I find that a lot of the recent allegedly great open models are cranking their reasoning way further than I find reasonable for interactive use. I’m writing this while waiting for the new Deepseek V4 Flash to finish its task, which is taking way longer than the older version.

What gets reported is always the benchmark result, but rarely the real-world trade-off made to achieve it. That’s an obvious incentive for the labs, so I think Simon is correctly zeroing in on it. Please continue doing so for models that don’t go too far as much as this release.

Don’t get me wrong, I think it’s amazing what we can get out of smaller models with more reasoning, but we should be super aware how very much not-free it is.

This is a good opportunity to call out models that reason quickly: Meta’s Glimmer seems to be pretty token efficient so far, as do the GPT 5.6s.