mlx

MLX is Apple's own machine learning framework, built specifically to take advantage of Apple Silicon — the chips in modern Macs, iPhones, and iPads (M1, M2, M3, M4 series). It lets AI researchers and developers train and run machine learning models directly on Apple hardware with maximum efficiency.

The key advantage is Apple Silicon's "unified memory" architecture, where the CPU (the main processor) and GPU (the graphics chip used for AI computations) share the same memory pool. Most AI frameworks on other hardware have to constantly copy data between separate CPU and GPU memory, which wastes time. MLX eliminates this bottleneck entirely.

MLX is designed for researchers who already know Python and are familiar with common AI frameworks like NumPy or PyTorch — it deliberately mimics their style so the learning curve is minimal. You can use it to train language models (like the AI behind ChatGPT), generate images with Stable Diffusion, run speech recognition with Whisper, or fine-tune existing large AI models on your own data.

For Mac-based developers and researchers, this means you can run and experiment with sophisticated AI models — including large language models — locally on your MacBook or Mac Studio without needing expensive cloud GPU services or a separate Linux machine with Nvidia graphics cards. This has made MLX popular for running open-source AI models like LLaMA locally.

MLX is free, open source, and created by Apple's machine learning research team. Installation is a single pip command on macOS. It also has limited Linux support.