head to head · open source
Ollama vs llama.cpp
Ollama has 181,161 GitHub stars, 17,917 forks, 3,957 open issues and last shipped yesterday. llama.cpp has 128,581 stars, 23,334 forks, 2,464 open issues and last shipped yesterday. Ollama leads on adoption by 41% (181,161 vs 128,581 stars). Ollama is written in Go under MIT; llama.cpp is written in C++ under MIT. Ollama has attracted 10% as many forks as stars, llama.cpp 18%. Ollama 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.
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Side by side
| Ollama | llama.cpp | |
|---|---|---|
| GitHub stars | ★ 181K | ★ 129K |
| License | MIT | MIT |
| Written in | Go | C++ |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 18K | ⑂ 23K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Ollama if
- You weight community size — 181K stars and counting
- You want the MIT license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick llama.cpp if
- You want the llama.cpp feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches C++
- You evaluated both and llama.cpp fits your workflow better
About Ollama
Ollama is a Go based, MIT licensed runtime that downloads and runs open source large language models such as DeepSeek, Qwen, Gemma, GLM, MiniMax and gpt oss locally on a user's own machine, and it is aimed at developers and teams that want model inference without routing prompts through a hosted API.
read the full Ollama overview →
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 →
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Frequently asked questions
Is Ollama or llama.cpp more popular?
Ollama has 181,161 GitHub stars and llama.cpp has 128,581. Ollama has the larger community by that measure.
Are Ollama and llama.cpp free?
Both are open source. Ollama is licensed under MIT and llama.cpp under MIT. Neither carries a licence fee.
What is the difference between Ollama and llama.cpp?
Ollama is written in Go and llama.cpp in C++. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Ollama or llama.cpp?
Choose Ollama if you want the larger community (181,161 stars) or its MIT licence terms. Choose llama.cpp if its feature set, stack or MIT licence fits better. Both are self-hostable.