I doubt there is a comparable correctness metric between LLMs and protein structure prediction models.

You can measure how many times they correctly predict a thing, but results will greatly change according to what your objective is. Those are only comparable when you're trying to predict the same thing.

As such my reply would be: sometimes more incorrect sometimes more correct. However, in general, a mishandled incorrect protein structure prediction is way more expensive than an LLM hallucination.

I mean... machine learning extends far beyond the stupid lying machines, and can produce far more trustworthy results than the dipshits at "Open" AI, but results will still always require validation, as all results require a lot of validation in science before they should be trusted.