Hard disagree. Opus reports to me like a student. Fable reported to me like a colleague (researcher). It genuinely seemed to pick up on nuance that the other models just don't, even when I tell them explicitly. It's been really frustrating that neither Codex nor Opus can make targetted edits to Fable's code without screwing something subtle up. For context, this is for computational geometry work, so your mileage may vary.

I found Fable to be both more intelligent and much better at pursuing complex goals than any previous model. I was impressed enough that I wrote up my experience – it's a little unusual because it was on open source code, so I could post the full session transcript and commits, if people want to judge for themselves https://tossrock.substack.com/p/36-hours-with-fable

You might have found a use case on which both have same capabilities, but this is in general very not true. I’ve had Fable autonomously fix concurrency bugs by itself other models couldn’t even diagnose from logs.

Perhaps it is a lot of small improvements all over the place, but the sum is a step change in capability.

In LLMs, much like in humans, agency and misalignment are two sides of the same coin.