I dislike Anthropic but I wouldn't argue 4.8 isn't an improvement on 4.5/4.6. Your tasks just might not typically need the extra intelligence.

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jorl17 2 hours ago | parent | next [-]

Opus 4.7/4.8 often over-engineers on my setups, plus:

- It talks a LOT more like GPT models. You know: wrinkle, shape, gate, coarse, scope, gap, path, production-ready-workflow-of-the-day, and so on -- "that's expected, a consequence of the previous like-driven workflow". If I wanted to get a headache using AI I would have gone with GPT in the first place!

- It outputs text in a much harder way to follow along. I can't exactly say what it is. Maybe a bit of everything? Bolds are missing, bullet points are gone, paragraphs are bland and too long, and it doesn't feel like a model programming with me, but rather a somewhat full of themselves grandpa developer looking down on me. It's very weird to describe this, but it is definitely how I feel.

Granted this can totally be because of the way it reacts to the prompts now. We've got a rather large corpus of skills and "rules and good practices" that Opus 4.6 responded to great, and maybe the new models just get turned into this when fed with them....I don't know.

Either way, with Opus 4.6 being as good as it is, I need Fable to be a significant step up to justify a price increase. if it can get me to babysit opus a little bit less on some stuff, it might be worth it. Otherwise, I'm very happy with Opus 4.6 and hope they don't deprecate it.

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taormina 2 hours ago | parent | prev | next [-]

I'd argue that 4.8 is a straight downgrade. For every type of task I've tried. It's been a gambit at this point. If 4.6 quits being available, I'm out at this point.

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coronapl 34 minutes ago | parent | prev | next [-]

Reading so many contrary positions about which model is better or worse shows how difficult it is to measure intelligence based on personal experiences. Of course, benchmarks try to make the process as objective as possible, but they often don't correlate with our personal experiences.

The other day 4.6 was fantastic for x task. Today, 4.6 overengineered everything and I had to revert all my changes. When evaluating models, perhaps it makes sense to consider luck as an ingredient before reaching any personal conclusion.

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surgical_fire 2 hours ago | parent | prev | next [-]

I actually experience 4.8 as worse than 4.6 for everyday coding tasks.

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dcchambers 2 hours ago | parent | prev | next [-]

IME Opus 4.8 (and 4.7) is often a downgrade from 4.6. I find that it tends to overthink and overcomplicate things.

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aspenmartin 2 hours ago | parent | next [-]

Yes but there’s a reason we don’t evaluate these models this way and instead do it as carefully and thoughtfully as we can at scale. Human evaluations are important but they are an absolute minefield of footguns. 4.8 is not a downgrade from 4.6 there is an insane amount of hard data that contradicts this.

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computerex 2 hours ago | parent | next [-]

The flip side is that benchmarks are gamed even by the top labs. Benchmark performance doesn't necessarily correlate with real world performance.

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aspenmartin 2 hours ago | parent [-]

Again correct but it overstates the issue. I can say labs don’t want this. This happened arguably unintentionally in Metas llama 4 release, it went horribly, heads rolled, and like several billion dollars were paid for new talent and the org that built llama 4 was destroyed.

Evals come from a million places and new evals and robust perturbations of existing evals abound. They test a variety of tasks in a variety of ways. All of them individually are flawed. Taken together the aggregate signal is highly useful as you more or less marginalize over a lot of different things. Not to mention these companies have plenty of proprietary internal measurements, they build benchmarks themselves to probe their models and then also have flywheel traffic and A/B tests.

You are right to call out benchmarks but to dismiss them or not take them seriously is a mistake.

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taormina an hour ago | parent [-]

Listen, you can say “but benchmarks, the benchmarks!” all day long, but consumer know when we are being sold a lemon. If it can’t do the most basic of things at least as good as it used to, this is table stakes. Nevermind that if you can’t do the basic stuff, how on earth can you be trusted with more?

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aspenmartin an hour ago | parent [-]

And you can say “If it can’t do the most basic of things at least as good as it used to, this is table stakes” all day long while people point you to much better evidence to the contrary too, I’d rather be on the other side of that.

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taormina 27 minutes ago | parent [-]

Listen. I don’t care about evidence. I care about my lived experience for the product I paid for. I used the new product. It’s actively terrible. To the point of not being usable. We’re all ancedata, but what is “better evidence to the contrary”? The known and game-able benchmarks that they know they need to win at, so they train it to. It’s all he said, she said, which is the only reason we keep having this conversation.

	▲	aspenmartin 13 minutes ago \| parent [-]
		Yea but it’s not right? You or I or the myriad of other institutions inside and outside of academia can probe these models with an evolving landscape of evaluation sets, even those unavailable to the developers. It’s just ignorance to claim benchmarks are somehow useless or all being gamed. You choose your tools in the way you want, but just don’t call it somehow better than a myriad of more carefully constructed setups and scaled evaluations.

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gen220 2 hours ago | parent | prev | next [-]

Actually anecdata I gather on my job from myself and coworkers is the only benchmark I trust anymore, because it so heavily diverges from the “benchmarks”.

	▲	aspenmartin 2 hours ago \| parent [-]
		That’s your call just don’t expect anyone ever to take that seriously. It’s not like we don’t have exact evaluations like this.

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pythonaut_16 27 minutes ago | parent | prev | next [-]

Seems like a bunch of noise. What does this even mean?

It sounds like you're saying "Actually you, as a human, are simply not smart enough to evaluate Opus 4.8"

	▲	aspenmartin 17 minutes ago \| parent [-]
		No it’s: evaluating these systems are complex and there’s a reason why sociology, cognitive psychology, medicine, etc are all done in careful double blind conditions with pre registered tests. It’s not that humans are not smart enough, as I said human evaluations are incredibly important. And yet they are a minefield of biases you have to worry about and correct for. - evaluations need to be done at the same time to avoid drift in your bias - you need to worry about your test set: which questions are you asking? How many of them? Are they representative of your work? - which one did you do first? Raters have a tendency to bias in one direction or another - you also know the label! You know which model is which! This biases your assessment… And on and on and on. Careful science exists for a reason.

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recitedropper 2 hours ago | parent | prev | next [-]

"Carefully and thoughtfully" is antithetical to the approach to benchmarks these days.

Maybe back when this was a scientific endeavor; not now when enormous, enormous amounts of capital are on the line. Along with an entire cult's chosen eschatology.

	▲	aspenmartin an hour ago \| parent [-]
		You can call it a cult but it’s several thousand skilled workers who know what they’re doing, by and large, most of whom have a PhD and know how science and statistics work. Benchmarks are incredibly hard, and any PR or comms department at any company is going to obviously want to make things as rosy as possible, but beneath this are earnest, expensive efforts to get good quality measurements. The better you can do this the better you can compete. If you want to make a modeling decision you run an ablation, and the quality of that decision is only as good as your measurements.

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OtomotO 17 minutes ago | parent | prev | next [-]

There is no data that I would trust that contradicts it.

Frankly I don't give a damn about data that could be made up on the spot or appears to be scientific or meaningful while it's not at all clear how it was made (up).

Claude was heavily lobotomised for my work starting somewhen in February.

I talked to friends and people I know and trust and many felt the same. (I didn't ask them whether they felt like I did, but what they felt, how happy they were with agentic coding etc.)

I quit my abo in March and talked to said friends who are still on a plan just last week: they are still not happy, but company pays so whatever...

	▲	aspenmartin 10 minutes ago \| parent [-]
		That’s ok but at what point is this getting into conspiracy territory? You have just said there is nothing you would believe to the contrary, but then by definition that’s not exactly a very thoughtful or insightful position.

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orbifold an hour ago | parent | prev [-]

[dead]

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BoorishBears 2 hours ago | parent | prev [-]

"Fable 5" is Opus 4.7, and the Opus 4.7 we got is a Sonnet sized model on a stronger base.

That's where all the regressions and inconsistency in experiences stem from: RL can still only go so far vs having more parameters

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OtomotO 29 minutes ago | parent | prev [-]

Lol. If you're doing anything non trivial that's not a CRUD webapp but e.g. some physics simulation or high performance GPU code any and all models I've tried suck.

They are not just leagues behind what experts would code, they are not even playing the same game.

Which is to be expected, as there isn't so much physics or high performance gpu code available as there is for your typical CRUD API and JS frontend.