head to head · open source

llama.cpp vs OpenLLM

llama.cpp has 133,101 GitHub stars, 25,042 forks, 2,464 open issues and last shipped yesterday. OpenLLM has 12,576 stars, 848 forks, 20 open issues and last shipped 8 days ago. llama.cpp leads on adoption by 958% (133,101 vs 12,576 stars). llama.cpp is written in C++ under MIT; OpenLLM is written in Python under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, OpenLLM 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 ★ 133K OpenLLM ★ 13K category AI & Machine Learning

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Side by side

	llama.cpp	OpenLLM
GitHub stars	★ 133K	★ 13K
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-11-02	2026-10-26
Forks	⑂ 25K	⑂ 848
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 OpenLLM if

You want the OpenLLM 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 OpenLLM fits your workflow better

full OpenLLM 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 OpenLLM

🦾 OpenLLM: Self Hosting LLMs Made Easy OpenLLM allows developers to run any open source LLMs (Llama 3.3, Qwen2.5, Phi3 and more) or custom models as OpenAI compatible APIs with a single command. It features a built in chat UI, state of the art inference backends, and a simplified workflow for creating enterprise grade cloud deployment with Docker, Kubernetes, and BentoCloud. Understand the design philosophy of OpenLLM. Get Started Run the following commands to install OpenLLM and explore it interactively. Supported models OpenLLM supports a wide range of state of the art open source LLMs. You can also add a…

read the full OpenLLM overview →

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Frequently asked questions

Is llama.cpp or OpenLLM more popular?

llama.cpp has 133,101 GitHub stars and OpenLLM has 12,576. llama.cpp has the larger community by that measure.

Are llama.cpp and OpenLLM free?

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

What is the difference between llama.cpp and OpenLLM?

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

Choose llama.cpp if you want the larger community (133,101 stars) or its MIT licence terms. Choose OpenLLM if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.