They don't need to catch up. They just need to be good enough and fast as fuck. Vast majority of useful tasks of LLMs has nothing to do with how smart they are.

GPT-5 models have been the most useless models out of any model released this year despite being SOTA, and it because it slow as fuck.

> their main trick for model improvement is distilling the SOTA models

Could you elaborate? How is this done and what does this mean?

Too bad, so sad for the Mister Krabs secret recipe-pilled labs. Shy of something fundamental changing, it will always be possible to make a distillation that is 98% as good as a frontier model for ~1% of the cost of training the SOTA model. Some technology just wants to be free :)

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