head to head · open source

llama.cpp vs ome

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. ome has 523 stars, 106 forks, 134 open issues and last shipped yesterday. llama.cpp leads on adoption by 25,365% (133,181 vs 523 stars). llama.cpp is written in C++ under MIT; ome is written in Go under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, ome 20%. 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 ome ★ 523 category AI & Machine Learning

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Side by side

	llama.cpp	ome
GitHub stars	★ 133K	★ 523
License	MIT	Apache-2.0
Written in	C++	Go
Last push	2026-11-02	2026-11-02
Forks	⑂ 25K	⑂ 106
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 ome if

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

full ome 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 ome

OME (Open Model Engine) — Kubernetes Operator for LLM Serving What is OME? OME (Open Model Engine) is a Kubernetes operator for enterprise grade management and serving of Large Language Models (LLMs). It optimizes the deployment and operation of LLMs by automating model management, intelligent runtime selection, efficient resource utilization, and sophisticated deployment patterns. Read the documentation to learn more about OME capabilities and features. Features Overview Model Management: Models are first class citizen custom resources in OME. Sophisticated model parsing extracts architecture, parameter count…

read the full ome overview →

More in AI & Machine Learning

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Frequently asked questions

Is llama.cpp or ome more popular?

llama.cpp has 133,181 GitHub stars and ome has 523. llama.cpp has the larger community by that measure.

Are llama.cpp and ome free?

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

What is the difference between llama.cpp and ome?

llama.cpp is written in C++ and ome in Go. 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 ome?

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