MLX
An array framework for machine learning on Apple silicon with unified memory and dynamic graph construction.
What is MLX?
MLX is an array framework for machine learning on Apple silicon, developed by Apple's machine learning research team. It provides efficient tools for training and deploying models with a unified memory model and dynamic graph construction. The framework offers familiar APIs similar to NumPy and PyTorch, making it accessible for researchers and developers.
Machine learning researchers and developers working on Apple silicon who need efficient, flexible tools for model training and deployment with seamless multi-device support.
MLX offers a unified memory model that eliminates data transfers between devices, dynamic graph construction for flexibility, and APIs that mirror popular frameworks like NumPy and PyTorch, all optimized for Apple silicon performance.
Overview
MLX: An array framework for Apple silicon
Use Cases
Best For
- Training transformer language models on Apple silicon
- Large-scale text generation with models like LLaMA
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