MLX LM vs openedai-speech
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 | openedai-speech |
|---|---|---|
| Deploy effort | Read-the-docs project | Under-an-hour setup |
| Health score | 89 · Excellent | 13 · At risk |
| Status | Actively maintained | Archived |
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | AGPL-3.0 |
| Language | Python | Python |
| Setup difficulty | Medium | Easy |
| Min. RAM | 16,384 MB | 2,048 MB |
| Deployment | source, binary | docker |
| GitHub stars | ★ 7,117 | ★ 857 |
| First released | 2024 | 2024 |
| Replaces | OpenAI API | OpenAI API, ElevenLabs |
What are MLX LM and openedai-speech?
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
openedai-speech
openedai-speech is a self-hosted text-to-speech server that mimics the OpenAI audio speech API. It uses local models such as Piper and Coqui XTTS to generate audio without sending data to the cloud.
- OpenAI speech API compatible
- Piper and XTTS backends
- Custom voice mapping
- Drop-in replacement
MLX LM vs openedai-speech: key differences
The biggest difference is maintenance: openedai-speech's repository is archived and no longer developed, while MLX LM is actively maintained. Both projects are written in Python. Licensing differs — MIT for MLX LM versus AGPL-3.0 for openedai-speech. Openedai-speech is the lighter option, starting around 2,048 MB of RAM against 16,384 MB for MLX LM. MLX LM has the considerably larger community, at 7,117 GitHub stars versus 857. Openedai-speech 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 openedai-speech if…
- Released under the AGPL-3.0 license
- Easy to set up — beginner-friendly
- First-class Docker support for quick deployment
- Written in Python
Frequently asked questions
Is MLX LM or openedai-speech better?
Neither is universally better. MLX LM has the larger community, while openedai-speech is simpler to set up (easy difficulty). Choose based on the comparison table above and your own setup.
Are MLX LM and openedai-speech free and open-source?
Yes. MLX LM is licensed under MIT and openedai-speech under AGPL-3.0. Both can be self-hosted at no software cost.
Can I run MLX LM and openedai-speech with Docker?
MLX LM: check the project docs for container support. openedai-speech: yes.
Which is lighter on resources, MLX LM or openedai-speech?
openedai-speech has the smaller minimum footprint at 2,048 MB of RAM, compared to about 16,384 MB for MLX LM. Real-world usage depends on library size, user count, and enabled features.