MLX
opensource.apple.com
Spec sheet
- Purpose
- MLX is an array framework designed for efficient and flexible machine learning research on Apple silicon.Read 8 Oct 2026 · opensource.apple.com
- License
- The GitHub repository lists an MIT license.Read 8 Oct 2026 · github.com
- Founded
- 2023Read 28 Sep 2026 · opensource.apple.com
- Examples
- The project’s examples include transformer training, LLaMA text generation and LoRA fine-tuning, Stable Diffusion image generation, and Whisper speech recognition.Read 8 Oct 2026 · github.com
- Function transformations
- MLX supports transformations for automatic differentiation and graph optimization.Read 8 Oct 2026 · opensource.apple.com
- Higher-level packages
- The framework includes neural network and optimizer packages for building more complex machine learning models.Read 8 Oct 2026 · opensource.apple.com
- Installation
- The project README gives macOS installation through pip and Linux installation options for CUDA or CPU-only packages.Read 8 Oct 2026 · github.com
- Language bindings
- MLX has Swift, C++, and C bindings, alongside its Python API.Read 8 Oct 2026 · opensource.apple.com
- NumPy-like API
- MLX provides a NumPy-like API intended to be familiar and flexible.Read 8 Oct 2026 · opensource.apple.com
- Support and documentation
- The project links to documentation, quick-start guidance, examples, and contribution guidelines.Read 8 Oct 2026 · github.com
- Supported devices
- Operations can run on CPU or GPU devices supported by MLX.Read 8 Oct 2026 · github.com
- Target users
- MLX is designed by machine learning researchers for machine learning researchers and is intended to support training and deploying models.Read 8 Oct 2026 · github.com
- Unified memory
- MLX is optimized for Apple silicon’s unified memory architecture.Read 8 Oct 2026 · opensource.apple.com
Plans and prices
MLX Free Open-source array framework for machine learning on Apple silicon Read 8 Oct 2026 · opensource.apple.com
Where Specifiction places it
- Deep Learning Software#17 of 357.6