They test it on launch day, then benchmark it against that. A deviation of above 10% is considered a change. They're currently tracking Opus 5.5 and GPT-6 Astra.
This bench famously detected a degradation of Opus 4.6 which Anthropic later blogged about. I personally think people sense nerfs more often than they happen and that it's often about honeymoon effects.
Used to work on a chat app where we had full control of the stack from the GPUs to the chat interface and everything in between. We were a small team too so I could be pretty confident that nothing changed in the stack and we still regularly had users complain that this or that model got nerfed. Perceived performance is actual performance over expectations and the latter just keeps increasing over time.
It doesn’t mean the big labs don’t also nerf models! But if they didn’t you’d still have users complaining.
This reminds me of the fact that true random does not feel random to users due to the clumpiness that the average person does not anticipate existing in true random.
e.g. The original apple shuffle and the Risk app ins which a string of songs from the same album or three one roles are "not random"
I've been working on a game that has dice rolling and even knowing about this effect, I started going crazy yesterday when I had a long streak of numbers, like 1-20, it was 15-16 like 9 times out of 10. I was sure there was some kind of bug in how it was initializing random, or saving the number, etc etc. Just could not find it. Streak continued to another roll, another roll... still couldn't find it. Then the streak just broke. Apparently just random being random.
> I've been working on a game that has dice rolling and even knowing about this effect, I started going crazy yesterday when I had a long streak of numbers, like 1-20, it was 15-16 like 9 times out of 10. I was sure there was some kind of bug in how it was initializing random, or saving the number, etc etc
Been through that this week as well with 100% success on 40% odds over multiple iterations on my game.. I tend to not dig into random but just rather ensure it works 'as closely to intended' as possible..
jug · · focus · HN ↗
<a href="https://www.bridgebench.ai/nerf-bench" rel="nofollow">https://www.bridgebench.ai/nerf-bench
They test it on launch day, then benchmark it against that. A deviation of above 10% is considered a change. They're currently tracking Opus 5.5 and GPT-6 Astra.
This bench famously detected a degradation of Opus 4.6 which Anthropic later blogged about. I personally think people sense nerfs more often than they happen and that it's often about honeymoon effects.
nsarrazin · · focus · HN ↗
It doesn’t mean the big labs don’t also nerf models! But if they didn’t you’d still have users complaining.
goodmythical · · focus · HN ↗
e.g. The original apple shuffle and the Risk app ins which a string of songs from the same album or three one roles are "not random"
svachalek · · focus · HN ↗
x______________ · · focus · HN ↗
Been through that this week as well with 100% success on 40% odds over multiple iterations on my game.. I tend to not dig into random but just rather ensure it works 'as closely to intended' as possible..