head to head · open source

llama.cpp vs kitops

llama.cpp has 133,181 GitHub stars, 25,063 forks, 2,464 open issues and last shipped yesterday. kitops has 1,439 stars, 188 forks, 50 open issues and last shipped yesterday. llama.cpp leads on adoption by 9,155% (133,181 vs 1,439 stars). llama.cpp is written in C++ under MIT; kitops is written in Go under Apache-2.0. llama.cpp has attracted 19% as many forks as stars, kitops 13%. kitops 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 kitops ★ 1.4K category AI & Machine Learning

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Side by side

	llama.cpp	kitops
GitHub stars	★ 133K	★ 1.4K
License	MIT	Apache-2.0
Written in	C++	Go
Last push	2026-11-02	2026-11-02
Forks	⑂ 25K	⑂ 188
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 kitops if

You want the kitops 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 kitops fits your workflow better

full kitops 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 kitops

KitOps: Standards based packaging & versioning for AI/ML projects Table of Contents What is KitOps? Try KitOps How Teams Use KitOps KitOps Architecture Security and Compliance KitOps by Role Integrations Community and Support What is KitOps? KitOps is a CNCF open source tool for packaging, versioning, and securely sharing AI/ML projects. Built on the same OCI (Open Container Initiative) technology that underlies containers, KitOps packages everything your model needs for development or production into a versioned and layered artifact stored in your existing container registry. It integrates with all your AI/ML…

read the full kitops overview →

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Frequently asked questions

Is llama.cpp or kitops more popular?

llama.cpp has 133,181 GitHub stars and kitops has 1,439. llama.cpp has the larger community by that measure.

Are llama.cpp and kitops free?

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

What is the difference between llama.cpp and kitops?

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

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