mlx

SKILL.md

MLX-LM is a Python package for running large language models on Apple Silicon, leveraging the MLX framework for optimized performance with unified memory architecture.

| Memory | Separate CPU/GPU copies | Unified memory, no copies | | Optimization | Generic Metal backend | Apple Silicon native | | Model loading | Slower, more memory | Lazy loading, efficient | | Quantization | Limited support | Built-in 4/8-bit |

MLX arrays live in shared memory, accessible by both CPU and GPU without data transfer overhead.

Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models via HTTP API. Source: itsmostafa/llm-engineering-skills.

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