[MediaSquirrel]

Our app wasn't running on CPU or GPU –– the actual software we built was running entirely on Apple Neural Engine and it was crazy fast because we designed the architecture explicitly to run that specific chip.

We were just calling the iPhone's built-in face tracking system via the Vision Framework to animate the avatars. That's the thing that was running on GPU.

[llm_nerd]

Okay, though I'm not sure what that has to do with my comment. I understood that from the post: you were concurrently maxing out multiple parts of the SoC and it was overheating as they all contributed to the thermal load. This isn't new or novel -- benchmarks that saturate both the CPU and GPU are legendary for throttling -- though the claim that somehow normal thermal management didn't protect the hardware is novel, albeit entirely unsubstantiated.

That is neither here nor there on CoreML -- which also uses the CPU, GPU, and ANE, and sometimes a combination of all of them -- or the weird thing about MLX.

[MediaSquirrel]

I don't get what's so weird about MLX. Apple's focus is obviously on MLX / Metal going forward.

The only reason to use CoreML these days is to tap into the Neural Engine. When building for CoreML, if one layer of your model isn't compatible with the Neural Engine, it all falls back to the CPU. Ergot, CoreML is the only way to access the ANE, but it's a buggy all-or-nothing gambit.

Have you ever actually shipped a CoreML model or tried to use the ANE?