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design

omlx: Fast LLM Inference

Get fast LLM inference with omlx, ideal for founders working on Apple Silicon projects.
17,675 stars1,486 forksPythonQuality 8/10Updated 7/9/2026100% free ยท open source
What it does

omlx provides fast LLM inference for Apple Silicon projects, enabling continuous batching and SSD caching for efficient machine learning model deployment

Install / run
git clone https://github.com/jundot/omlx.git && cd omlx
When to use it
  • โ€ขWhen building Apple Silicon-based applications that require low-latency LLM inference
  • โ€ขWhen developing macOS or iOS apps that rely on large language models
  • โ€ขWhen optimizing machine learning workflows for Apple devices
Quick start
  1. 1Run `python3 -m venv venv` to create a virtual environment
  2. 2Activate the environment with `source venv/bin/activate`
  3. 3Install the required packages using `pip install -r requirements.txt`
  4. 4Start the omlx server with `python app.py` and manage it from the macOS menu bar
  5. 5Configure the SSD caching by modifying the `config.json` file
Ready-to-paste prompt
python app.py --model gpt2 --batch-size 16 --ssd-cache /path/to/ssd
Heads up: Ensure you have Python 3.9 or later installed, as omlx relies on newer Python features for optimal performance
Saves to your device

Topics

apple-silicon
inference-server
llm
macos
mlx
openai-api
What's inside โ€” free to inspect
No purchase needed

Read the entire source before you build โ€” unlike paid marketplaces that hide it behind a buy button.

11
top-level files
8
folders
55.2M
repo size
Apache-2.0
license
Key files
README.fr.md
README.ja.md
README.ko.md
README.md
README.zh.md
File tree
.github/
apps/
docs/
Formula/
omlx/
packaging/
scripts/
tests/
.gitignore
LICENSE
mcp.example.json
pyproject.toml
pytest.ini
README.fr.md
README.ja.md
README.ko.md
README.md
README.zh.md
setup.py
Quick Actions
Details
Creator
jundot
Language
Python
Category
design
Published
2/13/2026

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