llama.cpp vs Xinference
A side-by-side comparison of two self-hosted apps from related categories — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
llama.cpp
High-performance LLM inference in plain C/C++
VS
Xinference
Distributed inference framework for LLMs and embeddings
| Feature | llama.cpp | Xinference |
|---|---|---|
| Category | Local LLM Runners | Self-Hosted AI |
| License | MIT | Apache-2.0 |
| Language | C++ | Python |
| Setup difficulty | Hard | Medium |
| Min. RAM | 8,192 MB | 8,192 MB |
| Deployment | binary, bare-metal, docker | docker, kubernetes, source |
| GitHub stars | ★ 123,039 | ★ 9,483 |
| First released | 2023 | 2023 |
| Replaces | OpenAI API | OpenAI API, Hugging Face Inference Endpoints |
Why pick each one
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++
Choose Xinference if…
- Released under the Apache-2.0 license
- First-class Docker support for quick deployment
- Kubernetes-ready with Helm charts available
- Mature project with 9.5k GitHub stars
Frequently asked questions
Is llama.cpp or Xinference better?
Neither is universally better. llama.cpp has the larger community, while Xinference is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are llama.cpp and Xinference free and open-source?
Yes. llama.cpp is licensed under MIT and Xinference under Apache-2.0. Both can be self-hosted at no software cost.
Can I run llama.cpp and Xinference with Docker?
llama.cpp: yes. Xinference: yes.