That makes sense. The title initially sounded like a general llama.cpp speedup on Apple Silicon, but if the improvement comes from fixing kernel selection inside Virtualization.framework VMs, that distinction is pretty important.
What I don't get, which this article doesn't talk about, why would Apple’s Virtualization.framework expose a lesser Metal profile instead of reporting all capabilities supported by the host GPU?
All this work to get the Mac to be a platform useful for AI is being done despite Apple's efforts. They're famously pissed at Nvidia since the Nvidia + Intel Macs due to heat and other issues. But then the OS is a bit closed off and they move slow and are more focused on milking iOS and the App Store and services for money BUT the PA-Semi purchase and Apple Silicon and everything following it has made the hardware just so amazing and useful that despite all that people build for it.
I love the platform. I'm happy to see people building on it.
AND! if we ever get an M7 chip with the rumored 1.5TB of available ram all this work will not have been in vain. You think the ai acceleration is nice in the M5 wait till M7 and M8.
Related: does anyone have a basis for guessing whether the Neural Accelerators found in M5 Pro+ (accessed by Metal 4) will make their way into the M6 base processors?
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[ 3.1 ms ] story [ 44.9 ms ] threadSo this was the comparison, for me the title was a bit confusing
The fix here works around a problem where the VM was causing llama.cpp to select the wrong kernels.
I wonder if their work is related?
I love the platform. I'm happy to see people building on it.
AND! if we ever get an M7 chip with the rumored 1.5TB of available ram all this work will not have been in vain. You think the ai acceleration is nice in the M5 wait till M7 and M8.