

full llama.cpp profile →

pick claude-context if

You want the claude-context feature set and don't need the biggest community
You prefer the MIT license terms
Your stack matches TypeScript
You evaluated both and claude-context fits your workflow better

full claude-context profile →

About llama.cpp

llama.cpp is a C/C++ library and set of command line tools for running large language models (LLMs) and vision language models (VLMs) locally. It enables inference without external dependencies, targeting diverse hardware including Apple Silicon, x86 CPUs, NVIDIA GPUs (via CUDA), AMD GPUs (via HIP), and other accelerators. The project lives in the ggml ecosystem, leveraging the ggml tensor computation library for low level operations and quantized model execution.

read the full llama.cpp overview →

About claude-context

Claude Context is an open source Model Context Protocol (MCP) plugin that adds semantic code search to Claude Code and other AI coding agents. It is written in TypeScript, licensed under MIT, and published to npm as @zilliz/claude context core and @zilliz/claude context mcp . The project lives in the AI coding agent ecosystem, where it plugs into MCP compatible clients such as Claude Code, OpenAI Codex CLI, Cursor, and Gemini CLI. A companion VS Code extension is distributed through the Visual Studio Marketplace as zilliz.semanticcodesearch .

read the full claude-context overview →

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Frequently asked questions

Is llama.cpp or claude-context more popular?

llama.cpp has 128,880 GitHub stars and claude-context has 12,548. llama.cpp has the larger community by that measure.

Are llama.cpp and claude-context free?

Both are open source. llama.cpp is licensed under MIT and claude-context under MIT. Neither carries a licence fee.

What is the difference between llama.cpp and claude-context?

llama.cpp is written in C++ and claude-context in TypeScript. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, llama.cpp or claude-context?

Choose llama.cpp if you want the larger community (128,880 stars) or its MIT licence terms. Choose claude-context if its feature set, stack or MIT licence fits better. Both are self-hostable.