Llama Stack vs MLX LM
A side-by-side comparison of two self-hosted self-hosted ai options — licensing, setup difficulty, resource needs, and what each one replaces.
| Feature | Llama Stack | MLX LM |
|---|---|---|
| Deploy effort | Under-an-hour setup | Read-the-docs project |
| Health score | 92 · Excellent | 89 · Excellent |
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | MIT |
| Language | Python | Python |
| Setup difficulty | Medium | Medium |
| Min. RAM | 4,096 MB | 16,384 MB |
| Deployment | docker, source | source, binary |
| GitHub stars | ★ 8,437 | ★ 7,117 |
| First released | 2024 | 2024 |
| Replaces | OpenAI API | OpenAI API |
What are Llama Stack and MLX LM?
Llama Stack
Llama Stack from Meta defines and implements a set of standardized APIs for inference, RAG, agents, safety and evaluation, with multiple provider backends. It can be self-hosted as a unified server for building local generative AI applications.
- Standardized AI APIs
- Pluggable provider backends
- Agents and RAG support
- Self-hostable server
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
Llama Stack vs MLX LM: key differences
Both projects are written in Python. Llama Stack is the lighter option, starting around 4,096 MB of RAM against 16,384 MB for MLX LM. Llama Stack lists first-class Docker deployment; MLX LM does not.
Why pick each one
Choose Llama Stack if…
- Released under the MIT license
- First-class Docker support for quick deployment
- Mature project with 8.4k GitHub stars
- Written in Python
Choose MLX LM if…
- Released under the MIT license
- Mature project with 7.1k GitHub stars
- Written in Python
Frequently asked questions
Is Llama Stack or MLX LM better?
Neither is universally better. Llama Stack has the larger community; both share a medium setup difficulty, so the decision comes down to features and licensing.
Are Llama Stack and MLX LM free and open-source?
Yes. Llama Stack is licensed under MIT and MLX LM under MIT. Both can be self-hosted at no software cost.
Can I run Llama Stack and MLX LM with Docker?
Llama Stack: yes. MLX LM: check the project docs for container support.
Which is lighter on resources, Llama Stack or MLX LM?
Llama Stack has the smaller minimum footprint at 4,096 MB of RAM, compared to about 16,384 MB for MLX LM. Real-world usage depends on library size, user count, and enabled features.