head to head · open source

llama.cpp vs genkit

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. genkit has 6,563 stars, 875 forks, 741 open issues and last shipped yesterday. llama.cpp leads on adoption by 1,929% (133,181 vs 6,563 stars). llama.cpp is written in C++ under MIT; genkit is written in TypeScript under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, genkit 13%. 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 genkit ★ 6.6K category AI & Machine Learning

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Side by side

	llama.cpp	genkit
GitHub stars	★ 133K	★ 6.6K
License	MIT	Apache-2.0
Written in	C++	TypeScript
Last push	2026-11-02	2026-11-02
Forks	⑂ 25K	⑂ 875
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 genkit if

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

full genkit 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 genkit

Genkit is an open source framework for building full stack AI powered applications, built and used in production by Google's Firebase. It provides SDKs for multiple programming languages with varying levels of stability: JavaScript/TypeScript : Production ready with full feature support Go : Production ready with full feature support Python (Beta) : Wide feature support approaching production readiness Dart (Preview) : Early development with core functionality It offers a unified interface for integrating AI models from providers like Google, OpenAI, Anthropic, Ollama, and more. Rapidly build and deploy…

read the full genkit overview →

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Frequently asked questions

Is llama.cpp or genkit more popular?

llama.cpp has 133,181 GitHub stars and genkit has 6,563. llama.cpp has the larger community by that measure.

Are llama.cpp and genkit free?

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

What is the difference between llama.cpp and genkit?

llama.cpp is written in C++ and genkit in TypeScript. 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 genkit?

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