Apple literally mentioned local LLMs in the event video where they announced this phone and others.

Apple's privacy stance is to do as much as possible on the user's device and as little as possible in cloud. They have iCloud for storage to make inter-device synch easy, but even that is painful for them. They hate cloud. This is the direction they've had for some years now. It always makes me smile that so many commentators just can't understand it and insist that they're "so far behind" on AI.

All the recent academic literature suggests that LLM capability is beginning to plateau, and we don't have ideas on what to do next (and no, we can't ask the LLMs).

As you get more capable SLMs or LLMs, and the hardware gets better and better (who _really_ wants to be long on nVIDIA or Intel right now? Hmm?), people are going to find that they're "good enough" for a range of tasks, and Apple's customer demographic are going to be happy that's all happening on the device in their hand and not on a server [waves hands] "somewhere", in the cloud.

It's not difficult to find improvements to LLMs still.

Large issues: tokenizers exist, reasoning models are still next-token-prediction instead of having "internal thoughts", RL post-training destroys model calibration

Small issues: they're all trained to write Python instead of a good language, most of the benchmarks are bad, pretraining doesn't use document metadata (ie they have to learn from each document without being told the URL or that they're written by different people)