@twtayaan: The volunteers bringing Linux to Apple MacBooks are almost ready to ship it on the M3, with zero help from Apple. This …
Summary
Asahi Linux volunteers are nearly ready to release Linux support for Apple M3 chips after reverse-engineering components like webcam and USB, with plans for M4 already underway.
View Cached Full Text
Cached at: 08/29/26, 01:49 AM
The volunteers bringing Linux to Apple MacBooks are almost ready to ship it on the M3, with zero help from Apple.
This is Asahi Linux. A tiny team that has spent years reverse-engineering Apple Silicon from scratch.
And they are getting dangerously close.
Webcam support now works on M3. USB 3.0 and Thunderbolt work too. The team had to reverse-engineer Apple’s changing USB controller designs just to get there.
A full M3 release is expected in the coming weeks. And they’re already working on M4.
The funny part? Apple never opened a single door for them.
Yet they kept picking the locks anyway.
Similar Articles
We Rebuilt the Linux MicroVM Stack on Apple Silicon
Encore has rebuilt the Linux microVM stack on Apple Silicon, optimizing virtualization for Apple's M1 and M2 processors.
Dissectingthe Apple M1 GPU, the end
The article concludes the series on reverse-engineering the Apple M1 GPU, detailing the development of open-source drivers that now provide full graphics acceleration on Linux for M1 and M2 Macs.
@0x0SojalSec: Apple hid 15.8 TFLOPS of raw AI power in every M4 Mac & iPhone. They only let you use the Neural Engine for inference. …
A developer reverse-engineered Apple's private APIs to enable training neural networks directly on the Apple Neural Engine (ANE) in M4 Macs and iPhones, bypassing CoreML and GPU. The project demonstrates that ANE hardware is capable of training, though with limitations like low utilization and CPU fallbacks for some operations.
@sitinme: There's a pretty interesting open-source project called Cider, specifically designed to accelerate local AI inference on Macs with Apple Silicon chips. Many people buy a Mac mini or MacBook Pro and want to run models locally, but often encounter issues like insufficient speed and high memory usage. Actually...
Cider is an open-source project designed for Apple Silicon Macs, accelerating local AI inference by fully leveraging the computing power of M-series chips. It is compatible with the MLX ecosystem, supports models like Qwen and Llama, and is easy to install.
@Youssofal_: MTPLX V0.3 Is Out!: - I realised M1 & M2 macs do not support BF16 and were emulating it leading to significantly decrea…
MTPLX v0.3 is released, a native runtime for Apple Silicon that uses Multi-Token Prediction (MTP) to double decode speed while maintaining distributional accuracy via Leviathan-Chen acceptance.