One trick is to simply as for a fast answer when talking to a high effort model, when working interactively. Sounds stupid but I do this all the time and it works. Just tell it you are working interactively now and need ultrafast answers with no thinking.

I would be really curious to know as well, why effort is linked to cache as its quite inconveniant. Is it possible the token used to indicate effort is only passed once at the start, not per thinking trace, or quite simply that different efforts have different model weights?

I’m guessing that there’s a system prompt at the top telling the model about its reasoning budget. So when you switch reasoning effort it busts the cache.