head to head · open source

llama.cpp vs Olares

llama.cpp has 128,581 GitHub stars, 23,334 forks, 2,464 open issues and last shipped yesterday. Olares has 5,276 stars, 327 forks, 155 open issues and last shipped yesterday. llama.cpp leads on adoption by 2,337% (128,581 vs 5,276 stars). llama.cpp is written in C++ under MIT; Olares is written in Go under AGPL-3.0. llama.cpp has attracted 18% as many forks as stars, Olares 6%. Olares 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 Olares ★ 5.3K category AI & Machine Learning

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Side by side

	llama.cpp	Olares
GitHub stars	★ 129K	★ 5.3K
License	MIT	AGPL-3.0
Written in	C++	Go
Last push	2026-09-17	2026-09-17
Forks	⑂ 23K	⑂ 327
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 Olares if

You want the Olares feature set and don't need the biggest community
You prefer the AGPL-3.0 license terms
Your stack matches Go
You evaluated both and Olares fits your workflow better

full Olares 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 Olares

Olares is an open source personal cloud operating system built to run AI agents and large language models on hardware you own. It is written in Go and released under the AGPL 3.0 license, and it sits in the cloud native and self hosted corner of the machine learning infrastructure ecosystem. The project describes itself as an operating system you operate in plain language, powered by Kubernetes, turning a machine or a set of machines into a self hosted AI platform reachable from any browser.

read the full Olares overview →

More in AI & Machine Learning

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llama.cpp vs Ollama llama.cpp vs vllm llama.cpp vs GPT4All llama.cpp vs llama_index llama.cpp vs LocalAI llama.cpp vs PageIndex llama.cpp vs Langfuse llama.cpp vs cognee llama.cpp vs taipy llama.cpp vs dagster llama.cpp vs zvec llama.cpp vs langchain4j

Frequently asked questions

Is llama.cpp or Olares more popular?

llama.cpp has 128,581 GitHub stars and Olares has 5,276. llama.cpp has the larger community by that measure.

Are llama.cpp and Olares free?

Both are open source. llama.cpp is licensed under MIT and Olares under AGPL-3.0. Neither carries a licence fee.

What is the difference between llama.cpp and Olares?

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

Choose llama.cpp if you want the larger community (128,581 stars) or its MIT licence terms. Choose Olares if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.