head to head · open source

llama.cpp vs burr

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. burr has 2,589 stars, 215 forks, 99 open issues and last shipped yesterday. llama.cpp leads on adoption by 5,044% (133,181 vs 2,589 stars). llama.cpp is written in C++ under MIT; burr is written in Python under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, burr 8%. 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 burr ★ 2.6K category AI & Machine Learning

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Side by side

	llama.cpp	burr
GitHub stars	★ 133K	★ 2.6K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-11-02	2026-11-02
Forks	⑂ 25K	⑂ 215
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 burr if

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

full burr 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 burr

Apache Burr (incubating) Apache Burr (incubating) makes it easy to develop applications that make decisions (chatbots, agents, simulations, etc...) from simple python building blocks. Apache Burr works well for any application that uses LLMs, and can integrate with any of your favorite frameworks. Burr includes a UI that can track/monitor/trace your system in real time, along with pluggable persisters (e.g. for memory) to save & load application state. Link to documentation. Quick ( [!NOTE] In version 0.43.0, the optional CLI included with [start] , [learn] , and [cli] requires Python 3.10+. Core library usage…

read the full burr overview →

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Frequently asked questions

Is llama.cpp or burr more popular?

llama.cpp has 133,181 GitHub stars and burr has 2,589. llama.cpp has the larger community by that measure.

Are llama.cpp and burr free?

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

What is the difference between llama.cpp and burr?

llama.cpp is written in C++ and burr in Python. 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 burr?

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