Rui CarmoA collection of tools, frameworks, and models built on or optimized for Apple’s MLX array framework and the Neural Engine (ANE) on Apple Silicon. MLX is Apple’s answer to PyTorch/JAX for the M-series chip, with lazy evaluation, unified memory, and first-class Python bindings.
Resources
| Field | Category | Date | Link | Notes |
|---|---|---|---|---|
| Audio | Libraries | 2026 | mlx-audio | TTS, STT and speech-to-speech library built on Apple’s MLX for Apple Silicon. |
| Models | mlx-audiocraft | MLX port of Meta’s AudioCraft for Apple Silicon — music and audio generation via MusicGen and AudioGen |
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| Frameworks | Core | 2023 | MLX | An array framework for Apple Silicon — the foundation for all MLX-based tools |
| Examples | mlx-examples | Official Apple MLX examples covering LLMs, image generation, speech, and more |
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| Inference | Libraries | ml-ane-transformers | Apple’s Transformers library optimized for the Neural Engine |
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| Python Bindings for Apple Intelligence | Python bindings to Apple’s on-device foundation models |
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| Research | Tools | 2026 | autoresearch-ANE | Autonomous Apple Silicon LLM research suite combining ANE, MLX, and legacy MPS training paths |