head to head · open source

llama.cpp vs faiss

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. faiss has 41,251 stars, 4,584 forks, 327 open issues and last shipped 2 days ago. llama.cpp leads on adoption by 223% (133,181 vs 41,251 stars). llama.cpp is written in C++ under MIT; faiss is written in C++ under MIT. llama.cpp has attracted 19% as many forks as stars, faiss 11%. 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 ★ 133K faiss ★ 41K category AI & Machine Learning

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Side by side

	llama.cpp	faiss
GitHub stars	★ 133K	★ 41K
License	MIT	MIT
Written in	C++	C++
Last push	2026-11-02	2026-11-01
Forks	⑂ 25K	⑂ 4.6K
Self-hosting	Yes	Yes
Data ownership	Your server	Your server

pick llama.cpp if

You weight community size — 133K 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 faiss if

You want the faiss feature set and don't need the biggest community
You prefer the MIT license terms
Your stack matches C++
You evaluated both and faiss fits your workflow better

full faiss profile →

About llama.cpp

llama.cpp LLM inference in C/C++ ggml / ops / maintainer PRs%20sort%3Aupdated desc) / dev stats / lib llama API / llama server REST API Quick start A few options to get llama.cpp installed on your machine: Visit and follow the instructions Run with Docker see our Docker documentation Download pre built binaries from the releases page Build from source by cloning this repository check out our build guide Once installed: VLM session with llama cli Built in web UI against llama serve Description The main goal of llama.cpp is to enable LLM (and VLM) inference with minimal setup and state of the art performance on a…

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About faiss

Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed primarily at Meta's Fundamental AI Research group. News See CHANGELOG.md for detailed information about latest features. Introduction Faiss contains several methods for similarity search. It assumes that…

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Frequently asked questions

Is llama.cpp or faiss more popular?

llama.cpp has 133,181 GitHub stars and faiss has 41,251. llama.cpp has the larger community by that measure.

Are llama.cpp and faiss free?

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

What is the difference between llama.cpp and faiss?

llama.cpp is written in C++ and faiss in C++. 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 faiss?

Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose faiss if its feature set, stack or MIT licence fits better. Both are self-hostable.