MLX LM vs Petals
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?
MLX LM
Run and fine-tune LLMs locally on Apple Silicon with MLX
VS
Petals
Run large language models collaboratively in a swarm
| Feature | MLX LM | Petals |
|---|---|---|
| Category | Self-Hosted AI | Local LLM Runners |
| License | MIT | MIT |
| Language | Python | Python |
| Setup difficulty | Medium | Hard |
| Min. RAM | 16,384 MB | 8,192 MB |
| Deployment | source, binary | source, docker |
| GitHub stars | ★ 6,543 | ★ 10,483 |
| First released | 2024 | 2022 |
| Replaces | OpenAI API | OpenAI API |
Why pick each one
Choose MLX LM if…
- Released under the MIT license
- Mature project with 6.5k GitHub stars
- Written in Python
Choose Petals if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 10.5k GitHub stars
- Written in Python
Frequently asked questions
Is MLX LM or Petals better?
Neither is universally better. Petals has the larger community, while MLX LM is simpler to set up (medium difficulty). Choose based on the comparison table above and your own setup.
Are MLX LM and Petals free and open-source?
Yes. MLX LM is licensed under MIT and Petals under MIT. Both can be self-hosted at no software cost.
Can I run MLX LM and Petals with Docker?
MLX LM: check the project docs for container support. Petals: yes.