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Comment by square_usual

4 days ago

Easy enough to explain: they're benchmaxxing. Fable is intelligent but not benchmaxxed. Opus is less intelligent but benchmaxxed.

That's a plausible explanation but I'm not seeing evidence for it.

I have a personal benchmark suite of 14 real, non-public tasks. Opus 5 and Fable tied on 10, Opus won on 3, and Fable won on 1. It's a really strong model.

  • This is an interesting idea, without giving away your benchmarks specifically what kind of stuff do you test? I might try to assemble something myself, it's so hard to determine model quality from the system card these days.

    • I have actually been planning to open source the framework. Only benchmarks I care about are the ones that look like real work I do. So it makes it easy to trawl your own repos looking for benchmark task candidates from real bug fixes or features. Then as a bonus I can compare the agent’s solution to my own as a reference.

      So most look like that but I did include a few one-shot “build an app that solves this problem” and some qualitative design tasks and a tough algorithmic optimization one.

      4 replies →

Honestly that's the simplest explanation and thus likely the correct one.

  • They don't have a track record of benchmaxxing. The simplest explanation is that the blog post lists the things this model is better than Fable at, but not the things it isn't.