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.
| Feature | MLX LM | Xinference |
|---|---|---|
| Deploy effort | Read-the-docs project | Under-an-hour setup |
| Health score | 89 · Excellent | 93 · Excellent |
| 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 | ★ 7,117 | ★ 9,592 |
| First released | 2024 | 2023 |
| Replaces | OpenAI API | OpenAI API, Hugging Face Inference Endpoints |
What are MLX LM and Xinference?
MLX LM
MLX LM is a Python package from Apple's MLX project for running and fine-tuning large language models efficiently on Apple Silicon. It provides a command-line interface and HTTP server for local text generation entirely on-device.
- Native Apple Silicon inference
- LoRA fine-tuning
- OpenAI-compatible server
- Model quantization
Xinference
Xorbits Inference (Xinference) is a framework for serving language, embedding, image, audio, and rerank models with a single command. It exposes OpenAI-compatible APIs and supports distributed deployment across multiple machines.
- Serve LLMs, embeddings and images
- OpenAI-compatible API
- Distributed cluster support
- Built-in model registry
MLX LM vs Xinference: key differences
Both projects are written in Python. Licensing differs — MIT for MLX LM versus Apache-2.0 for Xinference. Xinference is the lighter option, starting around 8,192 MB of RAM against 16,384 MB for MLX LM. Xinference lists first-class Docker deployment; MLX LM does not.
Why pick each one
Choose MLX LM if…
- Released under the MIT license
- Mature project with 7.1k 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 9.6k 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.
Which is lighter on resources, MLX LM or Xinference?
Xinference has the smaller minimum footprint at 8,192 MB of RAM, compared to about 16,384 MB for MLX LM. Real-world usage depends on library size, user count, and enabled features.