PyTorch and MLX for Apple Silicon

A side-by-side CNN implementation and comparison

A few months ago, Apple quietly released the first public version of its MLX framework, which fills a space in between PyTorch, NumPy and Jax, but optimized for Apple Silicon. Much like those libraries, MLX is a Python-fronted API whose underlying operations are largely implemented in C++.

Below are some observations of the similarities and differences between MLX and PyTorch. I implemented a bespoke convolutional neural network …

api apple apple silicon cnn convolutional-network framework images implementation jax libraries machine learning mlx numpy operations public python pytorch silicon space