Around February, Opus 4.6 was excellent. Smart, fast, proactive. Then it got lobotomized and it's never been the same after that nerf. 4.7 came along and it too was disappointing—not unlike 4.8, which despite feeling a smidge smarter, tends to write word salad and is basically unusable for some workflows.

Fable felt like having access to that "old Opus" again, but a little smarter. Sort of like I'd expect an Opus 5 to be. It's not earth shattering, but it was a step in the right direction. And it was distinctively so, because having to go back to Opus 4.6/4.7/4.8 has been borderline depressing...

It understood more with less help, did more per turn, and was less argumentative. It also felt a little less trite in its answers, which is an understated improvement for those who use claude code all the time

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RaSoJo 4 hours ago | parent | next [-]

This is exactly what I find frustrating. I get comfortable with the latest model X. Then a new sparkly model Y launches. I am like, I don't need your new fangled Y, that consumes more tokens. My needs are small and i am happy with the older X.

But then X starts to degrade. At first subtly, and then drastically. So then I am forced to upgrade to Y.

What I do not understand is:

> is this a sneaky way for companies to push users up the chain?

> Or is this a genuine fault in model design/resource allocation?

	▲	sigmoid10 3 hours ago \| parent [-]
		I suppose it is both. Basically all frontier models are inference-time compute bound thanks to reasoning. And actual reasoning traces are locked behind closed doors at all American labs. So whenever they want to push a new model and need to give it hardware, it would make sense to cut into the reasoning budgets of older models. Users will not be able to see that directly, it will only become apparent on high-end, difficult tasks - exactly the kind of tasks where the provider wants you to use the new model anyway, so they can further improve it.

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jeffyaw 39 minutes ago | parent | prev | next [-]

february was some kind of nirvana. i do think claude code versions and what is introduced at that level is/was relevant.

but 4.8 xhigh w/ ultracode to me is just about Fable level (w/ some agents harness tweaking).

but have to switch to 4.7 xhigh and 4.6 max quite often these days.

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matheusmoreira 3 hours ago | parent | prev | next [-]

I miss the old Opus 4.6 too. They're probably quantizing the old models.

	▲	pbgcp2026 2 hours ago \| parent [-]
		K/V cache compression and context shortening / summarisation. And yes, I suspected Quants too.

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dist-epoch 3 hours ago | parent | prev [-]

All of these discussions of models being "nerfed" reminds me of discussions among audiophiles "this cable sounds so much better than this other one, it's night and day, ferrari versus honda civic"

Yet when you do blind tests they can't tell the difference between a $1000 cable and a $1 one.

I bet if you do blind tests between GPT-5.3, 5.4 and 5.5 most would struggle to tell them apart, yet they are certain that "5.5 was nerfed 1 week after release, it's so obvious, it was John Carmack, now it can barely write a for loop"

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anentropic 3 hours ago | parent | next [-]

Exactly this. And it's not really possible to do repeatable trials, it's all just vibes. People have very little awareness of their own cognitive biases.

	▲	spiorf 2 hours ago \| parent [-]
		And companies have high awareness of this all. They have a way to decrease cost and probably increase token consumption, with gradual changes and no abrupt jump in capabilities, and users have no way to reliably detect it. Market will advantage companies that do it. And they are in the best position to automate online narrative shift (the real LLM killer application IMO) towards "Users are imagining it".

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pbgcp2026 an hour ago | parent | prev [-]

You will be amused to hear that when Anthropic "refreshed" 4.6 on AWS Bedrock I found it in my tests and wrote about it – and they actually rolled it back. This is how much non–coding tests may tell you about the model.