Pipe Network(@pipenetwork):Run Kimi K3 on a Mac Studio 🫰 K3 is 2.8T parameters and 1.6TB on disk, which makes it impossible to run on Apple Silicon. Until now. Our MLX port is now open source: https://t.co/Iszg55hRZT To accomplish this, we solved two things: 1. We wrote a streaming converter that walks one layer at a time, so that mlx_lm doesn't need to materialize the whole model. 2. REAP pruning sits on top and scores all 896 experts against a calibration corpus to keep only ones your workload needs. That's what brings K3 down to 350GB and inside a Mac Studio.

2026.07.28 01:13

Run Kimi K3 on a Mac Studio 🫰 K3 is 2.8T parameters and 1.6TB on disk, which makes it impossible to run on Apple Silicon. Until now. Our MLX port is now open source: To accomplish this, we solved two things: 1. We wrote a streaming converter that walks one layer at a time, so that mlx_lm doesn't need to materialize the whole model. 2. REAP pruning sits on top and scores all 896 experts against a calibration corpus to keep only ones your workload needs. That's what brings K3 down to 350GB and inside a Mac Studio.