Is it the models or the fact that earlier hallucinations are starting to spread, accumulate and contaminate training data?

Performance degradation over time has been a recognized concern for a while now.

Looks like latest chatGPT likes to hallucinate code segments that don't work or wrong API calls. Simpler instructions work fine, but at some point it starts to diverge and experiment.