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.

I made a graphic to explain why people feel like the models get nerfed:

https://x.com/thesilenceturns/status/2103551351825543610

The idea is that new models can handle up to a certain level of complexity, at which point they fall apart. Every new model can handle more complexity, so there's a wonderful time upon release when you feel like you can do anything, only for you to hit the complexity ceiling a few days later when you saturate it. Rinse and repeat for the next model.

The quality of the output/work seems the same, but the speed at which it gets stuff done is a lot slower, because it's asking for permission so much more

I don't have any numbers/stats, just my impression. However, I imagine that if Anthropic could make the models ask for permission more often, it could be an interesting way to throttle access, without degrading quality of the output

After Fable launch I switched over to Codex and it was simply amazing, with frequent usage resets that seemed never ending. They clearly had more compute than they knew what to do with. Post Astra, Codex has gotten dumb again across all models, increased usage for no real reason, and no resets.

I'm guessing Opus 5.5 will take the heat off Codex for a bit, leading to better performance. So I guess I stick around here instead of switching again?

Yesterday I fought claude fable to not just jump to make changes like a dog following a treat, that we were researching... at some point I introduced the word HAWAI... and only if I say HAWAI the thing can start making changes..

I was going to post here in HN just to have a "I knew this was the reason" when they release fable > 5.1

I had the exact same feeling every time they have a new big release

The current period is as pro-customer as we're ever going to get, with cash still flying around and neither OpenAI nor Anthropic on the public market, and people are already forced into this sort of business to keep them true to their word. The point isn't even whether they're nerfing the models (I don't think they are), but that people can't seem to trust them to do right.

Truly, madly, deeply sloppy.

Open models are the endgame.

Anthropic has admitted to nerfing in the past. There have also been inference bugs. On top of that, model performance changes as they move compute to schwaggier providers as well.

Your chart is wrong.

Btw, you have a typo in the twitter handle on your profile (not in your comment), 'thesilencesturns'.

My work at my job has stayed the same. But the model quality has varied.

They definitely tune the models in production after launch, if not only to share load during high traffic times. It’s not a crazy conspiracy that the same model can be stupider at different times.

What Anthropic presents as Opus 5.5 isn't actually a single model...it's Anthropic's ecosystem as a whole. If you are lucky, you get the top model handling your issues all the time, however, that never happens. What really happens is that your request and content are graded along with your subscription (example: API? subscription, if so, what tier? how much has the user used it? Do we trust the user? how much? how much are they paying? are they asking something we think is dangerous?) and your request and context are routed accordingly.

Anthropic isn't alone in this behavior, Open AI does it as well, just look at the respective subreddits on reddit for both if you need some examples, or just play around with the various models from both companies.

There are a few folks who've done some analysis on this (their findings were posted on reddit and X), and a bigger multi-national study is apparently coming, though I admittedly don't know their findings.

I guess the tl;dr is that Anthropic and Open AI are actually selling you "best-effort" routers, so you may or may not get the best in class model, and only they get to determine if you do or do not. No guarantees.

By the way, dont for a second think LLM hourly limits are all about revenue, they're playing into this psychology. They hire literal gambling UX designers, they want to turn you all into addicts. They want to make you reliant.

Want to run your llm like a slot machine? They'll let you do that spin the generation on a multiple, get 6x results, pick your favorite. Feel that high.

Just know you can get that same hit of dopamine by fostering your own intelligence and creating something with it. Token dealers are just selling you the shortcut, straight to the reward, short circuiting the the natural process.

Bad times ahead for many. This shit isnt good for your brain. And you all know the truth, you just wont admit it. Its doing damage, making you lazier, less intelligent.. Making you an addict.

My local models don't display that degradation, sensed or measured. They consistently perform equally to what I expect of them, precisely because they don't change.

How does twitter explain that? Is my internal model for expectation of capacity magically not drifting for local models but somehow is for anthropic api call based models?