Just anecdotal experience, but this model seems more eager to write tests, create test scripts and call various tools than the previous one. Of course this results in more roundtrips and overall more tokens used and more money for the provider.
I had to stop the model going crazy with unnecessary tests several times, which isn't something I had to do previously. Can be fixed with a prompt but can't help but wonder if some providers explicitly train their models to be overly verbose.
Eagerness to tool call is an interesting observation. Certainly an MCP ecosystem would require a tool biased model.
However, after having pretty deep experience with writing book (or novella) length system prompts, what you mentioned doesn’t feel like a “regime change” in model behavior. I.e it could do those things because its been asked to do those things.
The numbers presented in this paper were almost certainly after extensive system prompt ablations, and the fact that we’re within a tenth of a percent difference in some cases indicates less fundamental changes.
>I had to stop the model going crazy with unnecessary tests several times, which isn't something I had to do previously
When I was playing with this last night, I found that it worked better to let it write all the tests it wanted and then get it to revert the least important ones once the feature is finished. It actually seems to know pretty well which tests are worth keeping and which aren't.
(This was all claude 4 sonnet, I've barely tried opus yet)
I had to stop the model going crazy with unnecessary tests several times, which isn't something I had to do previously. Can be fixed with a prompt but can't help but wonder if some providers explicitly train their models to be overly verbose.