MLX LM vs Xinference
A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.
Not the right match-up?
MLX LM
Run and fine-tune LLMs locally on Apple Silicon with MLX
VS
Xinference
Distributed inference framework for LLMs and embeddings
| Feature | MLX LM | Xinference |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | Apache-2.0 |
| Language | Python | Python |
| Setup difficulty | Medium | Medium |
| Min. RAM | 16,384 MB | 8,192 MB |
| Deployment | source, binary | docker, kubernetes, source |
| GitHub stars | ★ 6,543 | ★ 9,483 |
| First released | 2024 | 2023 |
| Replaces | OpenAI API | OpenAI API, Hugging Face Inference Endpoints |
Why pick each one
Choose MLX LM if…
- Released under the MIT license
- Mature project with 6.5k GitHub stars
- Written in Python
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 MLX LM or Xinference better?
Neither is universally better. Xinference has the larger community; both share a medium setup difficulty, so the decision comes down to features and licensing.
Are MLX LM and Xinference free and open-source?
Yes. MLX LM is licensed under MIT and Xinference under Apache-2.0. Both can be self-hosted at no software cost.
Can I run MLX LM and Xinference with Docker?
MLX LM: check the project docs for container support. Xinference: yes.