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I at least didn't see this. I had a baseline evaluation from before Nov 3 on Opus 5.5 medium, so I re-ran it this morning.

Eval context: 30 bug fixes and features evaluated by tests the agent didn't see. Ran on Opus 5.5 at medium effort in Claude Code.

20 of the tasks were last run on Nov 1, twice each. Nov 1 solved 36/40, and today solved 19/20. Thinking tokens per task were 0.95x Nov 1’s and output tokens 0.97x. The one significant change was speed: median time to first token decreased from 3.0s to 1.7s.

Caveats: one run per task today, medium effort only.

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Personally, I've found myself getting lazier recently, trying to get a single session to handle tasks that should be broken into multiple sessions, etc. I've suspected claims of nerfing might come from changes in user behavior. I'm glad more disciplined checks are being run.
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User behavior is overwhelmingly the most likely reason, regardless of what the text above your reply says.
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It could be harness changes too, been quite unhappy with opus 5.5 the last few days and there have been a lot of harness updates.
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Why dont we have the website that checks performance every day anymore? It’s a quite simple thing to build and clarifies the question re: degradation.
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Who's paying for the tokens, and since all inputs and outputs are logged "for abuse and safety" what is stopping anthropic from identifying which account is running the daily tests once it gets popular, and A/Bing it into a different slot?
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This is an example of LLM text that doesn’t make sense.

Paragraph 1 says there were 30 bug fixes.

Paragraph 2 first says they tested it on 20 of the “tasks”. But why is the denominator 40? Where did that come from? It should be 30.

It goes on to mention another test, this time with 20 tasks. Again, it’s unclear where this is even coming from. Based on the first paragraph it should be 30 not 20.

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Sorry this was confusing -

There are 30 tasks in my eval total:

- 20 of them ran on Nov 1, twice each (so 40)

- I created 10 more tasks and ran them on Nov 5 (also ran them twice each)

- Today I ran all 30 tasks, once each, on Opus 5.5 to see if the performance decreased at all

- I only put the comparison against the original 20 in my post, since I saw in another post that people are claiming Opus was nerfed on November 3

This will all get less confusing when I make my benchmark public (hopefully this week).

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It stands as written? The previous test had 20 tasks run twice each, so denominator 40. The recent retest did the same 20 tasks but only once each, as mentioned in the caveat. The 30 is presumably either a typo or a separate count (like the test had 20 tasks related to code with 30 bugs/features).

Also - LLM text? If GP is confusing it's because it's overly succinct and might have typos, which are not exactly the hallmarks of LLM text.

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2 alternative interpretations to consider:

1. 30 was a typo, it should have been 20.

2. 30 was the full suite, but they only ran 20 of those 30 on Nov 1st and so ran the same corpus again for a fair comparison.

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I think it's confusing and incomplete, but not wrong. Paragraph 2 says the Nov 1 test included 20 of the tasks and ran each twice. That's the 40 denominator.

Why paragraph 1 even mentions the full set of 30 tasks if 10 of them are irrelevant to the comparison, I don't know.

I'm not sure if it's LLM text, or somebody who has been reading way too much LLM text and is now corrupted into mimicking it. My guess would be a mix of human and LLM. "...evaluated by tests the agent didn't see" sounds very Claude. The first line (2 sentences) sounds human to me. Everything after sounds AI, though the last line is ambiguous.

It's kind of sad how our meat brains are getting non-consensually trained on this categorization task....

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It’s impossible to say for sure. But I never saw anyone write “caveats:” at the end of their analysis. But LLMs do it all the time.
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If I read your results correct it solved 5% more problems and used up between 3-5% fewer tokens, with a faster response time?
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Correct. But the 5% more solves and 3-5% fewer tokens are within the noise of previous eval runs I've done on models. The faster response time is not.
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Someone using an actual statistical test to quantify if there's actual measurable improvement?! An angel among men.
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from my basic stats knowledge, it's not reliable to calculate the confidence interval of the sample proportion with fewer than about 10 samples on both sides. So if you're only seeing 1 or 2 failures in 20, and that approximately held as you scaled, you would have to run about 200 tests with each in order to get at least 10 failures in order to calculate the confidence intervals of the two samples and see if they overlap or not.
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And this is why not many people do this. Even if you have the decals and the statistical knowledge, it's pretty expensive to do this regularly.
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Uncertainty from count statistics are far larger than this. These are two perfectly consistent results there’s no statsig difference
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The spending limit definitely goes down much faster as of last week or so.
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I dunno there are some other nerf trackers that aren't showing a regression: https://github.com/ninjahawk/livenerf
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The problem is that it seems to be an A/B testing thing:

https://news.ycombinator.com/item?id=50422951

So only if you were "selected" for their experiments, your account was nerfed.

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For sure, myself and colleague saw this nerfing. He said - new model coming. It was incredibly obvious. I also started getting a lot of "How's Claude doing today" messages at the same time, which is presumably to get feedback on the A/B
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I always skip those. I know it doesn’t matter in the bigger scheme of things, but I don’t want to be classified as a “good feedback provider”.

I’m working on a task. And the task is never to evaluate the agent performance.

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And whenever you press a number, even 0, they keep your full conversation.
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Source?
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I strongly believe it will be shit like this that will have people abandon them. They're being way too cocky for a company that pretty much didn't exist 2 years ago
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But the claim here is "the models are nerfed before a release", not "they A/B test quants / efforts". If it were A/B testing, it doesn't really make sense to correlate it to release windows at all.
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The models are nerfed [for some people] before a release
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They might want to see how people react to a new model depending on whether they've been nerfed.

If the nerfing is lower effort (seems to be, presumably why they hide the CoT) then they may be wondering if they can get away permanently with lowering effort on the new release provided it gives a wee improvement.

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Its incredibly easy to roll out a compute instance to X% of users, or route traffic between compute instances

so not everyone will have the same experience. If I was saving on costs that would be the easiest way to do it without deploying, without any nefarious intent. The persons in charge of that likely don't even know about how individual users are impacted

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At what point does this become false advertising, or even fraud? Imagine paying AWS for a high-performance server, but 5% of customers who order one quietly get a slower, cheaper server and still pay the full price. That's a serious claim and makes me skeptical Anthropic is doing something like that without more evidence.
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Actually, as a person who rented a dedicated server or two (not from aws) this exact thing happens quite often.

For example a provider quietly underclocks your cpu or puts it is an energy saving plan hoping you won't notice.

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Or your "dedicated" CPUs on your VM disappear for minutes at a time, or just process a tiny number of instructions
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I think they could easily reduce several parameters to slightly reduce cost (something like "it's the same model, a few less passes, but quality is still 95%+").

Or switch to a faster, cheaper cache mechanism or something that's almost as good, but much cheaper to run, in the name of improving efficiency and keeping up with demand. This switch to cheaper mechanisms is what it feels like to me.

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It's a problem for us. When they nerf the model our productivity really drops (due to the specific use case and process we have). We've started using OpenAI and will gradually use it more and more if this continues.
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The degradation only happens to some accounts but not to all.

https://www.reddit.com/r/ClaudeCode/s/64DXRERLyU

It would be nice to know how they select. I max out my $200 subscription every week and I was selected. On Saturday, the Opus on my account that happened to be supervising a running live process, became unusable.

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It would be trivial for them to opt-out accounts that are doing benchmarking from a planned regression.

I really really really do not trust companies on the verge of IPOing from goosing their numbers. Even if the lawyers are up their ass, the social pressures are more than enough to compel the behavior. For every good person willing to do the right thing even at the cost of a delayed career progression, there are 20 people willing to do anything not even for a dollar but for an "atta boy!" from the boss.

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If it's a private benchmark, how would they know it's a benchmark?
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Look up eval awareness. There are all sorts of subtle signals an LLM could use to know if something is shaped like a benchmark or not. But that's not a bad thing, every animal behaves differently in play vs real-life.
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Yes the model can do that, but it would not be "trivial" (as GGP had said) for Anthropic to opt out accounts performing private benchmarks from this theoretical model downgrade people think is happening.

The most plausible approach would be for Anthropic to train some separate classifiers to detect benchmarks. I'm not saying it's completely impossible but IMO this is conspiracy theory levels of effort.

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In the context of public relations they would not need to ID every benchmark only the most credible or most public benchmarks many of which are openly available on github and whose problem-set could be fingerprinted.

You're absolutely right that it is a game of whack-a-mole and eventually we may have leading private + credible + popular benchmarks that ultimately dissuade the behavior, if it can be dissuaded.

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That's a major reason to use local models. Or open weights models on a trusted cloud provider. Even if they are way less capable, they're more predictable
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"Nerf tracking" is adversarial and exploratory. It's not something Anthropic wants anyone to do, and it's not something that the "nerf tracking" designers are necessarily doing in a foolproof way. Don't assume too much from them either way.
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But do from anecdotal evidence without benchmarks?
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Did I suggest that?

Sometimes you just have insufficient evidence to be sure of something either way, and nobody gets to win the argument or shut somebody else down.

In this case, some have reported analytical work[0] that goes beyond "gut feel" anecodotal evidence, but even that's not going to conclusive and may not be trustworthy at all.

[0] https://www.reddit.com/r/ClaudeCode/comments/1xr9x5y/the_ner...

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For example in that A/B test the user got more effort from the model.

Ok, it probably burns tokens faster, but is it really a nerf?

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No, you did not comment on it. That is why I asked. Thanks for the clarification!
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These nerf trackers do not work. I wish people would stop posting them.

They don't detect a quantized model until the quantization gets down to 4 bits or less.

Humans absolutely do detect quantization well before 4 bits...

Try it yourself if you want. Try a small local model, both quantized and not, and I would be very surprised if it isn't immediately obvious which is which.

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But quantized local models also dip in evals.
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It doesn't matter if it's local or not, I just suggested local so people could test themselves.

But no, evals and benchmarks do not detect quantization, until around 4 bit quantization.

https://developers.redhat.com/articles/2024/10/17/we-ran-ove...

https://pub.towardsai.net/your-model-passed-safety-evals-the...

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That is not my experience. I have issues where quantized models fail pretty early so I have evals to catch it.

And the second article seems to reinforce the idea. Yes, broad perplexity tests are not a good proxy for the tests used during training.

Quantizing anything is effectively changing the weights, even if you don’t quantize the weights themselves.

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Nothing stopping Anthropic (or other labs) from pulling a VW Dieselgate and ensuring that benchmarks are routed to a non-nerfed model.
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Should be fairly routine for anthropic to game a nerf tracker?
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That must be on anthropic's benchmaxxing CI test
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Nerfmaxxing.

It probably need a whistleblower to uncover what they are doing.

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I used to be skeptical of nerfing, but as of a week or so ago I've noticed a severe degradation of quality for GPT Astra. It struggled with very simple tasks, and it often failed to follow my instructions.
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I hear a lot of accusations of nerfing as in, saying that the model itself has been quantized.

I doubt this is the case. I suspect all variation in quality and output can be explained in terms of prompt differences, and changing how much thinking happens at each level, as we see in the post above.

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Suppose a company has a limited amount of compute. What do they then do if peak demand exceeds what they can provide? They don't turn off people's access...

And what about A/B testing? Anthropic doesn't even try to hide that they do this. Limited compute and A/B testing alone, would guarantee a nerfed experience some of the time. That is, you don't even need a nefarious reason.

I consider it gas lighting to deny model nerfing.

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> They don't turn off people's access

They do. I often get the message "This model is currently experiencing high demand, please try again later"

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> They don't turn off people's access...

They do drop requests though? At peak times I sometimes have 1-2 requests fail with Opus; no biggie, the harness just retries it. But that, in aggregate, sheds load.

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You serve the requests more slowly. Same as if your bank has a sudden rush of customers - the tellers serve them in order, and the customers wait longer. Some of the customers 'time out' (get frustrated and leave).
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> You serve the requests more slowly.

Thats not what Openai and Anthropic do though

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Really? I have noticed times where the model simply doesn't start 'spending' tokens for a considerable period, using their official harnesses.
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I guess there's an alternate universe where that happens
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I must have found a wormhole into this universe and fallen through without realizing, because I've used Claude Code and gotten "This model is currently experiencing high demand, please try again later" as an error message.
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I'm not denying model nerfing. I'm asserting an opinion about the nature of the nerfing.

If you want to go accuse someone of denying model nerfing, go find someone doing it and argue with them.

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Na, surely effort level is silently degraded. Dead easy to do, impossible for anyone to verify, and very fine-grained so can be balanced perfectly with available compute.

Edit: maybe not impossible. Side channels perhaps.

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Exactly. How much higher is "very high" that "high"? Is it constant across weeks? Who knows!
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It's been the same for every version the last year.

Oh, this Opus X.Y is incredible. Hmm... Now it's dumb. Rinse, repeat.

Doesn't really matter if the cause is quantization, system prompt changes, changes to thinking etc.

It's hard to see how continuously rug pulling users at every release is a good idea. Only reason I can fathom is that it's needed to keep costs inline.

Either that or it's some weird tweaking to the prompts to fix whatever. But given the prevalent sentiment that it's worse that sounds like a long shot

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I presume it just makes the new version look way better? So instead of a more or less straight quality line it looks like a sawtooth
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The Apple software update strategy.
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Kind of sad but if it works, it works! Bit conspiranoic, but i have a feeling nearly all phone vendors do something similar...
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it's easy to suspect the hosting companies trying to do what they can to reduce cost-to-host up until the very threshold of perceptibility, so it's an easy guess to say they're probably doing something that shifts performance up or down between version releases..

but realistically I think you're right, it's prompt quality and the inherent non-determinism elements of LLMs showing up; when both of those things meet you get brain dead outputs.

Everyone likes to shout "slot machines! non-determinism!" until it actually explains something, heh.

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YES. To the point that I literally stopped using it, and have moved BACK to Claud.

This is getting ridiculous. The number of times I have switched from one model back to the other is crazy. I do not have any proof, so its quite possible I'm just delusional. AI psychosis? Either way, it FEELS like these models work really well for a while and then fall off. Switching to the latest model on the competitor always seems better, until it too seems to taper off. By then, a new model is usually available at the competitor, so I switch.

Its possible there's no degradation at all and just a PERCEPTION of it. But to me the end user, it really doesn't matter.

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People should think harder about the fact that this is exactly how heroin users describe a batch of heroin
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Both Astra and Opus didn't really looked good for the last week or two.
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why were you skeptical of other users?
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People are prone to seeing patterns in noise especially after suggestion. It's not hard to imagine someone concluding the model is nerfd after few bad responses in a row
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Why this won’t apply to you as well?
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It could apply to me but I run evals every time someone at work complains about this and it’s never shown any more or less variance than regular usage. I don’t have statistical relevance with my evals but I do have a decent history with them.

People seem to underestimate how high normal variance is with these tools.

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i'm not parent, but to answer your snark : there are efforts a person can take to try to reduce things like suggestability in ones' own personality. Same as anything, the brain can be trained, thus it should go without saying that some of us react differently in the face of suggestion -- both for the better and the worse.
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A growing percentage of the users on the internet are not human.
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Sol been really bad in some basic stuff that I would remove it from frontier models entirely
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Yes I agree, Astra has been awful this week.
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GPT Astra felt nerfed just days after it launched.
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According to our measurements this isn't true. We re-ran Opus 5.5 today on the benchmark we ran in September, with the same prompt and settings. Before and after, side by side: https://playcode.io/blog/macbook-svg-benchmark#reruns

Max, streamed (128K cap): 128,000 tokens, $2.56, empty file, in September and today.

Max, Batch API (300K): 255,957 tokens for $2.56 in September, 243,707 for $2.44 today. The two drawings: https://playcode.io/marketing/assets/static/claude-opus-5-5-... and https://playcode.io/marketing/assets/static/claude-opus-5-5-...

Xhigh: 86,096 tokens for $1.72 in September, 107,333 for $2.15 today.

The Batch API bills half price. Max ran out of the 128K ceiling again, to the token. Given 300K, it drew the same kind of laptop with 5% fewer tokens. Xhigh used 25% more and drew the same kind of laptop. That's inside the noise: 17 identical calls at high ranged from 17,757 to 59,705 tokens.

The model is still the best of everything we've tried. Most likely the next best would be Fable 5.2. But we don't like Fable because essentially the result is the same, just the price is higher. Its medium and high are close to what Opus 5.5 Max had, but the price is higher.

(I run Playcode, an AI app builder. We benchmark every model before we add it.)

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I'm guilty of suspecting this.

If this turns out to be accurate, I think that would be a pretty unethical thing for Anthropic. Even if it is just a "we had to allocate compute to this new model release".

It should be fraud to swap out the model. We need a term for this, something like a bait-and-switch.

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> "We need a term for this, something like a bait-and-switch."

The media coined the term "dual quality" for a European food scandal a few years back, in which conglomerates (including Coca-Cola) adulterated products with cheap, substitute ingredients, if they were destined for distribution in specific markets (mainly, lower-income).

The packaging exteriors were the same. You wouldn't know which version you got unless you were paying close attention to taste. It was essentially what the software industry calls "A/B testing", except with sneaking things into what people eat.

I don't have any good reading links on hand; here's one source,

https://ec.europa.eu/commission/presscorner/detail/en/qanda_... ("Dual Food Quality: Questions and Answers")

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I've been working with Opus 5.5 every day, probably around 10h on average, and I feel confident in saying that they did not replace anything.

I'm a bit disappointed with how this nonsense is spread across HN today.

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"I'm a bit disappointed with how this nonsense is spread across HN today."

Are you saying that the many, many people posting and experiencing this are wrong and you are right?

And not just in this instance, nerfing has been complained about in a cyclical fashion for many months.

But, they're all wrong?

You're so confident in your experience that you cannot think that other's experiences are also true?

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What people claim is not "some experiments degrade performance", it's "Anthropic nerfed the models [because they are evil and do not like the user etc]".

Like most experiments do not save the company money, there was an experiment to test the new fable, people got to use it at opus-5.5 usage. But this experiment clears the thinking blocks when people go back to the vanilla model; not sure if Anthropic overlooked this, but idk, it does not sound like "nerf on purpose".

There are experiments to adjust the effort level, at the moment the ones that I've seen switch to a higher effort. Again this is not a nerf; might be annoying perhaps, the model does start to behave differently (and consume more tokens). But it's not a nerf.

Then there is apparently one experiment that replaces opus-5.5 system prompt with the one from opus-4.8; the model is the same; this experiment is perhaps a bit more questionable, but still it's not "anthropic nerfed the models".

If people think they are getting nerfed they should check what experiments are enabled (claude.json and session logs).

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I'm pretty convinced that those who have constantly been posting these complaints, probably for every single model release out there, are indeed wrong.
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It’s been happening often before and I’ve never seen evidence on degradation.
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> And not just in this instance, nerfing has been complained about in a cyclical fashion for many months.

No, it gets complained about constantly even if there is no model coming out. A completely unrelated thread on Claude will feature comments like "can I just say that [model] has suddenly become useless this week?" Merely asking that question is bound to get people agreeing with you because we are evaluating all of this on vibes and placebos.

I too feel that way sometimes, I don't think it's ridiculous that Anthropic might silently downgrade you as demand warrants. But asking others if they "feel" something I feel is less than useless.

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If you go back in time far enough, your logic can successfully be used to demonstrate the earth is flat.

"Could all these people seriously be wrong?" Yes, yes they could.

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I believe fraud is a sufficient term. You claim to be selling X but you actually sold them Y. Bait and switch is a selling tactic to avoid fraud where they make you believe product is X and then when you go to buy they tell you X isnt available but they have Y. While also unethical, it is not fraud because they did tell you what it is you are buying before you buy it.

if they just straight up dont sell you something you bought then its fraud.

I think there is a ripe opportunity for expanding the definition of fraud to include changing the "ingredients" of a named product on the market. It is not limited here, we see it with food, and even in the medical field

(I will die on the hill that medical fraud was committed when mRNA therapy was used as a treatment for covid and it was 'sold' to the public as a "vaccine" despite not being the same thing as any vaccine before it. The definition of vaccine was expanded to include it without sifficient public disclosure to warrant informed consent imo. This is not a statement about conspiracy or the efficacy of vaccines or a moral judgement on whether it was for the greater good or not.. it was simply an act of fraud that robbed the public of proper informed consent by making people believe it was X when it was really Y.)

So yes, I think there is a large need for the public to at the very least put a strong handle on the ability to change what a product name means. It is a trivial problem to solve considering it is only a problem due fraud or fraud adjacent activities.

heres the solution: You have your product name, and then any changes to it REQUIRE a new version name. Like how you have Coke and Diet Coke, only formalized such that Coke cannot legally replace the ingredients of regular Coke with the ingredients of Diet coke and still call it Coke. With Software they could at least use version numbers and release modifiers. most of the time its built in already, but it needs to include the full stack. if they change anything that has an interaction with the user it should change the label seen by the user for the product.

thank you for coming to my ted talk

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You don't buy a hard quantity of an LLM you buy access in general.

A Opus 5.5 is not a Opus 5.5. Its Opus 5.5 of some checkpoint.

mRNA btw. was well known how it worked, it wasn't hidden and some people waited for the non mRNA version because of it. I never seen or read the argument you make and I do not get it.

A vaccine is something which protects you from an infection. What definition do you think changed in humans? That we make the protein? How is that so different from viral vector vaccines?

The consent is a certain level of trust from the society to a group of researchers limited by being humans and having to act in a certain time frame.

Nontheless, I do agree I would like to have a fingerprint and proper changelogs etc. for products I buy including digital and analog. But this has a downside as usual: The smaller you are, the more it costs you to (probably) register, maintain and change.

You know the good thing about Claude etc. right now? It doesn't matter. My invest is not 4 digits and there are that many changes, i'm quite happy to have been upgraded for 'free' from Opus 4.8 to Opus 5 (what do you call this upgrade, which was significant better?)

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I agree you buy access in general and they are free to cahnge their offering to what that access is however much they want. there should also be communication regarding what it is you are accessing. the meaning of "Opus 5.5" is based on unwritten trust that can be broken at anytime without consequences. the fact that its a hobby and not much at risk to changes

I also agree that if its too formalized with registrations and such that it could be a negative pressure on small business. documenting what the labels mean could have separate rules and smaller business could operate on trust and face penalty if counterexamples are shown, for example. obv this would be the start of a much longer conversation about implementations but i think it's important

--

with respect to the covid vaccine, i want to be clear that i dont pick this fight lightly, I love science. The rare side effects of the mRNA therapy did actually kill people due to severe myocarditis. I believe it is unjust to change who is at risk without doing everything you can to inform people of exactly what it is they are getting. They treated the mRNA vaccine like we are Gods commanding the body to do whatever we want and not like we never have actually fucking know if something is going to kill someone or not. People can be allergic to things, for example, and its only okay because they themselves agreed.

>A vaccine is something which protects you from an infection

this is the new definition.

the old definition was accepted as: "a preparation of killed microorganisms, living attenuated organisms, or living virulent organisms that is administered to produce or artificially increase immunity to a particular disease"

this aligns with informal understandings and how it was taught to people. you get 'infected' with a safe amount of the actual virus to trigger your body's natural defense mchanisms

the definition was changed in 2021 to mean: "a preparation or immunotherapy that is used to stimulate the bodys immune response against noninfectious substances, agents, or diseases".

informally, and biologically, this is fundamentally different. i admit it's a grey area, in that the word vaccine was used to describe it in research phases.. but it was 50-50 and nearly always included 'mRNA' in the label.

But it was still deliberate misdirection that over-emphasized calling it something common and familiar and omitting whats different about it to push a new thing (new to the public, as it would be almost everyones first exposure to mrna therapy) and not only did they refuse to emphasize the differences and make an effort to educate people but they conflated anyone who asked questions about it to be the same as an "anti-vaxxer" and pushed the narrative such that the new 'vaccine' could not be viewed as its own thing. And then they changed the literal definition of the word vaccine to 'cover the tracks'.

it was backwards. everyone should have been informed, proper consent collected, and i think it would have been better received overall. whether people can articulate the problem as i am or not, they felt it. I felt it, and spent a lot of time and energy developing my understadning of teh situation as to be properly nuanced in my opinion of it and not actually go into conspiracy theory territory.

I still talk to people today who have no idea the covid vaccine is not dead covid virus being injected. They should have been informed that they were receiving something different.

again i never said mRNA didnt work or wasnt effective. but it was still fraud. they wanted to move fast, as if all other medical progress was somehow not operating with lives on the line already and that informed consent was just something we do for fun. Covid was serious and required a serious response with funding to scientific education and research, not lazy manipulation tactics. There should have been 24/7 news about mRNA therapies and their history, booths popping up everywhere to answer peoples questions, etc.

The response was lazy and fraudulent and sets an extremely dangerous precedent of allowing future reactions to scientific education problems to be handled through authority rather than education.

--

If you want to get me started on an actual political issue of the same form to understand why i havent let it go nad only become more emboldened with my opinion since covid, go research how the use of the term 'domestic terrorist' has changed over time. The laziness and use of authority to make things be defined however an authorty wants rather than through actual public consensus is only ramping up.

the danger is that the public is slowly being cut from the conversations completely. when a patient is too uneducated to understand any of the treatment you are giving them, is it still consent?

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This happened last time too with Opus 5.5 (released September 22): https://news.ycombinator.com/item?id=49789224
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idk, it hasn't felt nerfed at all to me, and it's not like i'm just doing trivial CRUD webapps either. opus 5.5 is very successfully porting my phone to postmarketos. claude just got the touchscreen up and working (and made a little program for me to test it, and it's legit).
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Benchmarks don't do a good job at capturing the difference in quality of frontier models over smaller models.

Opus 5.5 was so good that if it wasn't nerfed - at least just looking at the benchmarks - the difference in cost here does not seem to justify using this for anything besides design and review.

That's like maybe 1% of total token usage for SWE BUT a better design can have enormous benefits, so it's almost always worth using the best model for that.

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Cost per task

Fable 5.1 Max $11.46

Fable 5.2 Max $44.70

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I don't have a formal benchmark, but daily work (coding mostly, plus some complex architecture design and review) has had consistent outputs today for me. No noticeable nerf from my perspective. I definitely took notice in some past instances, but if they nerfed Opus 5.5, then I guess it was just so good that I was nowhere near its limits.
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Can you share some evidence?
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> Damn people were right about 5.5 being nerfed in preparation for a version release. This is not at all a good look.

Anthropic does this time and time again, unserious company

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I'm not surprised at all that they might be doing shady shit, my free request was used up in less than 7 minutes and said pay to continue, no thanks. I've paid for monthly before, never again I don't care how good the model is. I asked about the extreme limited usage in their discord and got banned, not a good look. You don't have a way to measure what you're actually paying for and they can change it at any time.
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OpenAI did the same and that was the end of it for me. Completely murderded 5.3 and rug pull on cost.
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No they weren't. Models are not "nerfed".
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They do change things though which can have impact on behaviour.

System prompt would be the easiest one.

But there were flash or inbetween models, different checkpoints etc. THey might also try different hardware which might not be binary compatible.

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In a normal world you are not allowed to degrade the service during your agreed and paid contract. You would get sued. Apparently this is perfectly fine in this current world.
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No it’s not nerfed. Another poster said it the best, your dopamine receiptors are nerfed after the new model hype wears off
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There are benchmarks that are measuring it now
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A friend who doesn't follow these news suddenly told me he felt Claude was doing worse the past week. I bet him there was a new model version coming up within days. It's like clockwork at this point, no matter what deniers say. I got a beer out of it at least :)
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People have been complaining about how the models are nerfed non-stop for two years. A stopped clock is right twice a day.
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yeah, we need to make sure we don't get stuck with these two evil corps. Dario is really the worst. Plays the drama queen but he is very hard in all things dark(i.e. dark patterns).
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But, it’s okay they do it because they charge less when it happens.

Right?

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It's been a mess over the last week or so. Went from being the best model I've ever used to utter dogshit that can't complete any task. It's very obvious with the Advisor pattern, where before when it chatted to Fable 5.1 there were small tweaks and so. No every time Fable comes back catching a ton of problems and bugs with Opus 5.5

Fuck Anthropic.

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Is this voodoo? Every time someone makes this claim I'm left scratching my head wondering what the hell they're talking about. Either I'm not very perceptive, or these claims are subjective hand-waving.
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This has happened every single time for the past year, why are people surprised? This is all so that the new models can look better on the benchmarks.
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It's a good pattern to detect for perhaps.
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It's not true. People need to stop believing these conspiracy theories.
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i thought i was going crazy. last week, claude went from having good judgement to doing all sorts of stupid stuff. what a shame.
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for me opus 5.5 was acting kind of dumb, like forgetting basic stuff he was nailing last week
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Interesting - I had the same feeling but mostly with 4.6 when I "downgraded" for some easier/trivial tasks: The model forget things I posted 20 min ago in the chat (and the same file was in the context as well)
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Yep, very stupid mistakes, that newly released Opus would have "laughed" at.
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Another reason we need to democratize local models.
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I literally hit the desk with an open hand yelling I KNEW IT
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It gets worse. You might wonder "why now"? Well ... this happened 2 days ago:

https://x.com/follistatindev/status/2119129611510383014

With early handouts of Qwen4 starting to be reported 5 days ago ... so if they're good, they would have had some hours to evaluate Qwen4 against Claude 5.5 and, then or right after was when Anthropic decided to put out 5.2 ...

So yeah ... benchmaxxing and all that. BUT nevertheless, the published results seem to say that Qwen4-Max appears to match Opus 5.5 on some benchmarks, and Qwen4-27B (probably by going even harder than Qwen3.8-27B on thinking/inference time compute) can beat Sonnet 5.5 on some things.

I guess they're not taking any chances. Keep in mind that Anthropic has declared they have non-public models (it's in their IPO filing). These are referred to by the shorthand names Model 2, Model 3, and Model 4. Essentially 4 is better than 3 is better than 2.

Fable 5.2 is "2.5" so to speak. So Anthropic was holding back, but not anymore. And now they can dial the performance up once more with what they have ready, and probably once more after that.

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“Why now” - they are about to IPO. It has been obvious for months that they would drop a new flagship model at exactly this point.

It would be funny though if you are right and that model is Fable 5.5 in a couple weeks.

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it was so obvious that i even decided to get myself an anthropic sub today, hoping that i'd get a reset or something and i actually did
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Do you know of any rumors if they are still planning to release Fable 5.5 before the IPO or today's 5.2 is it?
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Dario is gonna have to honeypot someone from Alibaba to get ahead.
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