infrastructure

MLX

Apple Machine Learning eXchange

Apple's ML framework built for Apple Silicon unified memory

Reading level

PRACTITIONER — Technical context

MLX is Apple's open-source array computation framework (like NumPy/JAX) designed for Apple Silicon's unified memory architecture. Key features: lazy evaluation, zero-copy memory sharing between CPU and GPU (no memcpy), unified device abstraction, and automatic differentiation. mlx-lm provides LLM-specific optimizations including Metal kernel fusion for attention and KV cache management.

Real-world example

`mlx_lm.generate --model mlx-community/Llama-3.1-70B-Instruct-4bit --prompt 'Explain neural networks'` — this runs Llama 70B at ~18 tokens/sec on an M4 Max with 128GB RAM using Metal GPU acceleration.

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