ExLlama 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 | ExLlama | MLX LM |
|---|---|---|
| Deploy effort | Read-the-docs project | Read-the-docs project |
| Health score | 23 · At risk | 89 · Excellent |
| Category | Self-Hosted AI | Self-Hosted AI |
| License | MIT | MIT |
| Language | Python | Python |
| Setup difficulty | Hard | Medium |
| Min. RAM | 8,192 MB | 16,384 MB |
| Deployment | source | source, binary |
| GitHub stars | ★ 2,946 | ★ 7,117 |
| First released | 2023 | 2024 |
| Replaces | OpenAI API | OpenAI API |
What are ExLlama and MLX LM?
ExLlama
ExLlama is a standalone Python/C++/CUDA implementation for running quantized GPTQ Llama models with low VRAM use on modern GPUs. It is the predecessor to ExLlamaV2 and focuses on fast, memory-efficient local inference.
- Low VRAM GPTQ inference
- CUDA-accelerated
- Standalone library
- Fast token generation
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
ExLlama vs MLX LM: key differences
Both projects are written in Python. ExLlama is the lighter option, starting around 8,192 MB of RAM against 16,384 MB for MLX LM. MLX LM has the considerably larger community, at 7,117 GitHub stars versus 2,946.
Why pick each one
Choose ExLlama if…
- Released under the MIT license
- Active community (2.9k 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 ExLlama or MLX LM better?
MLX LM is the stronger all-round pick: it has both the larger community and the simpler medium setup. Consider ExLlama if its specific feature set fits your needs better.
Are ExLlama and MLX LM free and open-source?
Yes. ExLlama is licensed under MIT and MLX LM under MIT. Both can be self-hosted at no software cost.
Can I run ExLlama and MLX LM with Docker?
ExLlama: check the project docs for container support. MLX LM: check the project docs for container support.
Which is lighter on resources, ExLlama or MLX LM?
ExLlama 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.