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iPhone 17 Pro Demonstrated Running a 400B LLM

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Re: iPhone 17 Pro Demonstrated Running a 400B LLM

#6

A year ago this would have been considered impossible. The hardware is moving faster than anyone's software assumptions.

This isn't a hardware feat, this is a software triumph.

They didn't make special purpose hardware to run a model. They crafted a large model so that it could run on consumer hardware (a phone).

Re: iPhone 17 Pro Demonstrated Running a 400B LLM

#7
post #2

[flagged]

This has nothing to do with Apple, and everything to do with MoE and that everyone forgot you can re-read the necessary bits of the model from disk for each token.

This is extremely inefficient though. For efficiency you need to batch many requests (like 32+, probably more like 128+), and when you do that with MoE you lose the advantage of only having to read a subset of the model during a single forward pass, so the trick does not work.

But this did remind me that with dense models you might be able to use disk to achieve high throughput at high latency on GPUs that don't have a lot of VRAM.

Re: iPhone 17 Pro Demonstrated Running a 400B LLM

#10

> SSD streaming to GPU Is this solution based on what Apple describes in their 2023 paper 'LLM in a flash' [1]? 1: https://arxiv.org/abs/2312.11514

Yes. I collected some details here: https://simonwillison.net/2026/Mar/18/llm-in-a-flash/
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