Comment by esskay
14 hours ago
Real world usage suggests otherwise. It's been a known trend for a while. Anthropic even confirmed as such ~6 months ago but said it was a "bug" - one that somehow just keeps happening 4-6 months after a model is released.
Real world usage is unlikely to give you the large sample sizes needed to reliably detect the differences between models. Standard error scales as the inverse square root of sample size, so even a difference as large as 10 percentage points would require hundreds of samples.
https://news.ycombinator.com/item?id=46810282 when they "detected" a statistically significant deviation, but that was because they used the first day's measurement as the baseline, so at some point they had enough samples to notice that this was significantly different from the long-term average. It seems like they have fixed this error by now.)
It's hard to trust public, high profile benchmarks because any change to a specific model (Opus 4.5 in this case) can be rejected if they have regressions on SWE-Bench-Pro, so everything that gets to be released would perform well in this benchmark
Any other benchmark at that sample size would have similarly huge error bars. Unless Anthropic makes a model that works 100% of the time or writes a bug that brings it all the way to zero, it's going to work sometimes and fail sometimes, and anyone who thinks they can spot small changes in how often it works without running an astonishingly large number of tests is fooling themselves with measurement noise.