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Apple Silicon ML framework
MLX (Apple)
Apple's open-source array framework for machine learning on Apple Silicon.
Official siteAxes (0–100)
- Local control / custody90
- Open stack (models & tooling)82
- Regulatory posture (curated)50
- Interoperability45
Last reviewed: 2026-04-10
Facts (curated)
- Focus
- NumPy-like array framework with Python, C++, and Swift APIs. Optimized for Apple Silicon unified memory and Neural Accelerators.
- Ecosystem
- mlx-lm for LLM inference/fine-tuning. Powers Ollama's new MLX backend. Experimental CUDA support for Linux.
- Backing
- Apple Machine Learning Research. MIT licensed. 25k GitHub stars.
Pros
Best-in-class performance on Apple Silicon. Up to 4x TTFT speedup on M5 with Neural Accelerators.
Cons / risks
Apple Silicon only for production use. Not a general-purpose cross-platform runtime — use llama.cpp or Ollama for that.
Related links
- vLLM Metal plugin — Apple Silicon via MLX
GitHub · 2026-04-06
- Ollama is now powered by MLX on Apple Silicon (preview)
Ollama Blog · 2026-03-30
- MLX — array framework for Apple Silicon
GitHub · 2026-03-12
- Exploring LLMs with MLX and Neural Accelerators on M5
Apple ML Research · 2025-11-19