MLX

MLX is Apple's machine learning framework built specifically for Apple Silicon. It uses the unified memory architecture (where CPU and GPU share the same RAM) so there's no copying data back and forth like you'd do with CUDA on NVIDIA GPUs.

This matters because most ML frameworks were built for NVIDIA hardware. Running PyTorch on a Mac works but doesn't fully exploit what Apple Silicon can do. MLX does. The API is intentionally similar to NumPy and PyTorch, so the learning curve is gentle if you know those.

MIT, backed by Apple's ML research team. Growing fast and gaining serious traction.

The catch: Mac-only. If your production environment is Linux with NVIDIA GPUs, MLX doesn't help you there. It's best for local development, experimentation, and running models on Mac hardware. The ecosystem of pre-built models and integrations is growing but still much smaller than PyTorch/CUDA.