head to head · open source

llama.cpp vs OpenLIT

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. OpenLIT has 2,770 stars, 388 forks, 60 open issues and last shipped yesterday. llama.cpp leads on adoption by 4,542% (128,581 vs 2,770 stars). llama.cpp is written in C++ under MIT; OpenLIT is written in TypeScript under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, OpenLIT 14%. 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 ★ 129K OpenLIT ★ 2.8K category AI & Machine Learning

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Side by side

	llama.cpp	OpenLIT
GitHub stars	★ 129K	★ 2.8K
License	MIT	Apache-2.0
Written in	C++	TypeScript
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 388
Self-hosting	Yes	Yes
Data ownership	Your server	Your server

pick llama.cpp if

You weight community size — 129K 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 OpenLIT if

You want the OpenLIT 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 OpenLIT fits your workflow better

full OpenLIT profile →

About llama.cpp

llama.cpp is a C/C++ library and set of command line tools for running large language models (LLMs) and vision language models (VLMs) locally. It enables inference without external dependencies, targeting diverse hardware including Apple Silicon, x86 CPUs, NVIDIA GPUs (via CUDA), AMD GPUs (via HIP), and other accelerators. The project lives in the ggml ecosystem, leveraging the ggml tensor computation library for low level operations and quantized model execution.

read the full llama.cpp overview →

About OpenLIT

OpenLIT is an open source, OpenTelemetry native observability and evaluation platform for AI applications, AI agents and coding agents, built for engineers who run LLM backed systems and need to see what those systems actually did.

read the full OpenLIT overview →

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Frequently asked questions

Is llama.cpp or OpenLIT more popular?

llama.cpp has 128,581 GitHub stars and OpenLIT has 2,770. llama.cpp has the larger community by that measure.

Are llama.cpp and OpenLIT free?

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

What is the difference between llama.cpp and OpenLIT ?

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

Choose llama.cpp if you want the larger community (128,581 stars) or its MIT licence terms. Choose OpenLIT if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.