Compiles HuggingFace transformer models into optimised native Metal inference binaries. No runtime framework, no Python — just a compiled binary that runs your model at near-hardware-limit speed on Apple Silicon, using 25% less GPU power and 1.7x better energy efficiency than mlx-lm UNC is 1.35x faster while using 25% less GPU power, resulting in 1.7x better energy efficiency. 8.4x fewer CPU instructions means less heat, less power, and more headroom for the GPU than MLX for Apple.