head to head · open source

llama.cpp vs infinity

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. infinity has 4,755 stars, 458 forks, 126 open issues and last shipped yesterday. llama.cpp leads on adoption by 2,701% (133,181 vs 4,755 stars). llama.cpp is written in C++ under MIT; infinity is written in C++ under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, infinity 10%. 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 infinity ★ 4.8K category AI & Machine Learning

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Side by side

	llama.cpp	infinity
GitHub stars	★ 133K	★ 4.8K
License	MIT	Apache-2.0
Written in	C++	C++
Last push	2026-11-02	2026-11-02
Forks	⑂ 25K	⑂ 458
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 infinity if

You want the infinity feature set and don't need the biggest community
You prefer the Apache-2.0 license terms
Your stack matches C++
You evaluated both and infinity fits your workflow better

full infinity 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…

read the full llama.cpp overview →

About infinity

The AI native database built for LLM applications, providing incredibly fast hybrid search of dense embedding, sparse embedding, tensor and full text Document Benchmark Twitter Discord Infinity is a cutting edge AI native database that provides a wide range of search capabilities for rich data types such as dense vector, sparse vector, tensor, full text, and structured data. It provides robust support for various LLM applications, including search, recommenders, question answering, conversational AI, copilot, content generation, and many more RAG (Retrieval augmented Generation) applications. Key Features Get…

read the full infinity overview →

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Frequently asked questions

Is llama.cpp or infinity more popular?

llama.cpp has 133,181 GitHub stars and infinity has 4,755. llama.cpp has the larger community by that measure.

Are llama.cpp and infinity free?

Both are open source. llama.cpp is licensed under MIT and infinity under Apache-2.0. Neither carries a licence fee.

What is the difference between llama.cpp and infinity?

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

Choose llama.cpp if you want the larger community (133,181 stars) or its MIT licence terms. Choose infinity if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.