OK that's a fair observation. Honestly my naive guess would be that they simply do not optimize mainline gpt models for the kind of use case you generally have on Api (tool use, multi-step actions, etc...). They need it to be a perky every day assistant not necessarily a reliable worker. Already on gpt-4 i found it extremely mediocre compared to the Claude models of the same time.

I think that's a more likely explanation than model collapse which is a really drastic phenomenon. A collapsed model will not just fail tasks at a higher rate, it will spit garbled text and go completely off the rails, which would be way more noticeable. It would also be weird that Claude models keep getting better and better while they're probably fed roughly the same diet of synthetic data.