head to head · open source

llama.cpp vs lightly-studio

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. lightly-studio has 889 stars, 34 forks, 53 open issues and last shipped yesterday. llama.cpp leads on adoption by 14,364% (128,581 vs 889 stars). llama.cpp is written in C++ under MIT; lightly-studio is written in Python under Apache-2.0. llama.cpp has attracted 18% as many forks as stars, lightly-studio 4%. lightly-studio 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 lightly-studio ★ 889 category AI & Machine Learning

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Side by side

	llama.cpp	lightly-studio
GitHub stars	★ 129K	★ 889
License	MIT	Apache-2.0
Written in	C++	Python
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 34
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 lightly-studio if

You want the lightly-studio 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 lightly-studio fits your workflow better

full lightly-studio 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 lightly-studio

LightlyStudio is an Apache 2.0 Python application that opens in a browser and lets computer vision and MLOps practitioners curate, annotate, and manage image and video datasets entirely on their own machine, with no account and no data leaving the local system.

read the full lightly-studio overview →

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Frequently asked questions

Is llama.cpp or lightly-studio more popular?

llama.cpp has 128,581 GitHub stars and lightly-studio has 889. llama.cpp has the larger community by that measure.

Are llama.cpp and lightly-studio free?

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

What is the difference between llama.cpp and lightly-studio?

llama.cpp is written in C++ and lightly-studio 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 lightly-studio?

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