MLX vs GGUF for Local LLMs on Mac: Speed, Compatibility, and When It Matters

Developers running large language models locally on Apple Silicon Macs must choose between two options: GGUF, a portable single-file format that runs across Mac, Linux, Windows, CPU, and CUDA, and MLX, Apple's native array framework that delivers roughly 15–40% faster inference and about 10% lower memory usage on M-series chips. MLX is not a file format but a runtime that reads a directory of safetensors files and is strictly limited to Apple Silicon hardware. At the 4-bit quantization level, GGUF's Q4_K_M mixed-precision approach can preserve model output quality slightly better than a comparable MLX quantization, a difference that becomes noticeable on memory-constrained machines. Tools like LM Studio support both formats, while Ollama's MLX backend, introduced in its 0.19 preview, currently targets machines with 32GB or more of unified memory, leaving 16GB users on the GGUF path. The practical guidance is straightforward: choose MLX for maximum speed on a personal Mac with no portability requirements, and choose GGUF for any setup that may need to run on other platforms or outlast a single runtime environment.