MLX LM vs screenshot-to-code
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
screenshot-to-code
Convert screenshots and designs into working code
| Feature | MLX LM | screenshot-to-code |
|---|---|---|
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | MIT |
| Language | Python | Python |
| Setup difficulty | Medium | Easy |
| Min. RAM | 16,384 MB | 1,024 MB |
| Deployment | source, binary | docker, bare-metal |
| GitHub stars | ★ 6,543 | ★ 73,884 |
| First released | 2024 | 2023 |
| Replaces | OpenAI API | Vercel v0 |
Why pick each one
Choose MLX LM if…
- Released under the MIT license
- Mature project with 6.5k GitHub stars
- Written in Python
Choose screenshot-to-code if…
- Released under the MIT license
- Easy to set up — beginner-friendly
- First-class Docker support for quick deployment
- Mature project with 73.9k GitHub stars
Frequently asked questions
Is MLX LM or screenshot-to-code better?
screenshot-to-code is the stronger all-round pick: it has both the larger community and the simpler easy setup. Consider MLX LM if its specific feature set fits your needs better.
Are MLX LM and screenshot-to-code free and open-source?
Yes. MLX LM is licensed under MIT and screenshot-to-code under MIT. Both can be self-hosted at no software cost.
Can I run MLX LM and screenshot-to-code with Docker?
MLX LM: check the project docs for container support. screenshot-to-code: yes.