If you run local models on a Mac, you eventually hit the same fork in the road: the same model is available as a GGUF file and as an MLX version, and something has to tell you which one to download. The short answer is that MLX is faster on Apple Silicon and GGUF goes everywhere. The useful answer is knowing when that trade actually matters, because for a lot of setups it does not.
Here is the practical version, with the reasons.
What the two formats actually are
GGUF is a single self-contained file. Weights, tokenizer, metadata, and quantization parameters are all bundled into one portable blob that llama.cpp (and everything built on it) can load anywhere: Mac, Linux, Windows, CPU, CUDA, Metal. That portability is the whole point of the format.
MLX is Apple's array framework, not a file. An MLX model is a directory of safetensors files plus a config that the MLX runtime reads directly. It is built to run on Apple Silicon and quantize natively against the unified memory pool. It does not leave Apple Silicon, full stop.
