exo vs llama.cpp
A side-by-side comparison of two self-hosted local llm runners options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
exo
Run your own AI cluster across everyday devices
VS
llama.cpp
High-performance LLM inference in plain C/C++
| Feature | exo | llama.cpp |
|---|---|---|
| Category | Local LLM Runners | Local LLM Runners |
| License | GPL-3.0 | MIT |
| Language | Python | C++ |
| Setup difficulty | Medium | Hard |
| Min. RAM | 8,192 MB | 8,192 MB |
| Deployment | source | binary, bare-metal, docker |
| GitHub stars | ★ 46,708 | ★ 123,039 |
| First released | 2024 | 2023 |
| Replaces | OpenAI API | OpenAI API |
Why pick each one
Choose exo if…
- Released under the GPL-3.0 license
- Mature project with 46.7k GitHub stars
- Written in Python
Choose llama.cpp if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 123k GitHub stars
- Written in C++
Frequently asked questions
Is exo or llama.cpp better?
Neither is universally better. llama.cpp has the larger community, while exo is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are exo and llama.cpp free and open-source?
Yes. exo is licensed under GPL-3.0 and llama.cpp under MIT. Both can be self-hosted at no software cost.
Can I run exo and llama.cpp with Docker?
exo: check the project docs for container support. llama.cpp: yes.