My iPhone 16 Pro Max produces garbage output when running MLX LLMs

Yes, "floating point accumulation doesn't commute" is a mantra everyone should have in their head, and when I first read this article, I was jumping at the bit to dismiss it out of hand for that reason.

But, what got me about this is that:

* every other Apple device delivered the same results

* Apple's own LLM silently failed on this device

to me that behavior suggests an unexpected failure rather than a fundamental issue; it seems Bad (TM) that Apple would ship devices where their own LLM didn't work.

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> Or, rather, MiniMax is! The good thing about offloading your work to an LLM is that you can blame it for your shortcomings. Time to get my hands dirty and do it myself, typing code on my keyboard, like the ancient Mayan and Aztec programmers probably did.

They noticed a discrepancy, then went back and wrote code to perform the same operations by hand, without the use of an LLM at all in the code production step. The results still diverged unpredictably from the baseline.

Normally, expecting floating-point MAC operations to produce deterministic results on modern hardware is a fool's errand; they usually operate asynchronously and so the non-commutative properties of floating-point addition rear their head and you get some divergence.

But an order of magnitude difference plus Apple's own LLM not working on this device suggests strongly to me that there is something wrong. Whether it's the silicon or the software would demand more investigation, but this is a well reasoned bug in my book.

My TL;DR is that they tried to run an on-device model to classify expenses, it didn't work even for simple cases ("Kasai Kitchin" -> "unknown"), they went deeeeeep down the rabbit hole to figure out why and concluded that inference on their particular model/phone is borked at the hardware level.

Whether you should do this on device is another story entirely.