I really don't think it's productive for internet forums to constantly be criticizing language choice when the meaning is clear. Better to respond to the substance of the issue than word choice.

Edit: In response to the initial replies. To me it clearly means "releasing frontier models at any pace less than as fast as possible". It implies relative restraint compared to the previous state and without stating the degree of restraint.

It combines the elegance of LinkedIn-speak with the humbleness of desk-bound people who speak in military metaphor.

It's interesting to compare Anthropic's language with what's coming out of the US military lately. They explicitly refer to China as the "pacing threat", meaning that there is a risk of China achieving superior military capabilities and thus we need to press forward with an arms race (including militarized LLMs) as fast as possible.

https://www.war.gov/News/News-Stories/Article/Article/264106...

You're right to call that out

IDK I think Anthropic is plenty smarmy and weird itself. Sounds like they wrote it.

Did no one in this entire HN thread read past the headline of the post from Amodei? He wrote a very clear set of actions Anthropic is taking.

It’s just another cry for regulatory capture which imo is the only way they stay afloat at their current direction.

China is literally only a single step behind and willing to drop free models just to undercut the US companies.

I’m for it because I don’t want another massive Google or Meta.

Fable 5.1 came out just 21 days ago. Only 3 weeks! And this is 20% relative improvement on terminal bench vs Fable 5.1 at less than half the price, and more human sounding output. does not feel paced to me tbh.

Occam's razor: they couldn't make any more substantial improvements.

I think the real reason is basic collusion. They're burning tens of billions training new models. It's a very competitive space. They know that the companies capable of frontier models is limited so if they can all get together and agree to slow down it gives them more time to make money from inference.

Thanks for spelling out what the original comment was implying.

I find it bizarre how intensely a bunch of these child/grandchild comments are criticizing the notion that people would even think to analyze the meaning behind the words.

Hacker News has always had a unique culture in which thoughtful discussion is basically the main goal, and it's intentionally incentivized in numerous ways. It's been my experience that any thoughts added to a post's conversation are seen as valuable as long as they are thoughtful and seeking to understand.

So these comments are clearly coming from a place that's antithetical to HN's culture. What that in mind, it seems likely to me (Occam's Razor) that these comments are either:

1. Astroturfing: Claude employees acting like everyday folks, secretly trying to shift public opinion.

2. AI cult mindset: "AI is humanity's salvation; how dare you have perspectives outside of those accepted by the cult."

Am I missing another likely option?

To bolster my point, right now we're posting on the top top-level comment, meaning a majority of active HN users find it to be a great addition to the conversation. Commenting to shut down the discussion is a red flag.

in what way is beating every other frontier model with their own second-tier model, 'lower than expected performance'? Please be specific.

Happened to be testing a "review patches on a mailing list" harness I was developing; here are a sample of the latest results, testing 12 patches containing a total of 14 issues:

Opus 5.5: Found 8/14 issues. Total cost: $15.40

Fable 5.1: Found 7/14 issues. Total cost: $66.34

Opus 5: Found 6/14 issues. Total cost: $15.19

Sonnet 5: Found 2/14 issues. Total cost: $19.15

This is a relatively small sample size, but it was both the best and the cheapest.

ETA: NB this is "Equivalent API" cost as reported by claude's CLI; I was using my subscription.

They're claiming a drop in token use too, and that it nets to 40% cheaper.

My workplace doesn't even offer Fable. And on the sub, I've had a hard time understanding Opus 5, but Fable can deal with it with subagents.

If 5.5 is any better, I might try to do agentic-assisted development instead of just telling fable to delegate

When you need to disable data retention, you cannot use subscription plans.

Fable tends not to perform better, just cost more.

Enterprise and most Team accounts use API pricing, they don't have an included-usage quota.

We can’t use fable at work, opus and Astra are as good as it gets.

It's the Chinese open source models. They're barely behind the frontier, making AI a commodity, forcing openAI and Anthropic's margins downward.

I'm hardly a fan of China/Xi, but I do appreciate and benefit from this.

These companies are posting massive losses while also lowering prices. This sounds just like the Chinese bikeshare bubble where they were all taking massive losses in hopes that their competitor would go broke first.

In the end, everyone lost and there are millions of bikes in landfills.

If you're interested in the bikeshare bubble, Asianometry did a video on it a while ago.

https://www.youtube.com/watch?v=FQrEDq8KPiU

You have no suspicion that this most recent collusion is in part to setup the conditions to guarantee government subsidies/bailouts?

There's zero chance of that ever happening. Pure delusion.

I noticed that when opus 5.5 was on parts on my codebase that had lots of 5.0-generated comments, it picked up its style. Unfortunately I think 5.5 has been trained to mimic what it sees so that you can ease up on the instructions, but this does mean parts of your codebase that 5 touched will be somewhat viral.

I will forgive it using load bearing as long as it finds the right seams.

Due to this release note, I used it once to rewrite a doc, and was disappointed.

If anything it seems worse. I'm experiencing about -10% insufferable jargon, but +30% more verbosity. It's unredeemable. There also seems to be even less structured output (headings, bullets, etc).

thank you, i did not try it myself and having read this, will not waste my time and energy

I know we're all experiencing NDFSMs differently, like that's part of the whole problem, but 5.5 just gave me "The truncating quantizer collides two oranges", which is a new low for me.

Yeah I’m having a much better time reading Opus 5.5 output today vs. 5’s wall of nonsense. You still get a few telltale turn of phrases, though the load-bearing smoking guns haven’t turned up yet. It’s still a bit verbose compared to what I’d ideally like, but it’s tolerable now.

Code-wise it seems to still nitpick, especially in reviews, but it doesn’t seem to rabbit hole quite as badly on tangents and scope-creep. These are just first impressions though. It’ll take a few weeks of regular use to really have a sense of it.

I prefer Astra for creative uses, Fable seems better for hardcore coding.

I really wonder how it converged on its style. It's pretty unique and terrible. It's not like it's just mimicking something or it was purposefully design to be that way. I mean the reason may be diffuse and uninteresting... just the result of a lot of factors and lack of control over the writing style probably.

But oddly enough its still great at coding. Just like a lot of people it either interfaces well with people or machines but not both.

Astra is better here, but the one I'm the most impressed with is Gemini. It's always been good, but 3.6 Flash is even better. It writes in a pleasant, human style. Not perfect, but it has a good balance between technical accuracy and readability that is better than what I've seen from any other mainstream model.

Yes, it made me want to vomit. If the new Fable only changed the writing style to just sound like a human, same performance for everything else, I'd be pretty happy.

Opus is only usable if you have a post-turn formatter that strips all comments from the generated source. I'm not even kidding it's that bad.

It's not X, it's Y, not A, not B, not C, and he haven't even woken up yet! Here's the catch, the detail is in the devils and the twist is that it's designed!

I’ve been working with frontier models for the last year on a large real-world project with multiple apps. Eventually they started becoming unreliable. Simple UI issues, usage limits and overengineering became constant problems. I had to come up with a robust process: task analysis, user intent analysis, implementation and testing. All of these steps loop when needed with 15-20 steps per task in total. This finally got the models to do a good job but I started hitting usage limits. Then I switched to DeepSeek and haven’t noticed any drop in quality. It’s fast at around 300 TPS and cheap. I don’t miss frontier models anymore! Come up with a good process and you might not need them either.

Yes, I tell exactly how I want it done and what files to modify, in those conditions sometimes a model that does not try to read between the lines works better.

I’d not put Luna and Deepseek in the same tier as Sonnet, they were clearly ahead last time I checked (though I might be outdated and that’s on my personal use case).

Deepseek on high reminds me of Opus 4.x which was quite good for a lot of tasks.

If you're producing slop, the quality of the model is irrelevant as long as it compiles. I frequently catch Opus/Sol making silly errors and over-engineering solutions while small ones like Luna struggle with complex tasks.

Yes exactly. Reading this "thinking" traces is a great tool.

It really is good. I forgot to mention that within that said sub agent, it also went into exploring top e-commerce websites (Zalaondo, Temu, Amazon, eBay) for exploring prevailing industry UX best practices and taking screenshots of their product and category pages with its own written chrome driver that I talked about and then went onto prototyping a new website in a temporary directory and then taking hundreds of screenshots to analyse what would be the best column density one each medium for each language.

And that all is 0.07 cents all included.

A good resource is this: https://artificialanalysis.ai/?cost=intelligence-vs-cost-per...

Go to the "Cost" -> "Intelligence Index vs. Cost per Intelligence Index Task" That diagram maps their "Intelligence" score to "cost per task" and I think this gives a good basis on deciding with which model you want to go. Then you can either get an API token from that models provider directly or use openrouter and set openrouter to the model/providers of your choice.

You can also see on openrouter itself the details for each model like prices and what providers are offering it at what price.

Finally you can compare models details using openrouters compare feature like this:

https://openrouter.ai/compare/anthropic/claude-opus-5.5/open...

Plenty of times I’ve seen a model say “it’s a classic X” despite not being a classic anything. Might just recognize it’s a test in general, or it might just be a tic.

Dont conflate "I know this is test case" with it being trained on it.

But its safe to say that pelicans on bicycles are disproportionally huge part of their training data

It's the model admitting that it has heard of the test. It's been around for a couple of years now so I'd be surprised if it hadn't.

Doesn't mean Anthropic deliberately tried to train it to do a good job. If they DID train for the test their results are quite disappointing, I've seen better efforts from open weight Chinese models.

I think people just like to see the drawings at this point.

It has read the internet. That doesn't mean it was literally RL'ed for this

I was a bit skeptical when they said it behaves like Fable but is cheaper... those two things have been mutually exclusive in my experience, no LLM can light tokens on fire faster while spinning its wheels than the Fable/Mythos tier of models.

I’ve been paying attention at this exact detail.

Misplaced legs clearly indicate lack is spatial reasoning - the llm can reason about verbal idea of a bicycle but not about the actual object. The fact that this model got it correct gives me a pause. Did they figure out spatial reasoning? Or did this complain trickle down to the training set?

I like the Pelican test. And I agree this pelican looks very boring.