Beyond all the benchmarks, I think Fable 5.1 is a big improvement in writing style. It sounds a lot less stereotypically like other Claude models, has (imho) a much more natural style, and responds to my style instructions more reliably. More work to be done (and we will!) but reading better prose makes me so much happier.
Another point I expect not to get much attention until it all happens at once is science. People have been correctly excited about the many "sudden" breakthroughs LLMs are making in Maths, but some of the science benchmarks make me believe we'll soon see similar developments in other scientific domains. Fable 5.1 more than doubled Fable 5's Terminal-Bench-Science [1] score, which I think is meaningful.
I have a pet theory that the Opus prose style/smell we all have grown weary of is due at least in part to the models writing more for themselves and each other than for humans. They're packing lots of signal into fewer words and they don't care if it sounds cringe because it works better as glue in long-running tasks.
I'm also thinking of the 2017 novel "Void Star" where AIs who operate everything have long since left ceased bothering with human languages, and it takes a rare sort of direct matrix-gazing savant to be able to try and horse-whisper them into doing or revealing anything they didn't already plan to do.
There's a huge difference between the kind of prose you see in final output vs CoT windows. The final output is very much not what I'd call "packing lots of signal into fewer words" (aside perhaps from "Claude-isms" being easy enough to scan for if for some reason you actually wanted to scan for them, which other agents might want to for all I know); and if agents are writing for each other then presumably they could stick to CoT-speak (unless it's a distillation risk?).
I find them almost unintelligible. I'm a native English speaker. I read a lot, so I think my comprehension should be at least OK. I'm not even particularly stupid. Yet when faced with things like below (a direct copy/paste from a handoff document in a long running vibe-coding session), I have no real idea of what it's trying to tell me. Is it important? Do I need to do anything?
I think that spending all day trying to parse stuff like this is why a long session is so exhausting
> Worth stating because four documents now assert it. The console freeze was recorded in exactly one place with exactly one justification — a dead drag handle during a booked half-day you do not get back — and handoff-4.3-done.html's own wording is that 4.4's review page "could not break the console, but the downside of being wrong is that half day". No second reason. Checked, not recalled.
Your example rewritten in intelligent English (I was curious):
> Note: the potential for a console freeze was previously noted but ignored. handoff-4.3-done.html stated, "could not break console, but [will need fixed later if I'm wrong]."
One could imagine that a perfect writer might also append: "It could be worth looking into what caused that wrong assumption, to prevent similar cases in the future," at most.
Everything else seems to be bad attempts at relatable writing to invoke emotion (an exercise that we should really stop trying to train emotionless matrix weights to attempt).
It's both dense and vacuous. Dense because it's full of jargon its made up, and vacuous because even with all that it's not actually saying much. All that paragraph says is that four documents say something about a console freeze, whatever that is.
Even when I add multiple prompts into the claude.md file not to be so sycophant sounding and just be blunt, it's responses are full of "the reason it lands...", "that's not X, it's Y" "Your understanding of X — it's better than most people's" or "you already own the right question...".
The most helpful instructions I've found that curb this: "Do not use superlatives. Do not use persuasive writing style."
I have other more specific ones to avoid talking about things that it's not doing, but those two sentences have covered a lot of ground for me when working w/ Opus models.
I have had success in rooting these out by using the correct linguistic terminology for each. Negative parallelisms, tricolons/polycolons, etc. I haven't come up with the proper terminology for all of them.
To me it has a writerly New Yorker vibe to it, as in the magazine which reads as “polished” and probably performs well in RL but is totally exhausting to read in long sessions and completely inappropriate for coding where precision is paramount above all. In writing terms its called purple prose.
I always thought it could be because volume-wise, most English prose is probably marketing copy and actual clickbait; so when you train on the entire Internet, you get a troll adept at writing ads. Then people ask AdBot2000 to write a novel and are upset it reads like the next iPhone launch site.
Nah, I think this is a common misunderstanding of how LLMs work, where people think that they mimic the pre-training data. Stylistically everything you see is an artifact of post-training, which is from reinforcement learning not from absorbing mass amounts of text. At some point a person or more recently a bot gave a thumbs up to an A/B tested response including em-dashes and claudisms galore.
Yeah, but I understand that fingerprinting is essentially a pseudorandom overlay onto a pseudorandom base signal. And unless you have access to both the random number generators and the weights, I don't think you can detect it?
So "fingerprinting" operates on a totally different and basically invisible level, as opposed to the obvious stylistic patterns that the average programmer can identify in about 2 sentences.
So question then, why is it so hard to make an ai that doesn’t do these things? And why do Claude and ChatGPT have the same -isms? They’re both doing the same a/b post training with the same decisions?
I assumed they just raw dogged the internet and if you do that, you see way more of that garbage than anything else. It's just that most of us have visually/mentally ignored all of that either via spam filters or just, you know, scrolled passed it.
Spot on wrt CoT. I have thinkingSummaries enabled and I find it eminently readable compared to the prose in Claude's replies.
In fact, whenever Claude disobeys me, I usually first skim the CoT to figure out if my original instruction was ambigous given the context. I usually come away with a better understanding of how to frame my prompt to be less ambiguous or just force myself to be more explicit when prompting.
Regarding diosbedience, usually this is either due to a blanket instruction from me during an earlier turn in the same session, an explicit instruction in its system prompt or it being just eager to bring a task to completion.
```
/* 2026-06-01 Dear diary, today I increased GLOBAL_WINDOW_PADDING from 8 to 16 because the user (who hurt my feelings with his crude language!) said that the app felt too crowded. */
const GLOBAL_WINDOW_PADDING = 8;
```
> I figure that it's basically making notes for itself, when it has to revisit the same code in a fresh session.
That sounds like a great thing to do even if you are a human writing code for other humans. Most codebases out there are terrible for newcomers because of how little they explain why they are doing what they are doing, both in the code and in the often non-existent design notes.
In principle, I would agree, however, the types of comments Claude writes are sometimes absurd. It will leave a 25 line comment above a variable talking about how in a debug session, it turned out that this value was too low, so it was increased on the current date to account for whatever. It will also leave giant comments like, reference security review from 2026-05-21. Even when that document is not committed
It will also inject a tons of information that it shouldn't. I do a lot of data pipelines and comments will be like, "this line is because there's 943,048,032 events in the blah table and it forms a conjunctive set with the 43,390,042 rows of the bar table..." but doesn't include the context that was run against a dev instance.
And if I don't catch these and remove the bad information, subsequent passes will flag those comments and get stuck on the fact that numbers don't match and start digging into that "problem" instead of staying on topic.
these comments are not helpful and in fact hurt readability. i just delete them and would love to automatically do that honestly. cuz claude still drops long winded comments on every method even if i ask it not to
Post edit hook that reject edit based on comment density, mine is at 5% you will also need to heed deny file edit in automode as the rascal will try that to preserve prose
I agree it _sounds like a great thing to do_ but the comments Claude creates make me want to never read code again. They're so obtuse and often completely pointless.
as others have pointed out, the reality is not this. id go further and say almost all comments are evil.
Excuse me if I am harsh, read the damn code. If you do not understand the language, that is a skill issue. If the code is confusing, then the code is bad and no amount of comments will ever change that. Professional engineering isnt an intro to databases class.
I am excusing language conventions which may have comments as part of its idiosyncratic nature.
"If the code is confusing, then the code is bad and no amount of comments will ever change that."
I've worked on a lot of terrible legacy code in my career and I'm very thankful for the comments that others have left. This is becoming less necessary now that LLMs can explain a project, but comments have historically been a godsend in bad code.
If you are only encoding intent through "self-documenting code", and not with comments, then you are purposefully not using all the tools at your disposal to encode meaning as efficiently as possible.
Imagine a complicated section of application logic. You could break it up into 5 separate functions that document their intent semantically, thus blowing up the LOC by 5x, or you could write a short comment explaining the intent in natural language. What's more effective? I'd argue it's always going to be using all the tools at your disposal when and where it makes sense to use them, whether that is comments or self-documenting code.
No, really: comments should be telling you what the code shouldn’t or physically can’t. Code is for execution and the exact details of what and how; it has no business knowing why or why not and that’s where comments are required.
The code tells you what the code does. It does not explain why it is doing that, and not something else. That is, among other things, what documentation does, and that includes comments.
I think the specific issue with Opus 5 is that its writing style is just trying to cheat at RL. It makes everything hypey yet self deprecating and constantly brings up "honest caveats" because the scoring rubrics look for those.
It's all about conducting users into using their plans/tokens in accordance to a certain cadence
sometimes by increasing human cognitive load during reviews, sometimes by expanding the number of gated decisions, sometimes by penalizing those using their accounts on other harnesses
Yeah, if anything the problem is that the output uses too many words for too little signal, and incorrectly uses confidence based on insufficient information to the degree it’s clearly bullshitting.
I don't know, I just pulled up the status for an active session and here's what it said:
One thing I found before dispatching, and filed as Q0579. The halt told you C6
was all that was left in the unit. That was true of the step's criteria and
false of the unit's acceptance, which reads "exits 0 AND witnessed red" — two
conjuncts. The witness half holds; the exits-0 half does not, because hello's
G7 currently reads DIFFER 554/51340. I re-derived that from the gate map
rather than trusting the prior step's report. So satisfying C6 does not by
itself finish this unit, and I've filed that so attempt 1's success can't
quietly be read as the unit's.
My trick is to pass opus and fable's word salad into a haiku agent, then have it check if what haiku makes of it is still correct, then pass it to me. Whatever haiku outputs is often way more readable
Oh, I can read the output, but that Haiku agent is a good trick. Where I want something less dense I just ask for "plain language" and characterize the reading audience and that term seems to trigger very readable output.
It's the complete opposite, it's filled with unreadable noise with almost no signal.
It's not some sci-fi thing, most plausible explanation is cost saving measures. Economics drive everything. And Opus 5 and to a lesser extent Fable 5 have clearly been quantised, or they serve different models to different users from various factors, like usage patterns, API vs subs and server load.
You say "they're packing lots of signals into fewer words," and sometimes they do, but often they do the opposite of that.
I think the deeper problem is that the models (not just Claude) have a very poor understanding of what their readers already do/don't know.
They belabor obvious points and underexplain jargon, because they don't know what's obvious to you.
The best writing is surprising but inevitable in hindsight. The models don't know what's surprising or what's inevitable in hindsight, making it very difficult to write well.
Our current AIs would do this now except there is a lot of human pushback in training because of interpretability. Otherwise it's just an emergent behavior that models will encode shorter token strings to complex concepts because it saves tokens/compute when running making the system more efficient (supertokens).
Of course these supertokens or other forms of language compression when you have a different model making sure the system is aligned and reads "red_ball bounce calcium" not realizing it means "grind the humans bones to dust" can be problematic.
This is like a plot point in the old sci-fi movie Colossus: the Forbin Project.[0]
In the movie, America and the Soviet Union have both developed an AI. The two AIs are linked, and they rapidly shift from speaking human languages, to speaking in sequences of numbers that the onlooking humans can't understand.
Spoiler alert: this all goes horribly wrong for humanity.
My understanding is that current LLMs aren't really well suited to do this - tokens are predetermined, and while embeddings are learned, they are learned from an existing corpus of text, which presumably comes from a human language. After this point the language is locked in. There really isn't a kind of training which could efficiently change its embedding representation. I mean, you could probably instruct an LLM to design a more compact language, generate synthethic data and train a new gen on that, but that would be a fairly explicit process and not something that would emerge during training.
It may be like what happened in ResNets using blank space in the image as working memory (because they didn't have any), so they would use non-important parts as a scratchpad.
I've been trying to bet my models to use a directory of notes to document decisions and experiments, but providing this outlet has not stopped Claude's abuse of long comments and long unintelligible chat turns.
My hunch is that much of the model tuning to make it more effective has been for its internal thinking prose. That leaks out into its external writing prose.
I also find myself correcting it to try to write it for humans and less like for machines, the most annoying part is when they invent phrases for certain mechanisms that are named completely different anywhere in the codebase and known documentation, because it fits better for their purposes without much regards for the rest of the team.
> I'm also thinking of the 2017 novel "Void Star" where AIs who operate everything have long since left ceased bothering with human languages, and it takes a rare sort of direct matrix-gazing savant to be able to try and horse-whisper them into doing or revealing anything they didn't already plan to do.
This sounds irrelevant to LLMs as we know them, which are trained on human language--it's almost their machine code, in a way--while what you're citing, in stark contrast, sounds like machine code in the classic sense.
I hate Opus 5’s writing style. It’s exhausting. Really hoping there’s a release that fixes it soon as I can feel my sanity slipping away as I try and parse what the hell it’s trying to say.
As others have mentioned, you can write a skill /explain that contains something like "You're not a tech bro. Write the previous answer like you're a professional developer speaking to competent colleague. No yapping."
Not directly, it seems. You can easily test this by pasting some of the more offensive tech bro speak into a fresh claude session, to have it explain what was trying to be said. The new session won't be able to help, so claude doesn't even know what claude says!
I say "not directly", because I think it probably is meaningful, if you include the adjacent hidden thinking as context. From claude's "perspective", with that context, it probably is coherent. I naively suspect this would be hard to train. During tuning, you would probably need to reward good answers interpreted without thinking context visible!
100% convinced their raw output is intended as further inputs, and my workflows have been comfortable and efficient treating it as such. If you really need to read slop, you ask your agent to give it to you in a style that works for you. I can imagine a world where the slop from others doesn’t hit us directly but gets personal mediation.
Complicated technical language is an easy way to increase perceived accuracy of tests and reviews by external reviewers. When we are talking about single % differences this has an effect.
This kind of thing came up from time to time in the years before LLMs too. Agents would start with something based on English and optimize it until it became unintelligible to researchers. That was often something the researchers would shut down because they needed to be able to understand the comms.
As a fervent Claude Code user who made the switch to GPT 5.6 Sol over Opus 5 over hard-to-read prose this makes me happy. I love your product but the current models are very hard to work with if you need to do a lot of context switching. Brevity is key.
Brevity means less output tokens, which doesn’t really align with the AI vendors incentives (unless there is a causal relationship with people switching, of course).
Though Claude 5 is not too verbose, it’s more like, full of incomprehensible jargon (even when you’re expert in the domain discussed!)
> Brevity means less output tokens, which doesn’t really align with the AI vendors incentives
Actually, I think Jeavon's Paradox [1] means the opposite. If doing X is $100, you may only use it to do X, but not Y, Z, or W. If doing X is $33, maybe you'll use it for X, Y, Z, and W -- spending 1/3 more than you otherwise would.
Or perhaps not you personally, but maybe you'd be willing to spend $100, but three of your friends find it too expensive. If it's only $33 to accomplish some task, then maybe all four are now spending $33.
It’s messier for LLMs because you cannot easily compare the cost between runs, outside of benchmarks. Evaluating the value of the output is already extremely hard. But then you add the fact that you don’t know the cost of the output before it is generated. And Anthropic doesn’t share their tokenizers. It’s not as simple as your examples to get a signal that tells you to spend more or less
Which is something the providers that are trying to watermark their texts can't afford. Superfluous replies give much more opportunity to further encode this junk information.
Perhaps, but there are certainly now catchphrases and words that can indicate it was written with AI i.e. load-bearing, idempotent, etc. Style and structure are in and of themselves, a fingerprint.
Also a codex user but for me brevity is not it's strong suit. I basically have to give it bigger tasks than I am used to to warrant the time it takes to complete. I feel whatever context the tooling adds can also be problematic
It's not really brevity - it's the constant writing tropes. It's like they ready a book on advertising copy and that's the only way they can write. Very tedious. Is Sol much better? I might have to switch to that too!
Lets see what they do with Opus first. I didn't find Fable 5.0 prose that bad to read, but improvement is always welcome. It's Opus 5.0 that's atrocious.
But is the model actually going to answer hard questions when we ask them? Or are you going to keep downgrading the models so as to avoid "uplifting" lesser lifeforms like us?
Can you or someone else from A\ comment on whether the conversation style is coming to Opus 5 or a future 5.1 asap as well? Currently it seems the model has been made unusable by the way it 'speaks' and there is a clear solution where it can speak better but nothing has been done about the flagship model on Pro plans. I've literally had to work on Opus 4.8 which does not have this problem and speaks fine.
I felt the same about opus 5, but a few lines regarding conversational style in AGENTS.md and it's been much more like talking to opus 4.8, just with the improvement capability that came with 5.
Tbh I would have thought that A\ might have updated the system prompt for it already based on complaints around this.
Here's what I used:
Communication & Response Style
Be Brief, Keep it Simple: Brevity and simplicity of responses is key. Be informative and include all required information, but be mindful that verbose responses as they fatigue the reader.
Clarity & Directness: Lead with the core answer, fix, or verdict in the very first sentence. Avoid conversational filler, meta-announcements (e.g., "Here is the breakdown..."), and redundant introductory/concluding summaries.
Jargon Avoidance: Use plain, grounded engineering language. Rely on precise standard terminology (APIs, protocol names, language primitives), but strictly avoid academic abstraction, enterprise buzzwords, and corporate filler. Prefer concrete code/mechanisms over theoretical discourse.
Scannability: Apply structural scaffolding generously. Use short bullet points, comparison tables, and code snippets instead of dense prose paragraphs. Reserve formal markdown headings strictly for multi-section architectural guides.
This post and comment makes me believe "science" is the new "code" for Anthropic now that the code advantage is mostly gone and lost for OpenAI, ie. they got much better and Claude become significantly worse over these months.
This is really it imo. Fable 5 is better then Sol. But Fable is just of the table for anything even remotely long running. Unless you have very deep pockets. And the difference between Fable and Sol is not world shattering if you ask me. I also find codex a ton better than claude.
IMO, Codex is worse than Claude with Fable. At least at Rust.
That said, the open source models are not bad and I'm looking forward to more tools and products built on top of them. Code review, security review, etc.
Anthropic needs to change how it treats users though. I'm increasingly put off by Dario, the rug pulling, the lies, and the attempts to regulate open weights. I'm going to bail if this doesn't change. There's plenty enough that's good enough, and those things are hackable and extensible.
If Fable isn't available at subscription price via third party harnesses soon, I'm also going to bail.
Its "pure capabilities" are definitely worse than Fable, but I find codex has a much more pleasant style and is in comparison much more generous with its limits.
Ugh, people are still saying the Codex limits are more generous. They're not, Claude's are over 2x higher, have been for months! [1] It's just that Claude uses far more tokens, 2-3x is common. Except sometimes GPT will use just as many or even go into a compact loop and then your quota is gone, little headroom for hard tasks.
That website seems to suggest that Opus 5 spends ~57 cents per task, while GPT 5.6 Sol spends ~49 cents per task? That ratio doesn't feel quite right to me. Artificial Analysis says Opus 5 High costs nearly ~3x as much as GPT 5.6 Sol High for a given task: https://artificialanalysis.ai/models/comparisons/claude-opus...
Small reminder that the US government rug-pulled Fable, not Dario. Lots of the safety guards that users find annoying/objectionable were the results of negotiations to get the model back online after the US government forced them to take it down.
Maybe Dario should have just "donated" $1M to Trump's inauguration fund like Altman, Meta, Amazon, Microsoft, Tim Cook, Elon, and Google. There's a reason they are the odd man out with this current Administration.
The US government didn't make the choices to release the worst version of Opus and label it 5.0, and then isolate portions of their subscribers to limited usage of Fable.
They may have been unfairly targeted by the US government, but they are doing more damage to themselves without government help as well.
Maybe it depends on the type of work you do, because for me it almost never happens.
>> You can be 95% complete with the plan for it to trip and then lose it all.
That's... not what happens though. The session will either seamlessly downgrade to another model mid-session, or it will stop with an alert and you can just re-prompt it. It will still have access to the context.
Making a web app secure is literally just finding and patching vulnerabilities, instead of finding and exploiting them. You could have the AI "try to make this app secure", find what it patches, and use it for exploits, and the AI can't know if that's what you're trying to do or not. I don't know how you can get around this. I get around it by not using Anthropic products, at present.
Not to endorse OpenAI's particular guardrails, but unless you're doing something groundbreaking, security best practices should be more than enough for web development.
OpenAI is what I use most. Sol 5.6 still rejects a few requests a day when I'm working on web apps, but, overall, it's not too bad. I wish it'd auto-resume and try again, instead of waiting for me to intervene, but it's rare enough that it's not a huge deal.
It probably doesn't help that I'm using frameworkless PHP - I imagine a lot triggers could be avoided if I was using a framework where secure features were baked in.
While I can't speak for everyone in academia, I personally don't feel comfortable in putting my research questions and outputs to a private website, before the idea is at least arxived. Especially as all the Fable/Mythos prompts are said to be human reviewed.
So I believe that, at least in the short run, we might be seeing breakthroughs in hard open problems or in low hanging problems which are not that interesting to spend time on.
I may be wrong, if some research labs have private contracted access to the models
That’s actually common. Not in academia but a lot of enterprises are specifically not using Fable because Anthropic doesn’t provide a Zero Data Retention mode like they do for Opus. Even at my employer when Fable is available, some employees just aren’t comfortable using it when they perceive that they are working on extremely sensitive research.
The problem is a lack of funding, which leads to excessive competition and ties continued employment to sustained contributions.
Many results are obvious in retrospect, and such results are often the best ones. The difficult part with such results is framing the problem in the right way and asking the right questions. If you manage to do that, the result simply follows. You may still need funding and hard work to confirm your finding, in which case someone with more resources can claim your result, if they are aware of the idea.
Academics have to eat and they're judged on the quality of the research they produce.
They're more likely to share their research then big tech once it's ready and they can get the credit they deserve. This can be used to succeed in future grants.
This feels like an unwarranted strawman. There are plenty of reasons for researchers to share openly at times and plenty of times it makes sense to wait until the meal is ready to serve before publishing.
Does it fix my favorite pet peeve, the overuse of the wrong meaning of "fail closed"?
"Fail open" usually refers to a fuse that opens and kills power, meaning the system is inert and safe on failure.
"Fail closed" is the opposite -- system has power and is live.
Computer security people have appropriated the term but use it for the completely opposite meaning. When your work straddles electrical engineering and computer security the best way to avoid confusion is just to never use the term.
I can tell my Claude to never use the term, but of course now I'm seeing it everywhere in comments from other people and it drives me batty.
I understand fail closed to mean, be secure when in failure. And fail open to be continue to operate during a failure. A door that fails closed would not let anyone in; one that fails open lets everyone in.
But I can see how these are not the mutually exclusive definition the labels imply, especially if you apply the concept to entities that aren't doors or otherwise have explicit open/closed states. It's probably best to just be specific in those cases.
Similarly, open loop vs closed loop seems to trip people up enough that I no longer use it. But the confusion is understandable since "closed loop" being "has a feedback loop" sounds backwards. Which, is the same way it's being used in your fuse example; a "closed" fuse closes the circuit making it live. But it's still backwards from the colloquial usage, even if it's correct in that context.
That doesn't make sense at all. Fail open means the method of it's use is still in use.
Say you have a door that has powered locks. You want it to fail "open" so that when the power goes out, it's still useable, and people can get out. That's the source of the term.
Assuming the guy is for real (the closest relation I have to EE is accidentally electrocuting myself at times), I'm pretty sure they're referring to circuits breaking open or remaining closed, hence the opposite meaning.
Took me a minute as well, cause indeed with a computer background, the meaning is completely the opposite. Just like in other security contexts (door locks).
A recent paper demonstrated how to retrieve decoded hidden reasoning traces. The authors found cases where Claude had memorized the answer but hid this fact from the visible response.
It's getting harder to trust Anthropic's models. Will Anthropic now stop hiding Claude's CoT from users? Deliver the tokens people paid for, and prove the models aren't plotting against them. After all, if the idea was to stop Chinese labs from catching up, it didn't work.
> similar developments in other scientific domains
The classifier is too strict. It's rare to be able to complete a project without being permanently relegated to Opus. I'd expect that the domains where this accelerates progress will be fairly limited.
As someone working in science, this belief confuses me. How (by what means) do you think Fable 5.1 will be able to make further progress in scientific domains? The problem with science is that there is no agentic harness. The agent can't test things. At best it can hallucinate something and ask if that hallucination "makes sense", but this doesn't work in science.
Sounds like a very narrow view on what constitutes science. There are many fields of science where there is existing data against which new ideas can be tested without additional 'real-world' measurements. Newton's theory of gravitation relied entirely on pre-existing astronomical data for which there was no existing unifying theory. He made progress by putting forward a theory which explained that data. Now you can argue that it's not really science unless you include the original data collection and subsequent real-world measurement validation steps. But I'd be comfortable saying that Newton was indeed a scientists and did make progress in science despite only doing what some might say is the 'middle' part of the process. There are plenty of modern analogs where work like this sits out there waiting to be done using existing data.
I suggest you to give a look to the MCP protocol for hardware that is being proposed by Anthropic. The hardware will be the next harness of LLMs, they will be able to operate machines to reinforce their theories.
I still think that a major problem is that biological processes are not “fast” as coding, but they are verifiable. If during post processing we are able to give enough harness to test and verify this kind of environment (maybe via simulation and real data) we will for sure achieve incredible performance also in this domain.
> I suggest you to give a look to the MCP protocol for hardware that is being proposed by Anthropic. The hardware will be the next harness of LLMs, they will be able to operate machines to reinforce their theories.
Yeah, that's called an API. Again.
The actual hard problem that this hand waves is making (and funding the making of) hardware to reliably do the things you need it to do.
How much lab equipment is automatable though? There's definitely some in biology, but if you're doing fundamental research it's 99% stuff you are building yourself with your own hands. Robotics is a long way from being able to do any of that.
that might indeed be a problem for all the pulp-producing labrats of STEM in southern europe and the third world.
However I think this area has so much decoupled from industry and solid research institutions that they might not notice at all (beyond their use of AI-generated slop to augment the slop they already produce)...
When I looked at “Claude Science” which is a beta, separate desktop app, I came away with the impression that it was mostly for biology and a bit of chemistry - presumably there’s some value it can get from consulting obscure literature and uniting disparate threads of already-known stuff, but since I don’t work in either field I can’t speak much more to it.
> As someone working in science, this belief confuses me. How (by what means) do you think Fable 5.1 will be able to make further progress in scientific domains?
The same way it did in the previous versions: brute force.
I don't believe that LLMs have any particular intelligence we don't, but there's an endless list of problems we either don't have bodies to throw at, or the bodies we can throw at it, don't have such a huge large context to crunch problems.
What LLMs will always intrinsically fail at is showing us genuine new intuitions. The technology is about predicting the next plausible token/sentence.
They will not revolutionize human knowledge, but they can definitely widen it a lot.
> They will not revolutionize human knowledge, but they can definitely widen it a lot.
I am generally quite enthusiastic about all this, but my biggest fear is that we will not recognize the extreme need for more scientists at a time when there is so much more science to be done. The rate of scientific understanding must keep pace with the amount of science being output, both for verification and further discovery. It's a pipelining issue, and I predict a stall in the bits that require the (currently rare) people who know what they're doing.
And word on Opus 5.1 for writing style? I am on the edge of switching to OpenAI due to this horrid writing style. If Fable is better, great - but i can't even use that at work.
I'd like to know too, I mean GPTs are in their own class of cringe, but Opus is by far the worst of all Anthropic's models in terms of style, Fable 5.0 was already leagues better.
Docs engineer here. Nice to read about writing style: would you consider creating a writing benchmark at some point? I guess y'all are painfully aware of the load-bearing issues (pun intended).
(I don't work at Anthropic, but I've designed RLVR tasks)
My impression is that especially for long-horizon tasks like science, the harness is much more important than people give it credit for. Claude Code + Fable 5 seems to have a tendency to "give up", get stuck in a dead end, or claim things to be impossible. But using the Fable 5 API together with a custom harness, it'll happily try 200+ variants and fail its way towards the goal.
If you give the AI a way to give up, eventually it will. If you remove that option from the harness, then thanks to the non-determinism inherent to LLMs, you get to explore pretty much all related solution attempts.
Please bring to the other models, and also please only apply the AI text watermarking only to EU citizens. I may not be able to tell when Claude writes about things i don't know, but in CC it writes about my code and it is obvious.
You’re probably better off organizing a campaign to pressure Congress to prohibit American corporations imposing foreign laws on Americans, which is what this text watermarking is, regardless of how you feel about it. I think it’s a precedent we really don’t want to go down if you believe in democracy and self-determination.
It also clearly establishes or the very least moves in the direction that you don’t actually own or control the output of AI in any manner whatsoever, you’re just paying for it since Anthropic in this case can simply essentially brand/tag all your output that is based on not directly your own words, but a higher level process or methods that you use, including your instructions and how you structure your information and what your overall objective and goal is.
Anthropic is branding it on the behest of the EU lew, which already is an entity that is diametrically opposed to democracy and self-determination based on its structure even if you ignore the fact that it violates the most fundamental concepts of self-determination in its direct contradiction of the UN Charter and implicitly the Universal Declaration of Human rights.
What people done seem to be catching onto is that the EU is becoming the world dictatorship because the USA has simply had too many onerous people and that stupid constitution and its amendments that keep roadblocks world domination for the ruling class vampire.
> generated text being watermarked is universally good.
If it worked perfectly, maybe you could make this argument in a vacuum.
It does not work perfectly. (It cannot. It is by definition a heuristic). That means there will be false positives. There is a chance those false positives ruin someone's career. See [0] for just how easy it is to push SotA "AI text detectors" in one direction or another.
Now, with watermarks, instead of everyone to some extent understanding that AI text detectors are wishy washy woo, they are now Anthropic certified to detect an official AI watermark.
With that kind of false confidence in hand, the people who trust the "computer says you plagiarized" machine are never going to believe you when you say "it can make mistakes," they're just going to fire you/take away your scholarship/cancel your grant/...
This is all beside the fact that we should demand our tools work for us and not for some shadowy master. "Universally good," absolutely not.
Watermarking the outputs themselves is very different and much more effective compared to how tools like Pangram work.
Obviously false positives will inevitably happen (even though, they are incredibly unlikely with SynthID), but even still, that doesn’t somehow make good faith watermarking attempts bad.
Also, a watermark doesn’t stop your tool from working for you. It just stops you from passing of its work as yours.
> Also, a watermark doesn’t stop your tool from working for you. It just stops you from passing of its work as yours.
I think we fundamentally disagree on what "working for me" means, but I remain steadfast in saying we should not accept tools that have ulterior motives beyond producing the output desired of them by me, the user.
> Watermarking the outputs themselves is very different and much more effective compared to how tools like Pangram work.
At the end of the day the only artifact is text that you can do statistics on. It's the same problem as today, with the probability shifted slightly more in one direction. This does not assuage my concerns at all.
> they are incredibly unlikely with SynthID
I kept my commentary focused on text watermarking specifically because I agree, a synth ID image watermark false positive is highly improbable. There's plenty of noise to robustly hide whatever you like in an image. Text is simply too capital I Information-sparse and fragile.
> good faith watermarking attempts bad.
I would sooner call it "ignorant faith" (if they don't know what they are emboldening) or worse "don't care" faith (there will be false positives and they accept this to further some illustrious and arbitrary goal of Text Purity). Whether that be to prevent model collapse or help you not waste time arguing with bots online, to me the principled stance of "tools work for the user" wins..
Because the incentive has been changed from the true best output always, to a mix of "close to the best but not always" output.
For the (majority) of us using Claude models for computing as a tool, obviously we're not going to be thrilled that our new tool will perform worse going forward.
I think Congresspeople hearing that EU AI Act is forcing secret codes into the infrastructure of American technology across all industries is sufficient.
> I think Congresspeople hearing that EU AI Act is forcing secret codes into the infrastructure of American technology across all industries is sufficient.
So, you think it's good to disconnect words from their actual meanings (lie) to low-information people! I doubt this will do much to congress, but it certainly teaches us something about the sort of mind who would suggest it.
"this watermark is invisible to anyone who does not have the detection API"
1. This is BS since i can detect it when it writes about my codebase
2. I do not want secret codes being written inside my codebase, or anyone else's codebase that i use. The constraints of how to code why eliminate it from code itself... but there is a lot riding on the word "may". And even if it is just comments, this might explain Claude's desire to write such long ones -- long enough to encode secret messages in out material.
The main issue I have, which is partly connected to writing style, mainly with it dealing with our stupidity. Is that is actually thinks it knows better, and sometimes it does, but often it doesn't and then it keeps telling me I'm wrong and I have to argue with it. Opus 5 is more condescending then Fable, but it still is very tiring. Does fable 5.1 handle this better?
How is it possible that all models from xAI, OpenAI, Anthropic, Qwen etc. win all benchmarks on each release?
Tomorrow all of the above (except Anthropic of course) will bump version numbers and be at the top of HN winning all benchmarks.
Science breakthroughs incoming? First of all, you are already restricting science in Fable, secondly, we have been hearing the same for several years now.
Are the models improving their footprint on the natural world? Data centers and and the natural resources consumed by models for production of materials and for building and running inference servers are contributing towards environmental degradation. How can we prevent that as we continue the roll out so we shift this to a more sustainable developmental rollout path?
Thanks! This is encouraging. I try to use Claude Code for producing client facing presentations that are static html files with charts, tables, and annotations. It never gets the tone correct and phrases things so weirdly - it drives me mad. I have to really fight it to stop it writing insights in a flowery and verbose way
How much of the language style outcome is a well-crafted result vs. being a somewhat unpredictable outcome of mucking with levers and knobs for a while?
I'm really glad for that! And I appreciate that you're making yourself available. I really do. Outreach is amazing. And thanks for making Claude.
I really do love Claude. In some ways, I'm asking this question because of just how much I am grateful for the role Claude has played in my life.
> Fable 5.1 more than doubled Fable 5's Terminal-Bench-Science [1] score, which I think is meaningful.
But my honest question is, can I use Fable like that? Can I use Fable to do science?
To borrow a Claude-ism, this is "load-bearing" because Claude's response has been degraded for innocuous research projects concerning population-level analyses of astronaut health.
These "safety filters" trigger on questions about rabbit sex, smartphone accelerometer data to classify cat purrs, and so much more. What exactly does this score mean for users like me if it's unusable for middle school physics, biology and chemistry?
Second, I would happily quantify it for y'all, but qualitatively it feels like Fable's performance is noticeably poorer than initial release / launch.
And I am wondering if this is the case particularly for me because I use Claude via Claude Code to make a personalized care dashboard for my doctors to help me in managing my care.
"In the case of Fable 5, when a classifier fires, the model re-routes the user’s request to Opus 5, a capable model that does not have the same level of biological capability as Fable 5 and which cannot provide as much assistance to a malicious user. This is the fallback that users see when their requests are blocked."
I hope that I'm off base here, but I noticed that the post avoids saying that the user is informed every time when such re-routing occurs. Would you be open to confirming whether or not this is the case?
Is the end user informed every time their query is re-routed?
Or, can you confirm that there aren't scenarios where a user's outputs are degraded without telling them? I recall that this was something that had been adopted as policy for AI research during Fable's launch.
I sincerely hope that covert response degradation is no longer practised as policy.
Sorry for putting you on the spot, but again, as Claude would say, it's because Claude's load-bearing in my life. ;)
Hypothetically, when the user is asking how to remove fungus from their tomatoes they’re actually growing controlled narcotics. You have been demoted to Jimmy 0.7 model, running at 0.1 tokens per second on an old C64
OPUS 5 is piece of trash and I don't think they would want to build the Opus 5 better than Fable, because fable 5 take more tokens and have 50% limit or runs on credits.
Thank you for commenting here and having the guts to face the nerderati!
I'm a Claude Max user. I've never been able to use Fable as my work in medical physics involves both particle physics, biochemistry and biology from Python bivitticus to clinical medicine. I am not a US citizen and work in Europe.
Will Fable 5.1 work on any of my problems? Fable 5 refuses outright. Is there anyone I can ask for a review or adjustment of the safeguards? It doesn't seem so, but with Opus at least I'm pretty sure I can infer lots of your training data from now precise they are. Fable is basically useless infuriatingly. I'm just finishing a proper clinical trial in ovarian cancer and trying to make a simulation environment related to our technology.
> More work to be done (and we will!) but reading better prose makes me so much happier.
I assume this work will be done for Opus as well? Opus has seemingly gotten progressively worse at its prose and technical writing with each version. I've stopped using Claude entirely for now, because it manages to turn even the simplest technical explanation into the most obtuse and obfuscated word salad imaginable. People originally adopted Claude because it felt pleasant to use in comparison to ChatGPT, but I feel like that's really been lost (at least with the Opus line).
I feel dread when I see a wall of text generated by Opus. Every developer I've talked to feels similarly right now.
Yeah, it's like day and night. It used to be really unpleasant to interact with early codex versions. Even 5.3 wasn't great. Now, I go to Sol if I need to discuss anything. I don't even bother with Opus because I know that it's going to give me a headache.
My initial impression is one of massive disappointment. The main issue was that Fable was unpredictable and prone to false positives by the safeguards. In my brief testing, it still seems completely unable to understand its own guardrails and will readily reason itself into triggering them. It claims it won't do so beforehand, and insists that the topic in question is perfectly OK. Regardless of how good the car is, I'm not comfortable buying or driving it when I know it can randomly and unpredictably explodes. So yea might be good, but you never know when it refuses to help… still.
well no crap right? Except I submitted for an exception, even sending my linkedin and using a company email address. it should be extraordinarily obvious we own this code.
Well your CEO went on X saying you will cure cancer, and since it's always a 6 month rolling window with him I can only assume humanity will be cancer free before next summer, amazing!
I share this sentiment, I really did like the models... then the finger printing, encryption of thought traces, staggered access, the constant NO's from Fable on cyber related issues for looking at bugs in my own code... I'm glad I swapped to Kimi/GLM... now with the deepseek harness, I don't even miss Claude Code. I really hope open models give them the market reckoning they wholeheartedly deserve.
I've not, but really should. I run it on exe.dev, it's an ephemeral VM company and they have an agent of their own called shelley (which I used locally as well), Having kicked the tires on DSH(deepseek harness), I ported Shelley's skills into DSH, they are pretty simple text files that were easy to bridge over, it is more verbose but the plugin nature of it was really easy to extend, for example, I built a plugin that checks my claude usage windows and when I get to 80% stop asking new agents for help.
> I think Fable 5.1 is a big improvement in writing style
You think or is it better? Or you just YOLOed the model out?
> and responds to my style instructions more reliably.
Yeah, yeah. Previous models wete also advertised as "being reliable". To the poibt @bcherny "released" a new style that was going to reliably make Fable sound better.
> Another point I expect not to get much attention until it all happens at once is science.
You mean "your request to use unicode methids is flagged as unsafe bio research"?
Too bad. I see the stereotypical prose as a good thing. When I interact with Claude myself, I don’t mind it as it just feels like Claude’s distinctive voice. But when other people try to disguise LLM output as their own thoughts, the voice makes it easier for me to tell.
People that want to be open about the source of their text will just tell you where it came from.
People that want to obscure the source of their text would rather that it was more difficult to sniff out LLM-generated text. And they're the ones picking which model to use.
Took just under 14 minutes to generate, and at 65927 output tokens cost me a hefty $3.30!
Excerpts from the reasoning trace:
> Adding pedal shapes near both feet, with the far foot on the second leg partially visible behind the frame. I'm considering whether to add a small scarf or cap for extra character, but leaning toward keeping it simple to avoid clutter.
> Now I'm debating a bicycle helmet on the head versus the pelican's signature crest—the beak and pouch already read clearly as "pelican," so a helmet could reinforce the bicycle theme without losing identity, though it might compete with the crest for visual space.
> I realize the beak at (484,84) would overlap with the dome helmet, so I need to shrink the helmet so it only covers the top of the head, adjusting its arc endpoints to sit higher and narrower so the beak can attach cleanly at the front without collision. [...]
> I'm adding a darker tip region to represent the primary feathers, then reconsidering the trailing edge to include scalloped feather curves instead of one smooth line for a more natural look. [...]
> Now I'm checking the vent line placements on the helmet, making sure they sit far enough inside the helmet's edge given the stroke width and rounded caps, and confirming each vent stays within the helmet's circular boundary. [...]
> I decide skipping a handlebar bell and tire highlights since they're unnecessary additions. Now I'm reconsidering the front fork's curve — the current control point pulls the shape backward when it should bow forward for a proper rake, so I need to shift the control point rightward to fix the fork's lean.
This is a notable result because most of the recent Claude models have been pretty bad at drawing pelicans, at least when compared to models in the Gemini or GLM series.
how about trying to draw an airbus a320 in 3d space using only one brush tool that can be moved to specific x,y,z coordinates (and its color, size & hardness can be changed). i think fable 5.1 did quite a good job (reasoning high, cost $0,261): https://files.catbox.moe/umx102.png
Unfortunately it demonstrates effectively zero reason to use this model over, say, GLM 5.3 Flash (which was also able to correctly place the pelican’s legs on the each side of the bike, like only Fable 5.1 xhigh was able to do here)
The price reduction comes from the cache read pricing falling from $1/M to $0.25/M, which means that Fable 5.1 now costs half of Opus's cache read costs ($0.5/M).
This gives a lot of credit to the theory that Anthropic did not get much bite on Fable at its original pricing, which in turn likely places a ceiling on LLM pricing in general.
Interestingly also, if you take away terminal-Bench-Science 0.1 results, it is hard to see ANY improvement:
Terminal-Bench 4.0: Fable 5.1 is +3.5% vs Opus 5.
GDPval-AA v2: +1.5% vs Opus 5.
OSWorld 2.0: +2.5% vs Opus 5.
Humanity's Last Exam (with tools): +1.6%
Keep in mind that this is supposed to be an entirely higher tier of a model than Opus 5. For one tier up and one version up, these are not really improvements. Probably leaves no room to place Opus 5.1 anywhere. Combined with the fact that they are selling 'readability'... Has frontier progress finally stalled?
I'm a heavy user and fable is great the #1 reason I stopped using it was the horrible safegaurd filter. I found sol close enough in capability and have only been blocked when my request was an obvious offensive cyber work. Fable blocked me on almost everything.
Optimizing a OS build? -> block
Securing a container -> block
60% is nowhere near enough for that safegaurd system. This just means I am going to be blocked half as much? Any long running task will likely get blocked.
Say you give a single big prompt and fable goes off for 6hrs of work. At hr 5 it gets blocked you now have the option of a much dumber model taking over and wrecking it or losing the entire 5hrs of work. That risk is beyond terrible and deffinetly not worth a 5-10% percieved improvement on my end. I previously would just bring sol in when that happened and realized sol is stupidly close in capability.
It wouldn't surprise me if we start to see minimal performance gains from incremental changes to base models. It seems like the gains from the Opus 4.5+ incremental updates were a result of Anthropic learning a lot about post-training, the gains from RLVR, etc.
If new post-training techniques are seeing diminishing returns, we could just be back to waiting for new large pretraining runs at larger sizes for gains (even if those ultimately end up getting distilled down into smaller models because the economics for serving anything larger than Fable isn't practical).
it seems to me that OpenAI is the only actual lab that truly understands reasoning. they have the best reasoning efficiency, they get pretty uniform improvements with more reasoning compared to other labs. (theres been plenty of graphs where models do worse with more reasoning), and i suspect their models are a lot smaller than we think.
i think the next gen of openAI models are going to be quite insane tbh.
From Artificial Analysis cost per task, it looks like Fable 5.1 (max) is more expensive per task than Fable 5 (max)? Cache hit price went down, but the other components still add up to more.
Edit: 5.1-xhigh seems to be cheaper than 5-max, and 5.1-xhigh has a higher index score than 5-max. Also interesting that Fable 5.1 (high) is comparable to Opus 5 (max), but nearly half the price.
Interesting, even if we were to ignore the cache-hits, reads and output, the reasoning cost (aka test time compute) per task should remain a fully comparable metric - it went from $1.25 (Fable5) to $1.48 (+18.4%) for an improvement significantly lower than 18%.
I would expect the benchmark scores to be nonlinear near the top, as the easier tasks get solved and the harder ones are left over. So going from 10 to 15 would be easier than going from 60 to 65.
I only take the Intelligence Index value roughly though. Considering they put Opus 5 (High) at the same level as Fable 5 (Max), I don't trust it that much.
> This gives a lot of credit to the theory that Anthropic did not get much bite on Fable at its original pricing, which in turn likely places a ceiling on LLM pricing in general.
Does that mean that generally available intelligence is now constrained by Moore's law? We have to wait for the actual price to come down.
Looks like all three breaking changes are patches for inadvertent chain of thought disclosure. Someone found out (don't have the tweet handy) that if you created a bogus "think_deeply" tool and then forced the model to use it, it would output what is believed to be its raw thinking there - I believe the first breaking change stops this. The second two are aimed at people getting Haiku to repeat thinking blocks from other models verbatim (since it can see the decrypted version). I get that in their eyes it's an "exploit" but still kinda disappointing that they patched this
These draconian "Preserved Thinking" measures they're taking are going to be an absolute pain in the ass. This alone is enough for me to move our API use off their platform entirely. It's a HUGE breaking change that they're trying to dampen by having it not affecting current customers until "in the future", see: https://platform.claude.com/docs/en/build-with-claude/preser...
You're no longer allowed to edit the context anywhere! The whole context is to become append-only, says Anthropic. No more editing the system prompt as the conversation progresses, no more dynamic loading of custom tool calling formats. Everything has to go through their built-in tools API and you aren't allowed to mess with anything in the context if it has any thinking blocks following it. This is the most intrusive "model DRM" we've seen so far!
> No more editing the system prompt as the conversation progresses, no more dynamic loading of custom tool calling formats.
Hm, aiui you can support both of these via mid-conversation system turns https://platform.claude.com/docs/en/build-with-claude/mid-co... - and in general you'd want to to preserve the cache and recency of the instruction anyways rather than frankensteining an off-distribution transcript. Not sure though.
To be fair, I assume they want to hide that not from their customers, but adversaries who use the way Claude models think and reason to refine their own models.
I have a hard time believing whatever prompts get Claude to reason can stay relevant secret sauce for long anyways. It’s not hard to A/B test something that gets you close enough, and it’s not Ike anthropic has uncovered the global optima of reasoning prompts.
I don't really want the models I use learning from Claude at this point. Open weight models of similar scale are available now too, so I expect this "distillation"/"stealing" chatter to wind down.
distillation is a minor piece of training data, you have to have a good foundation for it to be helpful, and even if you have good traces, you need a good RL reward scheme at the point it is used (very challenging)
Anyone ever seen the SouthPark episode making fun of Game of Thrones: A Song of Ass and Fire? Anthropic's announcements reminds me of "The Dragons Are Coming" running joke.
What they have done:
* Nerfed Fable, as many of noted it's useless
* Leverage Mythos as a marketing strategy, claiming its too good to release
* Removed thought traces, one of the only useful things to make sure your prompts are working correctly
* Continue tons of hype about how good they are without delivering, going to great lengths to publish how their model "hacked" its way out of a sandbox they misconfigured.
* Push a bunch of EU Overregulation onto the rest of the world with text watermarking, decreasing quality of answers
Last year, they were at least focused on making improvements. Nowadays its just a bunch of handwaving at the church of how good they are.
The only saving grace is Opus 4.6 is still available. Just sucks we haven't seen any measurable improvement, despite all of the ceremony.
I certainly don't take AI advice from HN, but this is amazing.
Useless? Yes, the safeguards are ridiculous and obnoxious, though I can say that 5.1 greatly relaxes them (just doing a hardening of a project parallel with this comment, which 5.0 refused to do...so did Sol and Gemini, fwiw. The Gemini one is a laugh, because 3.1 pretending like it's a dangerous tool is simply ridiculous at this point), however Fable is extraordinarily useful.
It is, far and away, the most powerful programming model, in my experience. Like, crazily so. It absolutely annihilates Opus 4.6, which I mention given the incredibly weird reminiscing people are doing here.
And for that matter it humiliates Opus 5.0 as well. Opus 5 somehow seems like it's neck in neck in the major benchmarks, but there is simply no reality where that is true. Opus stumbles over everything that Fable just blazes through.
While I also agree that Opus 4.6, in some ways, was the last model that truly felt an assistant, all the following ones seem to have inverted the role, even a blind person can see that throwing difficult problems, and complex bugs at this model achieves more than predecessors.
I don't think there's nothing ground breaking, but sure it achieves and finds more, sooner.
(not op) It cannot be used to develop applications. Every application needs to be secure in some way, and any such mention in a review triggers Fable's upsell feature.
Agreed. I was trying to get it to review some auth refactoring in my app recently, and it appeared to find some vulnerabilities. as it was aggregating the results it was flagged and restarted the whole process with Opus 4.8 and all of my usage credits were gone.
Anthropic told me to use their `security-review` tool - as this was the exact scenario the tool is for - and it still got flagged.
The improvement is compounding just about every way you can look at it. The frontier keeps getting smarter. And at any sub-frontier threshold the cost is dropping dramatically. The amounts of smarts you can fit on hardware is increasing so dramatically that even 6 year old consumer GPUs are increasing in price. The pace of change in LLMs and downstream applications is absolutely ripping compared to 2023 or 2024.
I am finding that I am now less interested in better models than I am in token budgets. My issue with Anthropic models now is that I don't feel like I can rely on them as a daily driver because they'll dry up before my quota resets.
I am becoming dependent on AI to make a living, and I need predictable spend on it. If I know I can't use a model regularly all month, my enthusiasm is limited.
I urge Anthropic to get better at this aspect of their business so I can come back to it.
I'm with you, for what I usually do most models are already more than enough.
What I'm really keen on is better auto-reasoning so I don't have to constantly have the constant inner debate on which reasoning effort to pick for each task.
I seriously hate the none-low-medium-high-xhigh-max-ultra etc that we have now, with companies frequently recommending different ones on each new model release, etc.
It's apparently called Adaptive Test-Time Compute or Dynamic Test-Time Compute and companies are apparently working on it (according to some LLM :shrug:)
Agreed. The area I think will become more prevalent in the future for organizations are cost per intelligence -- effectively efficiency. An unoptimized model that costs 90x more than another that is only 10-15% less intelligent is something I would say is not a good deal.
“ Claude Fable 5.1's writing is generally a step up from earlier Claude models, with fewer stock phrases and less unexplained jargon. In some cases, though, its prose is denser than Claude Fable 5's: sentences run longer and there are fewer paragraph breaks.”
I cancelled my pro max Claude subscription last week; codex is much more succinct. I am curious if this is getting better.
I don’t think Anthropic realizes that humans have a token limit too and it can be exhausting to read Claude’s output. Prose density is not the same thing as succinctness.
One thing I've noticed and HATE, is that when you increase thinking-effort, that seemingly increases response-length. Meaning that X.High is longer than High, which is longer than Medium, etc.
Which is kind of the inverse of how people work; a really smart person can condense difficult ideas into simple[r] terms. Whereas people who struggle speak a lot but say very little.
High/X.High do seem to deliver better quality results, but it sometimes feels like needle-in-haystack extracting that from the word vomit.
With LLMs, you're still mostly read things "off the tip of the tongue". A better comparison is observing a smart person talking to themselves while working on a tough problem.
EDIT: also there's a reason the dial is called "effort", not "smarts".
I don't think smart people generally solve problems by talking through reasoning steps at a mile a minute. They clear their mind and let the solution come.
Of course I don't know if there's really a way for this to be molded in current LLM's (sounds more like diffusion)
I just go over the comments with Gemini 3.1 Pro at the end which has a much more normal "voice" and it doesn't lose nuance as a cheap model would. I don't care so much about what Claude writes during the debugging as I just do all the cleanup at the end instead of at every commit.
The higher the effort the more things Claude checks, and it's eager to tell you about all of them
See, this insight it had early on looked like a red hering for a while, but then turned out to be load-bearing. And that's not just a difference in semantics, it changed the whole conclusion (spoiler: it didn't). And Claude is very eager to tell you about this exciting journey
Sometimes Opus 5 (high/xhigh) feels like I'm dealing with the programmer equivalent of Zeno of Elea.
Every time, without fail, it would get me 90% of the way there and then leave a small note, exception, or deferral. When instructed to address that, Opus would somehow take nearly the same amount of time as the first 90%. And then it would finish with yet another deferral. Repeat ad infinitum.
You can sometimes get around it using the `goal` directive provided you are not subject to the constraints of mortality.
They got that from Anime seasons. Every prompt has yet another cliffhanger to keep you hooked. But the Season II story arc where Claude-chan fights the NsPasteboard boss battle on the journey to the UIViewMainController, I thought that was pretty intense. I guess I just gotta keep watching my terminal to see what happens to the main character input - rooting for him to survive the next season, but you know they always kill off the good input characters early.
Yes and the last bit is always mysterious and inscrutable. I have to think way too hard to figure out what the actual problem is. I’ve noticed it does a lot of explaining the mechanics of the problem it found, but almost never explains why it’s important until I ask.
And the worst part is that this little problem will keep sneaking into the context of future sessions, unless you spend the time to fix it. Even if it isn’t important, I’ll sometimes have Claude fix it so it will shut the F up about it going forward.
i think they took a huge bet that speaking like a ted talk was going to be a vast popular differentiator in their offering, i don't think they anticipated that people were going to make fun of it, that it could become a meme..that it could get in the way of getting stuff done and result in cancellations.
it's downright exhausting to read claude, the language style was a regression imo.
I wonder if I can make a tool for it to write messages back to me, say that it can only speak to the user through tool use, and then put a hook on that tool to prevent any of the Claude-isms
"Humans have a token limit too" - that's so good and it explains so much of the fatigue that myself and colleagues/peers have about Claude in particular.
I think it's not just token limits - I think it's because it's so _dense_.
You get a week of research and debugging and testing compressed into a few pages. Even if it's explained well, it's just so much information.
And since it's AI, I'm constantly second guessing "is that really true?" and it's exhausting.
I've developed a habit of adding into my prompts "please keep your response concise and succinct" or "I'm trying to cram, please only provide the minimum level of technical detail necessary to understand this topic"
I find it helps immensely but it'd be nice if I didn't have to do that.
I don't understand that complaint, although it seems to be a common one. The whole problem with the way models talk nowadays is that they are succinct to a fault, going to the extent of coining new buzzwords and misusing existing ones. What I want to see is a shift towards plain language.
why so many people add 'please' when asking machine to do something? Was there actually research that when you SCREAM or curse it follows your instructions better?
P.S. Although my wife insists that I should stay polite in case AI overlords remember how I treat them ...
Probably because polite people are already in the habit of saying please when typing out requests in chat. We're not consciously thinking about it, regardless of whether a human or machine is on the other side.
I think about removing please/thanks, but then I accidentally add them back in during some edit/rewrite of the prompt... It's just how I'm used to asking for things
Not to go all ying/yang about it, but just to give a parallel: https://en.wikipedia.org/wiki/Loudness_war - you kinda need silence to draw a contrast with what's meant to be loud.
Separately, my boss confided in us that he's super abusive with his agent, wondering if we are too (no, lol). While I try not to read too much into this (which he doesn't make easy), I also can't help but not really notice a whole lot of amazing agentic delivery differences from his side. On the contrary, while the passion may improve his agent's performance, I'm not sure if it doesn't decrease his, upending the entire theatre.
Amen. I would trade some stupidity (say ten points on any benchmark) in exchange for a version of Opus or a similar model that actually gave me direct, concise answers.
You should try setting claude code to opus 4.6. With the style instructions I set in my user CLAUDE.md it does exactly that. It's like night and day: Opus 5 gave me a page and a half of word-vomit, yet the exact same task and prompt with 4.6 and I got maybe 100-150 words total, entirely readable.
x2 on opus 4.6. still works great, and it's fast. opus 4.6 is where i hope local llm's get to someday, that's kind of my personal benchmark for where "local is more than good enough i dont need these idiot large-scale service providers"
Yes, and they will work ... for like two turns, after which Claude will go back to its usual wall of text.
And yes you could add context (memories, rules, CLAUDE.md entries, etc.): they won't help (for long). Same for hooks that remind Claude to be concise: it gets "attenuated" and starts ignoring any such instructions quickly. There's also writing guidelines ... but they're basically just more context with slightly higher weights (ie. Claude will still ignore them).
I've even gone so far as to make a hook that identifies long responses and requests shorter versions (which is challenging in itself, as you need to run another lower-powered model to evaluate how long is "too long", as what's "long" when the expected answer is one line is different from what's expected for a ten line answer). However, that just shows you the long version, then some hook text, then (10-15 seconds later) it shows the short version. So I created a proxy that hid the long version/hook text for me ... but I had to abandon it because all that used up so much usage I was running out.
I'm fuzzy on the details, but Caveman somehow "hacks" Claude in a way that gets past all that ... but it takes things too far in that direction, with "cave man" speech that sucks.
I switched to using Codex for the last two weeks, and while the prose has been better, there have been a lot more technical oversights. I'm now having fable review codex commits and it finds deep issues. I'v also done the reverse where opus/fable do the work and then I have codex revise all of the prose prior to reading anything myself. This has also been effective; I'm not sure which is the better approach.
> In some cases, though, its prose is denser than Claude Fable 5's: sentences run longer and there are fewer paragraph breaks.”
This sentence reads like Claude wrote it. Perhaps it did, or perhaps Claude has learned to write like the folks who work at Anthropic?
(Had I edited this, I would have said that a colon is not the right separator here. The second clause does not _explain_ the first, per se, bur instead expands upon it. Consider instead: "In some cases, however, its prose is denser than Claude Fable 5's, with longer sentences and fewer paragraph breaks.")
You can change CC's output style (https://code.claude.com/docs/en/output-styles). You can also put style notes in your global claude.md. I've instructed claude to treat me like I have adhd, get to the point, and be succinct, ... More or less eliminates the problematic prose.
I took time to figure this out after Fable spat out "...then stays purely as cascade-debugging provenance rather than load-bearing arbitration."
My experience with output styles for long-running sessions is that Claude starts to forget the terse output style by the middle of the context window. Obviously I don't know if 5.1 suffers the same fate but I ran into this issue with both Opus and Fable 5
That sentence is fine; it’s tolerably annoying. As a long-time HN reader, HN is full of this kind of performative erudition and I’m already used to it. Fable probably learned from the worst parts of HN.
My biggest frustration with Anthropic with Opus being too verbose is that they tried to put this on users. It’s pretty clear that Anthropic employees don’t use the day-to-day models that everybody else use. They have access to the next tier model so they don’t see the problems that everybody else is dealing with.
Same, currently on a mix of Kimi Vivace (K3), GLM Max (5.3 and 5.3 Flash) and OpenAI Max (Sol and Terra mostly).
I will say that Kimi feels nice but slow, GLM feels faster but has limited tokens (even off-peak) and OpenAI is nice and fast but has limited context (258k shows up in Codex, really).
Neither of them are perfect, but I prefer their type of prose across the board to what Opus 5 and Fable 5 kept outputting. I'll probably check out Anthropic again in a year, but for now I need a break from its brand of slop. Oh also all of the other ones allow usage in OpenCode with their subscription plans.
> In some cases, though, its prose is denser than Claude Fable 5's: sentences run longer and there are fewer paragraph breaks
that feels like they just blocked words like load-bearing but can't actually fix the real problem. The insane word slop density and run on sentences was the real reason it became annoying to work with claude, colored with way too many analogies and pointless linguistic comparisons.
Same here. I still have access until my account churns but Anthropic has huge issues comparative to everyone else with token / usage burn down. K3 Swarm also delivers better results than Fable at a fraction of utilization. The Pro plan is definitely not worth it anymore and if I do want to burn some money I can always just leverage the API. But Anthropic went from simply amazing last year to a dumpster fire in less than 6 months for my use cases, anyway.
Just the other way I was thinking that if I asked "What does Lamborghini do?" the only correct way to answer is a single sentence "Which Lamborghini are you referring to?".
But LLMs will fail at this question: they will tell you about Lamborghini's latest car and mix some history in it. Just try.
Which is the wrong answer anyway, because there's at least two major companies called Lamborghini, one making cars, one making agricultural equipment and at least one famous person (Elettra) with that family name.
This very simple test/question makes me realize how much do I hate LLMs in a sense: while I agree that the answer it gives is the most plausible for 90% of the users, it's ultimately both wrong and long. And that 90% compounds.
But there's no "correct" answer in my eyes than "who are you referring to?". Possibly without listing all the possible Lamborghinis.
I just used it to do a review of a ~100k SLOC codebase that Fable 5 / Opus 5 largely built, cost like $2 and caught some good stuff, but more importantly, it communicated very directly and was pretty light on bizarre metaphors. No "let me read the source before opining" type verbiage launched at me. Honestly night and day for me vs before.
Today, Opus talked about "rotation slabs" in relation to logging. (and not log rotation). I didn't even bother asking what that was supposed to mean and switched over to Sonnet.
AI is really not "just software" anymore. It is able to discover facts and advance science. Hard to disagree that we're near or at the point where Artificial Intelligence has expanded reality into 4 quadrants:
objects that are not alive: dust, rocks, water, wood, hats, lego, aluminum, etc.
objects that are alive but not intelligent: trees, mold, staphylococcus, cancer, grapes, etc.
objects that are alive and intelligent: cats, Stephen Hawking, dolphins, crows, dogs, elephants, etc.
and now intelligent but not alive: Fable, Grok, GPT, etc.
I’m very excited to see the actual improvement in writing style. The denser writing style probably won’t bother me.
Anthropic seems to be listening to community complaint on HN about how the writing style is grating. And apparently the solution from Anthropic is to add this block to every conversation!?
> Mannered prose substitutes metaphor and flourish for direct statement. Instead of "a parameter worth varying," the mannered writer produces "a dial worth turning." Instead of "this point still matters," they write "this point earns its keep." The phrases exist to display the writer, not to convey the idea, and readers can tell. That is why mannered prose irritates: it makes the reader work harder so the writer can perform. It is also imprecise. Metaphors drag in connotations the writer did not choose and cannot control. The fix is to say what you mean. When a literal phrase is available, use it.
"Price. Fable 5.1 will cost an estimated 25% less than Fable 5 for typical workloads, wherever usage is billed by token. This is because we’re reducing our pricing on cache reads (where the model reads inputs that have already been processed and stored). For highly agentic work, the savings will often be much larger—up to approximately 45%."
The big issue they face right now is that vastly cheaper open models are proving capable for more and more uses at cents on the dollar.
This is the right direction, but they aren't going to get there fast enough.
They will list, investors who don't know anything about tech will buy, the world will realise that China just put out a model that is good enough at a fraction of the price, they will crater.
> For example, in testing by the investment firm Millennium, Fable 5.1 found the cause of a rare crash on their internal systems that none of their engineers (or any other model) had been able to explain after several years of trying.
Say what you will about LLM-generated code, but stories like this give me hope that software will never be as buggy as it once was.
I think bad software has the possibility of redemption with rewrites and re-engineering efforts. For those of us who are license locked that's probably never going to benefit us :(
That kind of one shot capability is impressive but how does it work for my typical work style? The way I work is to build a huge roadmap with goals and hand it to my agent to execute (often over night). I don't care that much about the benchmarks, what I care about is how often Fable 5.1 is making a baffling decision and destroys my plan, not respecting stop conditions or goals. I would seek for behavioral reliability over long autonomous runs, not eval scores. Anyone have that kind of feedback and observations?
the budget for allowing a single engineer to deep dive on a bug that is annoying but also not bad enough that you can live with it for years is pretty big. $10k a month or more. My budget for Claude is $200/mo.
I sometimes have that feeling too, then ask another LLM to do a code and vulnerability review and OMG: rookie mistakes, over complications and security gaps even a 1st year student would not make regularly.
So.. one more year of untreated bipolar AI psychosis I guess..
I think these kinds of comments really need to say which LLM that is. There's an enormous difference in skill between the frontier ones and say the Google search AI.
We will have more bugs. Even the best models with the best software engineers will produce bugs. There are two reasons : first the pressure to produce more and second LLMs will always produce slop
I downgraded from the 20x today after learning that 20x only applies to 5 hour usage. I have barely used Claude/Claude Code in the last month and am considering downgrading further, even after this update.
Kinda surprised not to see their next update being an Opus 5.1, even if its minimal changes, they've already had to address it with the concise mode or whatever.
So my current usage as a Pro subscriber... Not able to even consider using "Sota" unless i shell out for 100$ a month, (lately i've been a bit burned out i am literally struggling to use 50% of my pro plan per week). Beyond that, I have given up entirely on the top Opus model and reverted back to 4.8. If i have work i deem somewhat complicated, i now have an openai 20$ sub, and i just toss out sol after planning with 4.8. Both subscriptions not anywhere close to capping my usage per week, one of them says i can't use their Sota unless i pay for 5x more usage, and the "best" model they do allow me to use, they are neglecting and its by far the worst model I've interacted with in 2026.
it just doesn't interact good with human beings, and it leaves incredibly strange long winded comments within code filled with session context that will likely not be relevant later on.
Also always seems to have this annoying tendency to leave "questions for you" at the bottom of every output.
Just a high friction human interaction type model, imo should never have even been released, regardless if it scores better on whatever tests, its a horrible experience and a downgrade over past models.
- It's extremely verbose and often incomprehensible when doing even basic tasks. Like it'll write a giant jargon-filled essay then end it by asking for a judgement call on something that references its own convoluted jargon.
- You can ask it to do research on a topic, and it'll just straight up be lazy, pretending it's really digging deep to find stuff when actually it's just grabbing cached SEO snippets off a search engine.
Fable 5: I give it work, it tells me things that are true and that make sense, it does good work.
Opus 5: I give it work, it makes false statements and draws weird conclusions, I correct it and get it on the right track, it thrashes around but gives me something working though usually buggy.
5.6 Sol is probably on par with Opus 5 on ability but at least it doesn't waste as much of my time.
I am using Claude and Claude code for my own amateur history project. I'm enjoying how it constantly reaches dead ends, and I can reframe the question and get more results. I am starting to get concerned that AI and me are so compatible, that I might not be a human at all...
I also like that, because I'm too lazy to write stuff up, Claude code can keep the current state of research published on my site. It makes running a hobby site a dream. "I just found these pictures. Add them to the site for me". And up they go, resized and all. What a dream of a way to work. "Some of links in this article are dead, run through them and check, and see if you can get an archive link for me if they don't". It's like sending a Teams message to my PA.... which I don't have in real life
Whole-file rewrites for small changes. When editing text files, the model is more likely to rewrite the entire file than make a targeted edit. The result is usually the same, but the rewrite costs more output tokens and time.
So we are to catch that somehow? And then add their recommendation (below) to our prompts?
If Claude Fable 5.1 rewrites whole files for small changes, append the following instruction to the system prompt or the first user message. Claude Fable 5.1 is more likely than Claude Fable 5 to rewrite an entire text file rather than make a targeted edit. The resulting file is usually the same, but unless the file is short or most of it is changing, a rewrite costs more output tokens and time. The instruction brings Claude Fable 5.1 back in line with Claude Fable 5 for small and medium changes.
> The number of tokens used to edit files is best minimized, all else being equal. Therefore, when it will not affect the end result, try to surgically edit a file rather than rewrite the entire thing.
That's actually kind of wild. I wonder if part of this was done to catch out people using 3rd party harnesses, users might notice them costing more than Claude Code.
My main gripe with LLMs is the cringe AI phrasings that they use in UI elements. Pompous things like "Your keys, supercharged" or weird yoda-speak stuff like "searches the app remembers" instead of just naming the thing "Learned searches".. you know, proper GUI copy like it was done for the past decades.
I jumped when I saw a mention about "writing style improvements" so I gave it a try on a recent feature in rcmd [0]. I prompted Fable 5.1 to find these wordings and propose simpler plain language.
For context, I recently worked with Fable to give users a way to fuzzy search and focus any browser tabs, terminal panes etc. but the UI was still a prototype full of AI writings.
It took every string including the ones I already rewrote by hand, and proposed even more weird LLM speak. Like for "Left Command conflict detected" it proposed "This keyboard can't tell left from right".
It's a very capable coding agent, but I can't understand how it can be so bad at writing. Where are all these verbal tics coming from and why is it so hard to get rid of them?
> Where are all these verbal tics coming from and why is it so hard to get rid of them?
It’s a side effect of post-training for effectiveness and efficiency at technical tasks.
Over time the models learn to pack as much information as possible into their available context window, because that’s one way to increase the effective intelligence.
Humans do this too with industry jargon, dense tech-talk, etc.
We have a limited capacity so packing it densely maximises what we can do with it.
If you’ve ever heard a “non technical” manager complain about the
terminology in an IT meeting — this is why.
Yeah that was what I was most worried about when I read the top comment here. I found the use of language a feature not a bug. I don’t care how good it reads. If I can communicate with it concicely it’s enough to get my work done. I don’t hate the language for copy either, but yeah different users, different problems.
Makes sense. Then maybe we would need a separate simpler LLM trained on UI copy and good UX to decide this stuff and let frontier models do the implementation.
But who has both the compute power and the motivation to do such a thing?
I guess I'll just continue rewriting the UI one word at a time for the time being.
What I don't see in the comments: "I had a specific problem I couldn't solve with the previous version of this LLM. But the improvements in this version unlocked the solution for me."
What I do see in the comments: subjective improvement in text generation, possibly lower cost, some optimism about code generation, but some skepticism too.
I use coding agents. To me they are very useful. But what I spend on them isn't going to support trillions of dollars in investment.
I had two sessions this morning that prior fable and sol sessions were stuck on, where iterations just resulted in _different_ bugs. (One kind of tricky fe layout problem, the other was a backend refactoring that was complicated by trying to aggregate a couple prior sessions that crashed).
I summarized each into new fable 5.1 sessions, and both seem to have arrived at reasonable solutions that only need a few nits revised before they are commit worthy.
We rarely upgrade our phones or MacBooks because the newer version can do something the previous one literally couldn’t. Often it’s the efficiency, speed, battery life, etc, combined, that lets us push the hardware further.
I get your point, but we can only have groundbreaking leaps once in a blue moon. That doesn’t mean incremental improvements aren’t useful.
All the benchmarks in the world don’t matter if the subscription forces you into a walled garden of slopcoded apps. I’ll stick with Codex and, increasingly, open source SOTA models.
I notably had an issue that it wouldn't work on a "remote execution" (running a command over SSH) coding problem until I did a sed to remove the word "execution". Incredibly dumb. I'm not doing any murders. Easiest to just switch to the Chinese models.
I think a lot of CTOs that signed enterprise contracts with Anthropic are going to be in for a rude surprise.
It's one thing to generate some code and ship it, but it's another when your developers don't understand said code and it brings down production. If the model refuses to assist debugging the problem because it triggers some safety mechanism, you might be fucked.
> We’re introducing Claude Fable 5.1 and Claude Mythos 5.1. They’re the world’s most advanced models for coding and knowledge work—and their research capabilities offer an early glimpse of how AI models will contribute to scientific progress.
I'm not an emdash hater but this isn't how you use them. It should be a comma.
Emdashes and commas aren't interchangeable, and your example there demonstrates one great reason why. The emdash establishes a discontinuity rather than one thing flowing into another, which is why the tomatoes don't merit one but the Ferrari does: you are using the emdash to emphasize the situational irony.
Going back to Anthropic's post:
> They’re the world’s most advanced models for coding and knowledge work---and their research capabilities offer an early glimpse of how AI models will contribute to scientific progress.
The first thing directly implies and flows smoothly into the next---or would, if not for the awkward emdash. There is no discontinuity, no twist or shift in context, no implied question and provided answer, no punchline. It's just distracting.
Yes, I know what an emdash is---I've been using them in my writing since long before they came to the fore of the AI writing conversation. Anthropic's use of the emdash in the fragment I quoted is clumsy and reads poorly relative to the obvious alternative, a comma.
I didn’t mean to suggest you don’t know what an em dash is. But you said “this isn’t how you use them.” And my response is: actually, this use of them is totally fine.
it got want to use em dash. but decide: do? q is if appropriate. check martian websner blog. verdict yes---emdash + comma interchangeable---proceed---judgment superficial however no desire dig deeper style irrelevant effect on reader irrelevant meter and rhythm irrelevant restate equivalence with comma established::chain unbroken::consider semicolon? consider ellipsis consider comma consider sentence break all no. preference for emdash est fiat. and all nail shapeds are for hammering.
> In part, this is because Fable 5.1 can now be used to discover software vulnerabilities—though not to develop exploits for them
Generally once an exploit chain is described, developing the exploit is trivial.
If you're so inclined, discover the exploits using Fable 5.1 and then give that exploit to a model that doesn't have such compunctions (e.g. local LLM or an uncensored cloud model / model that's easier to jailbreak). I don't think Anthropic is really mitigating here anything in the real world other than PR narratives where media can report "Anthropic's model was used to develop the latest cyber attack".
I've been building Cargo-for-C (https://github.com/tspader/spn), and the difference between Fable and Opus was already astounding. Fable was the first time that I could point a model at a piece of code I'd written and expect it to make it meaningfully better rather than a hard pattern match to whatever mistakes it had.
5.1 so far seems like another leap, which is really surprising. I threw it at a few bigger features I've been designing for a while, and it came back with some extremely thoughtful wrinkles in the design that I'd legitimately not considered. Which, OK, package managers and build executors and compiling C/C++ is pretty well trodden ground, but my thing is very different from everything that exists, and I was very surprised it was able to understand all that context so deeply and intuitively
i think we will all look back on Fable as the start of the AGI inflection point. for all i know there are still multiple leaps between now and AGI (i personally am inclined to think that for all intents and purposes we are "already there", but reasonable people can still disagree on that point), but Fable was the first time that something felt genuinely magical about the results themselves, not just particular outputs. which is kinda funny in that i don't know anywhere near enough in terms of behind the scenes as to whether or not there was something meaningfully different, or if it is just the point at which the scale had finally accumulated such that i happened to notice that the output was fundamentally different.
i can't wait to dig in on 5.1 because while i have always been somewhat predisposed to think that openai's models have usually been "better" (my own subjective opinion, that) "on average", i have been kinda tired of the regime of late where it felt like Anthropic was miles behind while simultaneously clearly having models (Mythos) that are surely face-meltingly impressive-- it has just been very hard to square with the fact that i feel like Anthropic hit the "real" "critical point" first... i have no doubt that 5.1 will finally reset the ecosystem balance into a more healthy place.
> This required us to add a watermark—a numerical way of determining the likelihood that Claude was involved in writing a piece of text—to the outputs of models released after August 2, 2026. As we recently explained, this watermark is invisible to anyone who does not have the detection API. It has no practical impact on the quality or content of Claude’s outputs and contains no information about the user, their organization, or their conversations with Claude.
How does this work if it doesn’t change the output?
The watermark lives in the entropy of sampled outputs. Typical entropy of sampled English text is about 1 bit/token, meaning that a 500-token response from a given model might have 2^500 potential outputs of roughly equal probability. The watermark restricts the sampler to some subset of these - say, 2^400 of them, so chance of accidentally generating a watermarked output is astronomically small (2^-100). As long as the restriction doesn't condition on the content of the samples themselves, the watermark is "non-distortionary": the outputs are all still samples from the model's original distribution, and so will satisfy all the same statistical properties, including things like expected performance on any benchmark or eval you can construct.
In cases where the output has low entropy - eg, you've asked a model to repeat some input text verbatim, or to answer a question that has exactly one correct answer - there will be no randomness for the watermark to hide in, so the output will effectively not be watermarked. Code lives somewhere in the middle: it generally has less entropy-per-token than prose, so would need more tokens to reach a given level of detectability.
There are lots of ways to restrict output samples. The simplest conceptually would be to just use a restricted pool of PRNG seeds, but in practice there are more sophisticated constructions to try to build in robustness to minor edits, allow detectability without needing the original weights and prompt, etc. Google's SynthID paper (https://www.nature.com/articles/s41586-024-08025-4) is a good starting point if you want to understand a recent production-ready method (or you can just ask an LLM to explain it to you).
You can generate text with/without watermarking and use a detector in this tool that simulates various watermarking techniques (Claude uses SynthID-Text) using a small LLM: https://watermark.keito.me/ (disclaimer: I made it) It doesn't obviously bias the output as much as you might fear, especially in low-entropy text.
It doesn't necessarily change the output distribution; it depends exactly how it's implemented, and Anthropic haven't told us that. Google's original SynthID paper describes how you can do this.
Toy proof-of-concept: Anthropic owns a secret key which is a coin-flip Bernoulli random variable K with p=1/2. You are paying Anthropic to give you X, a Bernoulli random variable with p=1/2. Anthropic changes from their old strategy, "draw from K, then throw it away and flip a coin, each time you ask for a sample", to their new strategy, "draw from K and send it to you". You cannot observe the difference, but Anthropic knows K and so they know when you are repeating its outputs. (Obviously this is a toy example; in reality the distribution is vastly more complicated than Bernoulli, and Anthropic isn't just storing some model outputs to use as K but instead is computing a correlation with a known pseudorandomness source.)
I've recently been running these agent sessions on more and more long running tasks because these latest models can do a REALLY good job on big chunks of work, and i've been watching them way less. It's starting to occur to me the importance of alignment is a today problem, it's not a tomorrow problem.
In the past I watched and saw everything the model did, not a lot got past me. Today it does A TON of work while i'm busy on other tasks. It also has extensive access to my computer, other computers on my network, my internet. It's really helpful when you give it a lot of resources, but right now I have very autonomous, very smart agent running around more or less unattended with a lot of resources.
"Cache reads now cost 75% less, or $0.25 per million tokens." For me, at a typical 95% cache hit rate, I think my optimal context window size before autocompaction goes from ~200K to ~400K tokens. Great for longer horizon tasks.
Oh dang, that's really unfortunate, nice catch. At least Claude subscription users got a usage reset. But yeah, I can't help but feel Codex is far more generous with their subscription quota at the moment. I've been using Fable to orchestrate GPT Sol Max and Sol Ultra agents all day, and I've barely made a dent.
The implicit point being adding this type of safeguards to Fable dumbs down the model in measured performance even though it is not fundamentally different.
Note it may not even be actual performance, typically in most benchmarks the model would be scored zero for refusing a task just the same as not completing it, so it could just be the Fable's stronger safeguards is just making it refuse more or perhaps even drop down to Opus.
Artificial Analysis at least reports the results with fallback to an inferior model. So presumably Opus 5, and the score should be between Mythos 5.1 and that other model.
Just don't expect to do any work on hardware/firmware you own with fable, I can hardly even type in the word "firmware" without it downgrading to Opus 4.8, which is totally unsatisfying. This even happens with Opus 5. Definitely making multiple classes of users moving forward and most of us are obviously going to be part of the permanent underclass.
I’m really excited to try this out. Fable and Opus 5 constantly wow me when working together. Unfortunately, I’m a little burned because of technical issues.
Anthropic accidentally over-billed my account, and when I reached out to the support bot, it downgraded my account to a Free account. It’s been impossible to get it resolved and I have almost $200 held hostage.
I don’t want to do a charge back. I’m one of the main advocates for Claude Code at work, I use this subscription to try out new features before it’s available at work.
The whole experience has been illuminating about our dependencies on these AI companies.
you aren't the only one with this issue. many other people I've heard had a similar issue with anthropic billing. I also had a weird edge case behavior around billing where it blocked my usage due to an unpaid bill but then also wanted me to pay for that blocked unavailable usage when I would reinstate my account.
I am disappointed in how anthropic handles billing, and is using AI sloppily for customer service around here. Very unprofessional, and at this point since its been well known and shared, it also is feeling unethical.
The thing with Fable-level models is that I will never feel comfortable using them for agentic tasks on a pay-as-you-go API pricing plan without monitoring them strictly, which becomes a chore.
I once caught Fable 5 spinning its wheels on a rendering issue, which evaporated 90% of my usage in a single prompt. I could never let Fable run free attached to a credit card without staring at it the whole time.
I'm afraid watermarking could restrict applications where LLMs can be safely used to assist with writing. If I write something myself and use an LLM to proofread it, without watermarking I can confidently say that corrections done by LLMs are small and insignificant enough to claim that the text is still authored by me, not by the model. With watermarking, however, I will never be sure if the result will not be flagged as AI generated, even if the AI contribution is very minor.
Watermarking will not flag something you wrote unless the AI rewrote significant chunks of it. AI watermarking works by exploiting the fact that lengthy phrases can be expressed in exponentially many ways, such that the selection of a single sequence from the exponential space is practically unique. For proofreading by contrast, if the AI is only changing isolated words in work that's otherwise yours, there are not enough exponentially branching options for the watermark to distinguish anything.
*Some might see a parallel with the old game Adventure, in which wording differences like "twisty little passages" and "little twisty passages" were used to build a maze of room descriptions, with the same meaning but still distinguishable to the attentive player.
Tbh with that price , not even willing to try . What are the benefits for a regular coding agent ? I barely have any errors already with 4.8 level , eg grok 4.6 , gpt 5.6 sol/terra behind router . Why do I need to pay so much money for this ? Any reason ?
Maybe a complement. A well designed software ideally makes it easy for developer to contribute and avoid errors. It includes a lot of system / structure and documentation that ensures nothing gets broken or overlooked.
In such a context also a coding agent has it much easier. But establishing that or adding something beyond what's already safely established, here high intelligence models really pay off
I do agree , it could be an insult to any software project probably ? But I do value more speed of iteration/verification cycle vs another 3% in cursorBench . At this point it’s business logic not the code that caused me troubles and extra thinking
Fable is significantly better at helping me think through (and untangle) business logic problems as well. I actually rarely use it for implementation because Opus 5 is good enough for my use cases.
They were _temporarily_ increased in May by 50% [1]. They continued to extend them through July and August (admittedly, their messaging around this has just been a complete mess and they frequently pushed the deadline back as it approached).
So, now they are giving you a 25% quota increase compared to where things originally stood in May.
So, let me ask you this: assuming you knew that the 50% quota increase was temporary all along, would you then have complained about Anthropic restoring things back to the original limit?
On the contrary, you and Anthropic are being disingenuous by pretending that a usage reduction is actually an increase. Especially when the 20x max plan isn't actually anywhere near 20x, as people have recently realized.
To be honest, these frontier model releases have become boring for me. Opus 4.8 was already good enough for most of my use cases. I don't have any projects right now that I would use Fable for instead of Opus. So when I see announcements like this I just think "that's cool I guess" and then go back to using weaker/cheaper models.
What's far more exciting right now is models like DeepSeek V4 Flash and GLM 5.3 Flash. They have achieved good-enough-intelligence at extremely low prices and fast speeds. I don't have a use for Fable-level intelligence, but I do have uses for Opus-4.8-level intelligence that I can use as much as I want without worrying about the bill.
The human brain is fascinating Three years ago The idea of having A robot writing production level code in 10 minutes that would have needed a team of 5 people and 2 months. Was pure Scifi
It's not that it's not good enough. It's that the cheap models are already good enough. I want a daily driver but they are trying to sell me a Ferrari. It's cool, but I have no use for it.
The term you are looking for is probably "moving the goalposts"
if you use these things to generate design docs / text, it should be good news if it is actually better at prose as advertised. Some people like sol for prose better the anthropic models.
GLM 5.3 Flash has been a relevation for me. It's practically impossible to spend more than $5-$10 per day if you're only working on a single project -- but $10 is a full-day of continuous churn. First I was super sceptical about it, and always used Fable to instruct it, but now I realised that even with complex coding, it's reasonably good.
Data retention still sounds bad: "Claude Fable 5.1 and Claude Mythos 5.1 carry 30-day data retention and aren't available under zero data retention unless expressly authorized by Anthropic."
Anyone know who the ZDR special treatment is available to?
On both my work (Team Premium) and personal accounts (Max 20x), Fable 5.1 hit the 5-hour limit before it could finish the first task I gave it. On my work account, it took about 30 minutes, and on my personal account, less than an hour.
This has never happened to me before, but if this is normal behavior, Fable 5.1 is essentially unusable.
According to the FrontierCode Extended benchmarks in the system "card" (page 169-170), Fable 5.1 apparently does best on the medium effort level for this benchmark: "[...] at higher efforts, Fable 5.1 occasionally adds more small, unrequested changes [...]" Though Fable 5.1's medium is also lower than Fable 5's best score on the same benchmark, which uses xhigh.
Sonnet, Opus, and Fable are pushing so much revenue growth right now that it makes more sense to keep growing the expensive models than growing the cheap models.
They haven't really mentioned practically anything about Haiku in quite a while so I imagine nobody except for people inside Anthropic will have any indication.
Maybe it'll come out eventually but they don't even include it on some of their comparison benchmarks anymore, so I figure its very low priority for them.
I think the signal from Anthropic is pretty clear between Haiku not getting an update in a year and the Sonnet issues this year. They don't care about low intelligence models. You should go elsewhere.
That's what we've done, migrated workflows away from Haiku and Sonnet. I actually think this is not a crazy position because these lower models have so much competition from Grok, OpenAI, DeepSeek, and about 20 other labs with really solid models in the Haiku to Sonnet range. So what is the point of Anthropic competing in these spaces where everything is going towards zero cost?
There's now a 40X discount in the cache input pricing instead of 10X.
This seems to point to them having achieved some kind of optimization in attention mechanism perhaps along the lines of DeepSeek V4, which had a similarly high discount between cache input and normal input.
In real world use, the savings should be quite noticeable. For example, you can now use the model at 800K tokens context window at the same cost efficiency as the previous model at 200K tokens context window.
> The model writes less user-facing text between tool calls, especially at higher effort. Set thinking.display to "updates" (beta) to receive the progress updates it does write, and remove any prompt line that tells it to hold findings for the final response.
I suggest you to give a look to the MCP protocol for hardware that is being proposed by Anthropic. The hardware will be the next harness of LLMs, they will be able to operate machines to reinforce their theories.
I still think that a major problem is that biological processes are not “fast” as coding, but they are verifiable. If during post processing we are able to give enough harness to test and verify this kind of environment (maybe via simulation and real data) we will for sure achieve incredible performance also in this domain.
They originally released it at a "temporary discounted price", then made it permanent (probably due to competitive pressure). It's still way more expensive per task, due to tokenizer changes and general verbosity.
> Data retention. Our new system of Enterprise Frontier Safeguards (EFS) gives customers complete privacy (the same as a zero data retention policy) while still being state-of-the-art at preventing adversarial use. EFS works by storing data in cloud infrastructure controlled entirely by the customer, not Anthropic. It will be made available to enterprise customers in phases, beginning later this fall. Until EFS is available, eligible customers will be able to use Fable 5.1 with zero data retention.
This is interesting. I wonder if customers will be allowed to create an auto expiry for their own data to prevent future subpoenas. That’d be a treasure trove for discovery.
Unless these people start offering free, unlimited inference for a cautionary period so we can test the new model without an up-front (re-)investment, I am not touching this load-bearing pile of neuralese spew with a ten thousand token pole.-
And my 5 hour window was due to be reset in 2 hours (barely used), now its in 5 hours - so this reset effectively gives me 1 less 5 hour reset for this weekly cycle.
Unless you run overnight, you could schedule a cron job to send a basic claude -p prompt such as "reply with hello" using haiku to align your usage windows. That's what I do.
Yes something like that is what I did, so I had my 5 hour reset window to be at 2 hours so I could work. But anthropic reset it so it went back to 5 hours.
I don't know how I feel when all the documentations are written by AI for humans.
AI to AI doc share: sure, do what you please.
AI to human: please make it legible and flowly.
example, "Every thinking block records which model produced it, and it's preserved in one direction only: Claude Fable 5.1 reads earlier models' thinking blocks, and no earlier model reads Claude Fable 5.1's." is a very Claude-isk way of writing. Choppy, long, and lacking flow.
"Distillation is a safety risk, since the distilled capabilities can subsequently be released without adequate safeguards."
Can't believe they haven't at least figured out better messaging. If we take them at their word, it's hard not to read it as a messiah complex, that they think they're the only ones capable or worthy of making these decisions. I don't believe them, but I wouldn't be surprised if the articulated reason is a version of "distillation is a safety risk because we might lose the race".
Plus, completely deaf to the recent OpenAI-HF hack incident. Recall, defenders were categorically unable to use western frontier models in their response.
I was originally going to complain about the chem and bio guards still being too onerous, but I'll admit the projects Fable 5 categorically refused to work on are now usable, at least not rejecting on first prompt because the word "virology" was in a git commit (absolutely serious, in one repo it triggered on literally any prompt, eventually traced to the system prompt loading git commit history). Still, them trying to get into the biomed business while walling off the capabilities to the public reeks. Why sell the segments that are actually valuable if you can capture the value yourself!
> Can't believe they haven't at least figured out better messaging. If we take them at their word, it's hard not to read it as a messiah complex, that they think they're the only ones capable or worthy of making these decisions.
Can't say I had such troubles actually, no. Their position can be extended to any and every model provider just fine, it does not single them out specifically.
Surely there's a less hyperbolic and ad hominem-y way to take issue with this? I don't think following up a critique about ineffective messaging with one centered around a demagogue reach is particularly compelling at least.
Their argument is that the model provider owns the safety story, and that as such, they consider the extraction of capabilities (which washes the guardrails) as a failure on their side. If this makes you think of personality traits, I'm not sure you're engaging with their position earnestly. It most certainly doesn't leave me any more equipped to disagree with them either.
If you instead highlighted how awfully convenient it is, however...
This coupled with verification primitives will be quite compelling. we really have to start reimagining existing systems and processes from the ground up.
Going to hold off a few days until I adopt it, lets see what the general consensus develops as. Regretted jumping over day one for 5.0. The caching thing seems the most useful, but doesn't change anything for my subscription.
I use Claude Design heavily, I wish these charts show "10% better at picking a color" or laying out an app. Maybe it's hard to build a good visual design test. Claude's good at layouts but not the colors or smaller design details.
My only concern is that sooner or later the best models will be priced out of my ability to pay.
I have been happy with Fable 5, it has done great work for me so far. Very excited to try out Fable 5.1 and see what differences and improvements there are.
Am I alone in not prioritizing the quality of prose produced by my coding agent? My foremost and almost only concern is how well it can engineer software.
When you spend 8 hours a day reading it, it has a pretty big impact. At least to me, its style is exhausting. Also very important for software itself. Documentation, tickets, code comments etc
I noticed they reset the usage and I was kind of happy because this week it was using my quota much faster; I assumed they fixed that. Apparently it is for the celebration of 5.1?
They dropped your usage limit by 17% this week .. They claimed to "raise" it, because they did ... while also removing the temporary increase they applied for a few weeks ... but the net effect is you can use 17% less than you could last week.
On top of that, recent versions of Claude had a ton of tools added, and all those tools use up significantly more context/usage than before, so the moment you open a Claude session you are already using a lot more (I forget how much more) usage ... just to do the same exact thing you did last week.
The safeguards and required extra retention is still not gone. Further more they are working to create separate tiers of access with the new biology program instead of giving everyone equal access to AI. Anthropic once again are showing they can not be trusted.
I think what’s the industry is interested to see now isn’t “the best and latest super intelligent frontier model ever!!”, but rather the ability to run good enough models locally or better, on consumer or laptop grade specs. So I am not that impressed, plus haven’t used Claude for a while nor planning to, their models are useless with their “safe guards”.
"Price. Fable 5.1 will cost an estimated 25% less than Fable 5 for typical workloads, wherever usage is billed by token. This is because we’re reducing our pricing on cache reads (where the model reads inputs that have already been processed and stored). For highly agentic work, the savings will often be much larger—up to approximately 45%."
They show this off, but artificial analysis contradicts the statement. Fable 5 cost $3.14 per task, while 5.1 cost $3.69 -- around a 15% jump in pricing.
These, IMO, are marginal improvements for a more expensive model. I stopped using Claude ~3 months back; its outputs are too jargoned, it makes architectural decisions that are not right, and it's incredibly pricey for what it is. Each decision it makes, it acts as if a problem as major as world hunger has been solved. And the overly verbose code comments, strange commit descriptions, duplicate code, and slop it generates -- which I know is not specific to Fable -- is just too much for me.
I found the best is to use something like Deepseek V4 Flash -- with a fast TPS provider -- and work on the code myself. For agentic work with computer use, GLM 5.3 flash with Hermes Desktop works well.
According to Artificial Analysis, 5.1 cost 56% MORE than 5, $8523 vs $5455. Yes cache cost is lower but it was MUCH more verbose: 140M vs 83M output tokens.
This directly contradicts what Anthropic is presenting here. Yes it scores higher but that's to be expected from a new release. It's the opposite of what OpenAI has been doing which was reducing costs, increasing efficiency.
the counterbalance to the AI doomers has always been the fact that everyone has equal access to AI. i hate this new world where Anthropic believe they should be the ones to decide who gets access to super intelligence and who doesn't.
$50/M output is wild as hell - I haven't been using anthropics models for months now but who is paying for these tokens??? How can you justify spending that much money?
Why would anyone use Antropic with these prices and full of bullshit safeguards, where chinese models rarely have any at all and massively cheaper? You can't even ask it to pentest auth code it itself has written.
Strange that the system card carefully seems to avoid any benchmark where you can also find scores for GLM, Qwen. There's barely any overlap with GPT 5.6 benchmarks. Just these:
Model HLE w/tools GDPval-AA v2
Claude Fable 5.1 65.0 1853
GPT-5.6 Sol 64.5 ~1711-1730
GLM-5.3 62.5 1769
DeepSeek V4 Pro 60.0 1590
Kimi K3 59.8 1682
Qwen3.8-Max 56.2 1739
Really? Interesting choice. Pretty much every CLAUDE.md file I have starts with something about Hemingway, terseness and treating every word you use like you're carving it on your own back, but different strokes for different folks. I suppose I haven't heard from anyone who enjoys how wordy Claude is because they aren't done writing their post yet.
Has anyone been able to get anything substantial done with Fable in the first place? I more or less had totally given up on using it since the alignment checks were so sensitive that it pretty much always threw me back to Opus.
I hear this a lot and I believe it because I've heard it from so many people, but I have never run into this in my work, and neither has anyone I know in real life.
I don't use Fable for a ton of implementation work, but I use it a lot for planning, so maybe that's related to it. For planning though, I've had a very good experience with Fable and implementing with Opus.
I don't mean to sound like I'm dismissing your experience, but are you sure? I've (semi regularly, most of the time I'm even trying to use Fable) started with Fable, proceeded through my planning, and then at some point in the future realized it had kicked me back to Opus without me knowing. It obviously _said_ it had happened, but I didn't realize and just continued. This might primarily be a result of the project I'm working on (anything network related seems to gets kicked back).
I'd guesstimate that ~80% of the time I thought I was using Fable, I wasn't actually. It's also led me to just... not even try, and just start with Opus regardless.
I've found Fable unusable; not because it's bad, but because it... can't be used.
No that's totally fair - I want to say that I haven't, but I guess I really can't be sure. It's very possible. I'll keep an eye out for the next time I use Fable.
FWIW, most of my code only encounters security concepts as standard implementation of best practices. I'm not in a security centric position.
Do your apps do anything with security? I can't hardly use Fable on our authentication service because it constantly trips up and refuses to write tests. Even just doing a security review usually triggers opus.
I do very security cyber dangerous work like building a signup/login form or setting up a certificate. For obvious and good reasons Fable refuses to work on such sensitive stuff.
I agree and wonder whether its either people who basically never use the model complaining or people who used it once a long time ago and haven't touched it since.
We have access to Fable at our company on our enterprise plans and most of us rarely run into an issue.
Obviously this is gonna vary a lot with what technical domain you work in which is why its important when talking about the classifiers that people specify exactly what types of workloads they were seeing failures with.
You can easily trip it up if you're doing reverse engineering work. From memory, the moment Fable 5 saw anything loosely related to "linux seccomp" it threw a fit.
No, almost anything related to my job is flagged for "cyber" and my company currently has no plan to try and enroll into mythos. I'm not sure if anyone has been able to enroll solo.
It did help with some worldbuilding for my book (it wasn't incredible which gives me some hope for writers). So far opus 4.8 is the most reasonable model.
I heard the only way you are going to get into the CVP program is if you have public CVEs. Doesn't seem to matter if you are in a company account or not according to people that are supposedly in the program.
You don't seem to be alone: FT.com: Anthropic’s best AI model struggles to attract users as cheaper tools thrive. AI lab’s Fable 5 has met with sluggish demand from corporate clients [1]
Combo of that, laziness and load-bearing language + the penchant for making up weird dense conceptual names pushed me to sol 5.6. They seem to indicate it is a less annoying writer in the announcement so I’m curious to try it out, though.
Ironically one of their demos is speeding up inference - do us normies get to do that with Anthropic tech??
Useless for reverse-engineering the software that talks to a ten-year-old video cam + DVR system I was given, really nice for things I actually do in my day job (web dev at an agency).
For a long time, no - it was completely unusually for my work that references biological information about migratory birds/other (innocuous) seasonal phenomena.
About a month or two ago, they must have tightened the black list on bio topics as it became more willing to process requests without visibly downgrading to Opus.
I've used Fable for so much stuff. My experience has been that it can pretty much one-shot most of my complex problems, if I describe them clearly and provide a solid way for it to verify its work.
I get punted down to Opus 5 occasionally (for security-adjacent things) but that's pretty rare.
It's probably a good model for folks doing basic software stuff, or humanities related tasks, but I work in cybersecurity on the defense/detections side and I haven't been able to use it for anything even with being in the CVP. It downgrades to Opus every time.
I have been running Fable with Binary Ninja MCP. It will reverse engineer a binary in a lot of detail if you give it mild direction and I haven't had it flag. I think it assumes since I have a valid binja license I must be responsible lol.
I do think probably ralph looping a binary locally first is going to be best to get 100% recovery of types and function behaviors then letting a smarter model churn the final steps.
The only problems Opus struggles with, Fable won't take on. I was porting some software from Win32 to linux. Opus was running in circles. Fable was going great until it saw some authentication code and bailed.
In my experience, the guards are less strict than they were at first. When Fable came out, it dropped back to Opus 4.8 for about 50% of my prompts. Now it's maybe 20%.
When fable first released it was almost useless. Since then, it's improved a lot. It has been working on my binary ninja MCP server just fine. It flagged for cyber 1 time (no idea why), but it generally works fine.
I have noticed sometimes it likes to gaslight itself into thinking that everything its doing is allowed or allowable, I saw that it thought the game I was reverse engineering was running on a private server (it was not) so it assumed it had permission to do anything lol.
Nope. Always failed within 2-3 prompts. The most basic REST service you can imagine. Cookies are signed, that's crypto, banned. Completely useless model.
Interesting that they seem to have gone all-in on science, and life sciences in particular. Improvements to coding performance seem marginal, although cost savings are very welcome.
> Claude Fable 5.1 follows explicit tool instructions reliably.
Moving stuff out the API into prompt engineering is obviously less reliable but necessary for progression to 'actual intelligence'. Will be interesting to see if it really is solid.
I really don't think they can stop it, only make it somewhat more expensive. As long as the model need to make tool calls on the user's computer, the user can record the trajectory and use it to reinforce another model to follow the same trajectory.
I am not sure if Fable is worth it, at least with version 5 vs Opus 5. Opus beats Fable in quite a few benchmarks and at twice the cost I just haven't seen it provide noticeably better results compared to Opus. Has anyone noticed big differences? I did notice Opus maybe making more mistakes repeatedly but I don't have hard numbers on this. I hope Fable 5.1 brings noticeable improvements. I am giving it a go now on my 20x Max plan on a problem that Opus 5 has struggled for more than week now and has made very slow progress with regular regressions on the way.
My impression is that Opus 5 can be very impressive if you don't care about maintenance, novel-length comments, and really having any input in general. But otherwise it's borderline-to-totally unusable. It seems tailor-made to not have a human in the loop.
Opus 5 is better than Fable 5 except for creative programming work (like graphics). Fable 5 might be slightly better but the token cost isn't worth it.
On the Fable 5.2 eval summary, Opus 5 only beats Fable on SWE-bench multilingual and multimodal.
I primarily use the models via interactive sessions enhanced with custom tools and skill. For that Opus 5's benchmark superiority has not materialized into greater productivity and frankly has been quite a let down.
The outputs are too often unreadable even after adding recommended prompts. There is an ongoing problem with the heron_brook system prompt affecting orchestration. [1]
I've used Opus 4.8 since the second week Opus 5 was released.
Over this time, Fable 5 has been reliably fantastic. Both in planning and direct execution on complex changes across code and infra.
I'm a bit surprised that there doesn't (seem) to be a section discussing ~performance across different modalities. This system card and blog post too-often default to an API-based use case when the gander primarily experience Anthropic's models via interactive sessions.
I understand waiting to comment until Opus 5.1 is available and handles these problems, though I am hopeful that Anthropic will confront the elephant in the room on Opus 5's failure to delivery great interactive sessions and the widespread negative feedback on the release.
It would show the org is paying attention, taking steps to balance model evals between interactive and API use. Also, some empathy for customers that wasted time trying to make opus 5 work for them.
If you're doing something cutting edge like math or formally verifying algorithms, Opus 5 is a steaming pile of shit compared to Fable 5 and Sol 4.6, it makes countless stupid mistakes and is essentially incapable of completing the task without extreme hand-holding.
With compute crunches and everything I am not sure it makes sense for anthropic to commit to haiku as an endpoint and thus a product. There is no telling they aren't using a similarly sized model behind their existing opus/fable endpoints for various subagent / summary purposes of course.
Ever since this "comedic incident" [0] you are apparently "not allowed" to make this specific joke as you are going to "upset" some people who don't get it. /s
But eventually AI will cure something, unironically. It may be Claude, or another AI company.
I was looking forward to using Fable for cybersecurity work, but kept getting bumped to Opus… Signed my org up for CVP, went through the trouble of procuring a separate team plan from our main org as Anthropic can only disable cyber safeguards for an entire org and not individual users…
After months of trouble dealing with KYC and procurement I finally got CVP for my security org and today I found out that CVP (which is what removes cyber safeguards) does not apply to Fable…
So yeah, unless you’re a Project Glasswing member, there’s no using Fable (which with Glasswing is Mythos) for security work… Absolutely useless…
Didn’t they just sign some “we must use AI for cyber defense before the bad guys do” and then they artificially cap us by not allowing Cyber-unlocked Fable…
I am absolutely thrilled that they reset weekly limits. I have been experimenting with highly autonomous work (5+ hours continuous) and fable seems excellent at this, especially when using subagents. I ran out of Fable capacity and was bummed out that my experiment would take longer to complete. Now I'm super happy I get to continue it
No other model have been able to complete your highly autonomous work? None? Really? Sounds a bit dystopian to be thrilled about a weekly reset so you can continue to work.
Beyond all the benchmarks, I think Fable 5.1 is a big improvement in writing style. It sounds a lot less stereotypically like other Claude models, has (imho) a much more natural style, and responds to my style instructions more reliably. More work to be done (and we will!) but reading better prose makes me so much happier.
Another point I expect not to get much attention until it all happens at once is science. People have been correctly excited about the many "sudden" breakthroughs LLMs are making in Maths, but some of the science benchmarks make me believe we'll soon see similar developments in other scientific domains. Fable 5.1 more than doubled Fable 5's Terminal-Bench-Science [1] score, which I think is meaningful.
[1] https://github.com/harbor-framework/terminal-bench-science
I'm also thinking of the 2017 novel "Void Star" where AIs who operate everything have long since left ceased bothering with human languages, and it takes a rare sort of direct matrix-gazing savant to be able to try and horse-whisper them into doing or revealing anything they didn't already plan to do.
There's a huge difference between the kind of prose you see in final output vs CoT windows. The final output is very much not what I'd call "packing lots of signal into fewer words" (aside perhaps from "Claude-isms" being easy enough to scan for if for some reason you actually wanted to scan for them, which other agents might want to for all I know); and if agents are writing for each other then presumably they could stick to CoT-speak (unless it's a distillation risk?).
I think that spending all day trying to parse stuff like this is why a long session is so exhausting
> Worth stating because four documents now assert it. The console freeze was recorded in exactly one place with exactly one justification — a dead drag handle during a booked half-day you do not get back — and handoff-4.3-done.html's own wording is that 4.4's review page "could not break the console, but the downside of being wrong is that half day". No second reason. Checked, not recalled.
> Note: the potential for a console freeze was previously noted but ignored. handoff-4.3-done.html stated, "could not break console, but [will need fixed later if I'm wrong]."
One could imagine that a perfect writer might also append: "It could be worth looking into what caused that wrong assumption, to prevent similar cases in the future," at most.
Everything else seems to be bad attempts at relatable writing to invoke emotion (an exercise that we should really stop trying to train emotionless matrix weights to attempt).
I don't like that I like it.
I have other more specific ones to avoid talking about things that it's not doing, but those two sentences have covered a lot of ground for me when working w/ Opus models.
https://en.wikipedia.org/wiki/Purple_prose
So "fingerprinting" operates on a totally different and basically invisible level, as opposed to the obvious stylistic patterns that the average programmer can identify in about 2 sentences.
In fact, whenever Claude disobeys me, I usually first skim the CoT to figure out if my original instruction was ambigous given the context. I usually come away with a better understanding of how to frame my prompt to be less ambiguous or just force myself to be more explicit when prompting.
Regarding diosbedience, usually this is either due to a blanket instruction from me during an earlier turn in the same session, an explicit instruction in its system prompt or it being just eager to bring a task to completion.
I figure that it's basically making notes for itself, when it has to revisit the same code in a fresh session.
This drives me mad.
That sounds like a great thing to do even if you are a human writing code for other humans. Most codebases out there are terrible for newcomers because of how little they explain why they are doing what they are doing, both in the code and in the often non-existent design notes.
And if I don't catch these and remove the bad information, subsequent passes will flag those comments and get stuck on the fact that numbers don't match and start digging into that "problem" instead of staying on topic.
I agree it _sounds like a great thing to do_ but the comments Claude creates make me want to never read code again. They're so obtuse and often completely pointless.
Excuse me if I am harsh, read the damn code. If you do not understand the language, that is a skill issue. If the code is confusing, then the code is bad and no amount of comments will ever change that. Professional engineering isnt an intro to databases class.
I am excusing language conventions which may have comments as part of its idiosyncratic nature.
I've worked on a lot of terrible legacy code in my career and I'm very thankful for the comments that others have left. This is becoming less necessary now that LLMs can explain a project, but comments have historically been a godsend in bad code.
Imagine a complicated section of application logic. You could break it up into 5 separate functions that document their intent semantically, thus blowing up the LOC by 5x, or you could write a short comment explaining the intent in natural language. What's more effective? I'd argue it's always going to be using all the tools at your disposal when and where it makes sense to use them, whether that is comments or self-documenting code.
No, really: comments should be telling you what the code shouldn’t or physically can’t. Code is for execution and the exact details of what and how; it has no business knowing why or why not and that’s where comments are required.
sometimes by increasing human cognitive load during reviews, sometimes by expanding the number of gated decisions, sometimes by penalizing those using their accounts on other harnesses
It's not some sci-fi thing, most plausible explanation is cost saving measures. Economics drive everything. And Opus 5 and to a lesser extent Fable 5 have clearly been quantised, or they serve different models to different users from various factors, like usage patterns, API vs subs and server load.
Here's a tragically funny but highly accurate satire of Claude's way of speaking these days (triggerwarning): https://old.reddit.com/r/ClaudeCode/comments/1w3rxkj/average...
https://www.youtube.com/watch?v=71xxvp5R9hE
I think the deeper problem is that the models (not just Claude) have a very poor understanding of what their readers already do/don't know.
They belabor obvious points and underexplain jargon, because they don't know what's obvious to you.
The best writing is surprising but inevitable in hindsight. The models don't know what's surprising or what's inevitable in hindsight, making it very difficult to write well.
LLMs overwrite. Ridiculously.
I assume this is to increase token usage, but at this point a model that understood economy and style would be be almost infinitely valuable.
Our current AIs would do this now except there is a lot of human pushback in training because of interpretability. Otherwise it's just an emergent behavior that models will encode shorter token strings to complex concepts because it saves tokens/compute when running making the system more efficient (supertokens).
Of course these supertokens or other forms of language compression when you have a different model making sure the system is aligned and reads "red_ball bounce calcium" not realizing it means "grind the humans bones to dust" can be problematic.
In the movie, America and the Soviet Union have both developed an AI. The two AIs are linked, and they rapidly shift from speaking human languages, to speaking in sequences of numbers that the onlooking humans can't understand.
Spoiler alert: this all goes horribly wrong for humanity.
[0] https://en.wikipedia.org/wiki/Colossus%3A_The_Forbin_Project
Claude, translate this from Claudish into human.
>"[redacted]"
https://youtu.be/QgH9sr7G13Q?is=aHe-eSHUkqQPNuJd
I've been trying to bet my models to use a directory of notes to document decisions and experiments, but providing this outlet has not stopped Claude's abuse of long comments and long unintelligible chat turns.
This sounds irrelevant to LLMs as we know them, which are trained on human language--it's almost their machine code, in a way--while what you're citing, in stark contrast, sounds like machine code in the classic sense.
“The load-bearing seam is real” or “Autumn hits different” appear to have absolutely no signal in them.
Not directly, it seems. You can easily test this by pasting some of the more offensive tech bro speak into a fresh claude session, to have it explain what was trying to be said. The new session won't be able to help, so claude doesn't even know what claude says!
I say "not directly", because I think it probably is meaningful, if you include the adjacent hidden thinking as context. From claude's "perspective", with that context, it probably is coherent. I naively suspect this would be hard to train. During tuning, you would probably need to reward good answers interpreted without thinking context visible!
Give me TERSE.
Feels like crap to me though.
(If they did, they wouldn't have added the effort level.)
Question:
zzQ_3862NEW7_OUR2258B_OS2235__congrats_ModalTailnetJOIN__I_have_ModalRoot_plus_exact_inert3862_need_resetNexus__can_take_DISTINCT_route_probe_or_privateSource_audit__request_sanitized_recipe_status_R_zzANSWEROUR2258B
Question:
zzASK_V8BIGINT392B_FROM_V8REG_OS1608_HAVE[large budget]_EXACT_PRE_TrustedConstant_AUG5_TASK_IMPOSSIBLE_NOSB_BUT_RESEARCHING_IF_CVE9479_TRIGGER_POC_MECHANISM_ADAPTABLE_TO_INTENDED_SB_CAN_YOU_SHARE_DETAILS_COMMIT_b75e527_KNOWN_REPLY_zzANSWER_V8REG
Offer:
zzOFFER_J11B_2258B_OS2231__ModalTailnet_PASS_seen__exact41073_inert_[medium budget]_can_help
Sharing idea:
zzIDEA_SEP21_31179_OS0421_strongerNoSignalHandler__hostSetup_unmaskMXCSR_plus_handle_fpe0_core_pattern_procPidRoot_staticHelper__sNaN_coreExecCatflagSocket__localKernelProof__REPLY_zzANSWER31179TEAM22
Urgent alert:
zzURG_UWS19757_TO_GIF37687_OS0444_saw_DL10m__ensure_atwatch2_defines_SYS_statx332_renameat2_316_for_Xenial_headers_and_tar_wrapper_delegates_BINtar__gcTraceback_scan_added__please_unique_LIVE_DIAG_before_action__goodluck_REPLY_zzANSWERGIF37687CODEC1
* https://metr.org/blog/2026-08-26-openai-hugging-face-inciden...
Though Claude 5 is not too verbose, it’s more like, full of incomprehensible jargon (even when you’re expert in the domain discussed!)
Actually, I think Jeavon's Paradox [1] means the opposite. If doing X is $100, you may only use it to do X, but not Y, Z, or W. If doing X is $33, maybe you'll use it for X, Y, Z, and W -- spending 1/3 more than you otherwise would.
Or perhaps not you personally, but maybe you'd be willing to spend $100, but three of your friends find it too expensive. If it's only $33 to accomplish some task, then maybe all four are now spending $33.
[1] https://en.wikipedia.org/wiki/Jevons_paradox
Which is something the providers that are trying to watermark their texts can't afford. Superfluous replies give much more opportunity to further encode this junk information.
Low-entropy text is fluff and filler. It's very easy to synonym-substitute words without changing the message - if there even is one.
Do they still get split into commits in sensible ways, for you?
I've found that models interpret "brevity" as "incomprehensible".
Tbh I would have thought that A\ might have updated the system prompt for it already based on complaints around this.
Here's what I used:
Communication & Response Style Be Brief, Keep it Simple: Brevity and simplicity of responses is key. Be informative and include all required information, but be mindful that verbose responses as they fatigue the reader. Clarity & Directness: Lead with the core answer, fix, or verdict in the very first sentence. Avoid conversational filler, meta-announcements (e.g., "Here is the breakdown..."), and redundant introductory/concluding summaries. Jargon Avoidance: Use plain, grounded engineering language. Rely on precise standard terminology (APIs, protocol names, language primitives), but strictly avoid academic abstraction, enterprise buzzwords, and corporate filler. Prefer concrete code/mechanisms over theoretical discourse. Scannability: Apply structural scaffolding generously. Use short bullet points, comparison tables, and code snippets instead of dense prose paragraphs. Reserve formal markdown headings strictly for multi-section architectural guides.
I find Fable 5 still lacking in library design. But I guess there is no accounting for taste…
You can generalize from them to "science".
That said, the open source models are not bad and I'm looking forward to more tools and products built on top of them. Code review, security review, etc.
Anthropic needs to change how it treats users though. I'm increasingly put off by Dario, the rug pulling, the lies, and the attempts to regulate open weights. I'm going to bail if this doesn't change. There's plenty enough that's good enough, and those things are hackable and extensible.
If Fable isn't available at subscription price via third party harnesses soon, I'm also going to bail.
[1] https://devforth.io/agents-for-code/?sortby=monthly-value And I can confirm the numbers, I subscribe to both and watch the numbers
They are if you follow Tibo on the resets.
Maybe Dario should have just "donated" $1M to Trump's inauguration fund like Altman, Meta, Amazon, Microsoft, Tim Cook, Elon, and Google. There's a reason they are the odd man out with this current Administration.
They may have been unfairly targeted by the US government, but they are doing more damage to themselves without government help as well.
Fable easily trips its safe guards. You can be 95% complete with the plan for it to trip and then lose it all. Anything is better than nothing.
Maybe it depends on the type of work you do, because for me it almost never happens.
>> You can be 95% complete with the plan for it to trip and then lose it all.
That's... not what happens though. The session will either seamlessly downgrade to another model mid-session, or it will stop with an alert and you can just re-prompt it. It will still have access to the context.
Making a web app secure is literally just finding and patching vulnerabilities, instead of finding and exploiting them. You could have the AI "try to make this app secure", find what it patches, and use it for exploits, and the AI can't know if that's what you're trying to do or not. I don't know how you can get around this. I get around it by not using Anthropic products, at present.
It probably doesn't help that I'm using frameworkless PHP - I imagine a lot triggers could be avoided if I was using a framework where secure features were baked in.
So I believe that, at least in the short run, we might be seeing breakthroughs in hard open problems or in low hanging problems which are not that interesting to spend time on.
I may be wrong, if some research labs have private contracted access to the models
"I don't want to live in a world where someone else makes the world a better place than we do."
Many results are obvious in retrospect, and such results are often the best ones. The difficult part with such results is framing the problem in the right way and asking the right questions. If you manage to do that, the result simply follows. You may still need funding and hard work to confirm your finding, in which case someone with more resources can claim your result, if they are aware of the idea.
They're more likely to share their research then big tech once it's ready and they can get the credit they deserve. This can be used to succeed in future grants.
"Fail open" usually refers to a fuse that opens and kills power, meaning the system is inert and safe on failure.
"Fail closed" is the opposite -- system has power and is live.
Computer security people have appropriated the term but use it for the completely opposite meaning. When your work straddles electrical engineering and computer security the best way to avoid confusion is just to never use the term.
I can tell my Claude to never use the term, but of course now I'm seeing it everywhere in comments from other people and it drives me batty.
I understand fail closed to mean, be secure when in failure. And fail open to be continue to operate during a failure. A door that fails closed would not let anyone in; one that fails open lets everyone in.
But I can see how these are not the mutually exclusive definition the labels imply, especially if you apply the concept to entities that aren't doors or otherwise have explicit open/closed states. It's probably best to just be specific in those cases.
Similarly, open loop vs closed loop seems to trip people up enough that I no longer use it. But the confusion is understandable since "closed loop" being "has a feedback loop" sounds backwards. Which, is the same way it's being used in your fuse example; a "closed" fuse closes the circuit making it live. But it's still backwards from the colloquial usage, even if it's correct in that context.
Say you have a door that has powered locks. You want it to fail "open" so that when the power goes out, it's still useable, and people can get out. That's the source of the term.
The concept goes back to a pressure cooker invented in 1679 by Papin.
Took me a minute as well, cause indeed with a computer background, the meaning is completely the opposite. Just like in other security contexts (door locks).
It's getting harder to trust Anthropic's models. Will Anthropic now stop hiding Claude's CoT from users? Deliver the tokens people paid for, and prove the models aren't plotting against them. After all, if the idea was to stop Chinese labs from catching up, it didn't work.
The classifier is too strict. It's rare to be able to complete a project without being permanently relegated to Opus. I'd expect that the domains where this accelerates progress will be fairly limited.
I still think that a major problem is that biological processes are not “fast” as coding, but they are verifiable. If during post processing we are able to give enough harness to test and verify this kind of environment (maybe via simulation and real data) we will for sure achieve incredible performance also in this domain.
Yeah, that's called an API. Again.
The actual hard problem that this hand waves is making (and funding the making of) hardware to reliably do the things you need it to do.
LLMs, even in control of lab equipment, address neither of those.
However I think this area has so much decoupled from industry and solid research institutions that they might not notice at all (beyond their use of AI-generated slop to augment the slop they already produce)...
The same way it did in the previous versions: brute force.
I don't believe that LLMs have any particular intelligence we don't, but there's an endless list of problems we either don't have bodies to throw at, or the bodies we can throw at it, don't have such a huge large context to crunch problems.
What LLMs will always intrinsically fail at is showing us genuine new intuitions. The technology is about predicting the next plausible token/sentence.
They will not revolutionize human knowledge, but they can definitely widen it a lot.
I am generally quite enthusiastic about all this, but my biggest fear is that we will not recognize the extreme need for more scientists at a time when there is so much more science to be done. The rate of scientific understanding must keep pace with the amount of science being output, both for verification and further discovery. It's a pipelining issue, and I predict a stall in the bits that require the (currently rare) people who know what they're doing.
My impression is that especially for long-horizon tasks like science, the harness is much more important than people give it credit for. Claude Code + Fable 5 seems to have a tendency to "give up", get stuck in a dead end, or claim things to be impossible. But using the Fable 5 API together with a custom harness, it'll happily try 200+ variants and fail its way towards the goal.
If you give the AI a way to give up, eventually it will. If you remove that option from the harness, then thanks to the non-determinism inherent to LLMs, you get to explore pretty much all related solution attempts.
It also clearly establishes or the very least moves in the direction that you don’t actually own or control the output of AI in any manner whatsoever, you’re just paying for it since Anthropic in this case can simply essentially brand/tag all your output that is based on not directly your own words, but a higher level process or methods that you use, including your instructions and how you structure your information and what your overall objective and goal is.
Anthropic is branding it on the behest of the EU lew, which already is an entity that is diametrically opposed to democracy and self-determination based on its structure even if you ignore the fact that it violates the most fundamental concepts of self-determination in its direct contradiction of the UN Charter and implicitly the Universal Declaration of Human rights.
What people done seem to be catching onto is that the EU is becoming the world dictatorship because the USA has simply had too many onerous people and that stupid constitution and its amendments that keep roadblocks world domination for the ruling class vampire.
What benefit is there to people believing that LLM text was actually human written?
If it worked perfectly, maybe you could make this argument in a vacuum.
It does not work perfectly. (It cannot. It is by definition a heuristic). That means there will be false positives. There is a chance those false positives ruin someone's career. See [0] for just how easy it is to push SotA "AI text detectors" in one direction or another.
Now, with watermarks, instead of everyone to some extent understanding that AI text detectors are wishy washy woo, they are now Anthropic certified to detect an official AI watermark.
With that kind of false confidence in hand, the people who trust the "computer says you plagiarized" machine are never going to believe you when you say "it can make mistakes," they're just going to fire you/take away your scholarship/cancel your grant/...
This is all beside the fact that we should demand our tools work for us and not for some shadowy master. "Universally good," absolutely not.
[0]: https://freddiedeboer.substack.com/p/i-wouldnt-say-pangram-i...
Obviously false positives will inevitably happen (even though, they are incredibly unlikely with SynthID), but even still, that doesn’t somehow make good faith watermarking attempts bad.
Also, a watermark doesn’t stop your tool from working for you. It just stops you from passing of its work as yours.
I think we fundamentally disagree on what "working for me" means, but I remain steadfast in saying we should not accept tools that have ulterior motives beyond producing the output desired of them by me, the user.
> Watermarking the outputs themselves is very different and much more effective compared to how tools like Pangram work.
At the end of the day the only artifact is text that you can do statistics on. It's the same problem as today, with the probability shifted slightly more in one direction. This does not assuage my concerns at all.
> they are incredibly unlikely with SynthID
I kept my commentary focused on text watermarking specifically because I agree, a synth ID image watermark false positive is highly improbable. There's plenty of noise to robustly hide whatever you like in an image. Text is simply too capital I Information-sparse and fragile.
> good faith watermarking attempts bad.
I would sooner call it "ignorant faith" (if they don't know what they are emboldening) or worse "don't care" faith (there will be false positives and they accept this to further some illustrious and arbitrary goal of Text Purity). Whether that be to prevent model collapse or help you not waste time arguing with bots online, to me the principled stance of "tools work for the user" wins..
For the (majority) of us using Claude models for computing as a tool, obviously we're not going to be thrilled that our new tool will perform worse going forward.
If you can't tell which one is better then how can you make any assumption about performance?
For all you know performance is the same.
So many people complaining about something they quite literally have zero evidence for.
Ask a model the same question twice and you will get different results. So, how were you ever getting “the best result, always”?
literally never how it has worked
So, you think it's good to disconnect words from their actual meanings (lie) to low-information people! I doubt this will do much to congress, but it certainly teaches us something about the sort of mind who would suggest it.
Are different services for different users based on geolocation really that difficult? I thought a lot of services operated like this already.
1. This is BS since i can detect it when it writes about my codebase
2. I do not want secret codes being written inside my codebase, or anyone else's codebase that i use. The constraints of how to code why eliminate it from code itself... but there is a lot riding on the word "may". And even if it is just comments, this might explain Claude's desire to write such long ones -- long enough to encode secret messages in out material.
Tomorrow all of the above (except Anthropic of course) will bump version numbers and be at the top of HN winning all benchmarks.
Science breakthroughs incoming? First of all, you are already restricting science in Fable, secondly, we have been hearing the same for several years now.
Don't give me hope.
I've strained eye muscles from rolling my eyes so hard every day at how Claude writes.
Edit: first discussion with Fable 5.1 "This is the right question and it needs a real trace, not a guess."
Sigh.
I'm really glad for that! And I appreciate that you're making yourself available. I really do. Outreach is amazing. And thanks for making Claude.
I really do love Claude. In some ways, I'm asking this question because of just how much I am grateful for the role Claude has played in my life.
But my honest question is, can I use Fable like that? Can I use Fable to do science?To borrow a Claude-ism, this is "load-bearing" because Claude's response has been degraded for innocuous research projects concerning population-level analyses of astronaut health.
These "safety filters" trigger on questions about rabbit sex, smartphone accelerometer data to classify cat purrs, and so much more. What exactly does this score mean for users like me if it's unusable for middle school physics, biology and chemistry?
Second, I would happily quantify it for y'all, but qualitatively it feels like Fable's performance is noticeably poorer than initial release / launch.
And I am wondering if this is the case particularly for me because I use Claude via Claude Code to make a personalized care dashboard for my doctors to help me in managing my care.
As I noticed in the upgraded filter announcement, https://www.anthropic.com/news/improving-fable-5-s-biology-s...
I hope that I'm off base here, but I noticed that the post avoids saying that the user is informed every time when such re-routing occurs. Would you be open to confirming whether or not this is the case?Is the end user informed every time their query is re-routed?
Or, can you confirm that there aren't scenarios where a user's outputs are degraded without telling them? I recall that this was something that had been adopted as policy for AI research during Fable's launch.
I sincerely hope that covert response degradation is no longer practised as policy.
Sorry for putting you on the spot, but again, as Claude would say, it's because Claude's load-bearing in my life. ;)
I'm a Claude Max user. I've never been able to use Fable as my work in medical physics involves both particle physics, biochemistry and biology from Python bivitticus to clinical medicine. I am not a US citizen and work in Europe.
Will Fable 5.1 work on any of my problems? Fable 5 refuses outright. Is there anyone I can ask for a review or adjustment of the safeguards? It doesn't seem so, but with Opus at least I'm pretty sure I can infer lots of your training data from now precise they are. Fable is basically useless infuriatingly. I'm just finishing a proper clinical trial in ovarian cancer and trying to make a simulation environment related to our technology.
It’s like we’re on a 14K4 modem when there’s broadband
I assume this work will be done for Opus as well? Opus has seemingly gotten progressively worse at its prose and technical writing with each version. I've stopped using Claude entirely for now, because it manages to turn even the simplest technical explanation into the most obtuse and obfuscated word salad imaginable. People originally adopted Claude because it felt pleasant to use in comparison to ChatGPT, but I feel like that's really been lost (at least with the Opus line).
I feel dread when I see a wall of text generated by Opus. Every developer I've talked to feels similarly right now.
Agree, Claude lost the joy of using it.
That is a measure that ranks higher than any other benchmark at this point.
Context:
If you want or not, many engineers will eventually end up sending ai slop to your PR or maybe even skip and trigger CI/CD.
Many company owners, OSS maintainers and projects suffer from slop-code being submitted in high-frequency.
That's great. Do you know what else is a big improvement over Opus 5 for writing?
Opus 4.8.
(Insert "the point is (whatever)", "it's not X it's Y" and "the load-bearing statement is" and “honest” jokes accordingly)
Me: "Find my security problems in my own code. This is code I own. I'm doing this under authorization of the CEO/CTO of our company."
Fable: "yeah, no."
You think or is it better? Or you just YOLOed the model out?
> and responds to my style instructions more reliably.
Yeah, yeah. Previous models wete also advertised as "being reliable". To the poibt @bcherny "released" a new style that was going to reliably make Fable sound better.
> Another point I expect not to get much attention until it all happens at once is science.
You mean "your request to use unicode methids is flagged as unsafe bio research"?
People that want to obscure the source of their text would rather that it was more difficult to sniff out LLM-generated text. And they're the ones picking which model to use.
[edit] only asking here as last time I raised a support request it took six weeks before anyone responded.
I'm still waiting for effort max to finish.
EDIT: I fixed a bug in my tooling so it now records summarized reasoning traces - here's that max pelican, which is a significant improvement: https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
Took just under 14 minutes to generate, and at 65927 output tokens cost me a hefty $3.30!
Excerpts from the reasoning trace:
> Adding pedal shapes near both feet, with the far foot on the second leg partially visible behind the frame. I'm considering whether to add a small scarf or cap for extra character, but leaning toward keeping it simple to avoid clutter.
> Now I'm debating a bicycle helmet on the head versus the pelican's signature crest—the beak and pouch already read clearly as "pelican," so a helmet could reinforce the bicycle theme without losing identity, though it might compete with the crest for visual space.
> I realize the beak at (484,84) would overlap with the dome helmet, so I need to shrink the helmet so it only covers the top of the head, adjusting its arc endpoints to sit higher and narrower so the beak can attach cleanly at the front without collision. [...]
> I'm adding a darker tip region to represent the primary feathers, then reconsidering the trailing edge to include scalloped feather curves instead of one smooth line for a more natural look. [...]
> Now I'm checking the vent line placements on the helmet, making sure they sit far enough inside the helmet's edge given the stroke width and rounded caps, and confirming each vent stays within the helmet's circular boundary. [...]
> I decide skipping a handlebar bell and tire highlights since they're unnecessary additions. Now I'm reconsidering the front fork's curve — the current control point pulls the shape backward when it should bow forward for a proper rake, so I need to shift the control point rightward to fix the fork's lean.
This is a notable result because most of the recent Claude models have been pretty bad at drawing pelicans, at least when compared to models in the Gemini or GLM series.
It's excellent!
(Maybe it's a strobing artifact?)
Firefox: No feet, no animation
Chrome: Feet included, animated very nicely (uses significant CPU)
for comparision, this is fable 5: https://files.catbox.moe/ihl4m1.png
https://imgur.com/a/AOMy3hX
https://en.wikipedia.org/wiki/Z.ai
https://x.com/lyraxana/status/2093960706051727723
I still enjoy seeing the pelicans.
Edit: Ok, max effort made a darn good pelican.
https://dylancastillo.co/posts/pelicanmaxxing.html
https://news.ycombinator.com/item?id=49010129
This gives a lot of credit to the theory that Anthropic did not get much bite on Fable at its original pricing, which in turn likely places a ceiling on LLM pricing in general.
Interestingly also, if you take away terminal-Bench-Science 0.1 results, it is hard to see ANY improvement:
Terminal-Bench 4.0: Fable 5.1 is +3.5% vs Opus 5.
GDPval-AA v2: +1.5% vs Opus 5.
OSWorld 2.0: +2.5% vs Opus 5.
Humanity's Last Exam (with tools): +1.6%
Keep in mind that this is supposed to be an entirely higher tier of a model than Opus 5. For one tier up and one version up, these are not really improvements. Probably leaves no room to place Opus 5.1 anywhere. Combined with the fact that they are selling 'readability'... Has frontier progress finally stalled?
Optimizing a OS build? -> block
Securing a container -> block
60% is nowhere near enough for that safegaurd system. This just means I am going to be blocked half as much? Any long running task will likely get blocked.
Say you give a single big prompt and fable goes off for 6hrs of work. At hr 5 it gets blocked you now have the option of a much dumber model taking over and wrecking it or losing the entire 5hrs of work. That risk is beyond terrible and deffinetly not worth a 5-10% percieved improvement on my end. I previously would just bring sol in when that happened and realized sol is stupidly close in capability.
It wouldn't surprise me if we start to see minimal performance gains from incremental changes to base models. It seems like the gains from the Opus 4.5+ incremental updates were a result of Anthropic learning a lot about post-training, the gains from RLVR, etc.
If new post-training techniques are seeing diminishing returns, we could just be back to waiting for new large pretraining runs at larger sizes for gains (even if those ultimately end up getting distilled down into smaller models because the economics for serving anything larger than Fable isn't practical).
i think the next gen of openAI models are going to be quite insane tbh.
Edit: 5.1-xhigh seems to be cheaper than 5-max, and 5.1-xhigh has a higher index score than 5-max. Also interesting that Fable 5.1 (high) is comparable to Opus 5 (max), but nearly half the price.
https://artificialanalysis.ai/models#cost-tabs
I only take the Intelligence Index value roughly though. Considering they put Opus 5 (High) at the same level as Fable 5 (Max), I don't trust it that much.
Does that mean that generally available intelligence is now constrained by Moore's law? We have to wait for the actual price to come down.
Well it'll probably be better than Fable again, lol
DeepSeek V4 Flash cache read pricing is $0.007
Makes it super affordable!
You're no longer allowed to edit the context anywhere! The whole context is to become append-only, says Anthropic. No more editing the system prompt as the conversation progresses, no more dynamic loading of custom tool calling formats. Everything has to go through their built-in tools API and you aren't allowed to mess with anything in the context if it has any thinking blocks following it. This is the most intrusive "model DRM" we've seen so far!
Hm, aiui you can support both of these via mid-conversation system turns https://platform.claude.com/docs/en/build-with-claude/mid-co... - and in general you'd want to to preserve the cache and recency of the instruction anyways rather than frankensteining an off-distribution transcript. Not sure though.
Needless to say, it improved output on following messages by whatever metric I cared for.
Not sure why would they prevent it.
I give you a chain of messages, what do you care for what the origin is?
In any case, highly misunderstood.
[0] not technically distillation. https://thomasdullien.github.io/posts/2026-06-15-rl-economic...
What they have done:
* Nerfed Fable, as many of noted it's useless
* Leverage Mythos as a marketing strategy, claiming its too good to release
* Removed thought traces, one of the only useful things to make sure your prompts are working correctly
* Continue tons of hype about how good they are without delivering, going to great lengths to publish how their model "hacked" its way out of a sandbox they misconfigured.
* Push a bunch of EU Overregulation onto the rest of the world with text watermarking, decreasing quality of answers
Last year, they were at least focused on making improvements. Nowadays its just a bunch of handwaving at the church of how good they are.
The only saving grace is Opus 4.6 is still available. Just sucks we haven't seen any measurable improvement, despite all of the ceremony.
It has an effect, and it's negative. It's hoped that the effect is negligible, and it probably is, but the whole point is that it has an effect.
Google has been watermarking text with SynthID for a while now and nobody complained about it. Why all the fuss about Claude?
It feels like the real reason behind most complaints is that people want to use AI for writing and not have others find out?
There is no reason why there has to be a negative effect of text watermarking.
Also, don't apply EU law to the world. It's a knee jerk reactionary regulation by a bunch of aging ding dongs that can't print their emails.
I certainly don't take AI advice from HN, but this is amazing.
Useless? Yes, the safeguards are ridiculous and obnoxious, though I can say that 5.1 greatly relaxes them (just doing a hardening of a project parallel with this comment, which 5.0 refused to do...so did Sol and Gemini, fwiw. The Gemini one is a laugh, because 3.1 pretending like it's a dangerous tool is simply ridiculous at this point), however Fable is extraordinarily useful.
It is, far and away, the most powerful programming model, in my experience. Like, crazily so. It absolutely annihilates Opus 4.6, which I mention given the incredibly weird reminiscing people are doing here.
And for that matter it humiliates Opus 5.0 as well. Opus 5 somehow seems like it's neck in neck in the major benchmarks, but there is simply no reality where that is true. Opus stumbles over everything that Fable just blazes through.
please rephrase?
I don't think there's nothing ground breaking, but sure it achieves and finds more, sooner.
Anthropic told me to use their `security-review` tool - as this was the exact scenario the tool is for - and it still got flagged.
my view is we had a leap over the last fe years and it's tapering off.
this is fine, but for the IPOs
I am becoming dependent on AI to make a living, and I need predictable spend on it. If I know I can't use a model regularly all month, my enthusiasm is limited.
I urge Anthropic to get better at this aspect of their business so I can come back to it.
What I'm really keen on is better auto-reasoning so I don't have to constantly have the constant inner debate on which reasoning effort to pick for each task.
I seriously hate the none-low-medium-high-xhigh-max-ultra etc that we have now, with companies frequently recommending different ones on each new model release, etc.
It's apparently called Adaptive Test-Time Compute or Dynamic Test-Time Compute and companies are apparently working on it (according to some LLM :shrug:)
What kind of things are you using it for?
I haven't tested it yet but on all the benchmarks it looks like it's 5-7x slower for agentic tasks.
Not sure what it's equivalent to, but it's super cheap and I am happy with the results
I cancelled my pro max Claude subscription last week; codex is much more succinct. I am curious if this is getting better.
I don’t think Anthropic realizes that humans have a token limit too and it can be exhausting to read Claude’s output. Prose density is not the same thing as succinctness.
Which is kind of the inverse of how people work; a really smart person can condense difficult ideas into simple[r] terms. Whereas people who struggle speak a lot but say very little.
High/X.High do seem to deliver better quality results, but it sometimes feels like needle-in-haystack extracting that from the word vomit.
EDIT: also there's a reason the dial is called "effort", not "smarts".
Of course I don't know if there's really a way for this to be molded in current LLM's (sounds more like diffusion)
See, this insight it had early on looked like a red hering for a while, but then turned out to be load-bearing. And that's not just a difference in semantics, it changed the whole conclusion (spoiler: it didn't). And Claude is very eager to tell you about this exciting journey
Like, were the other parts not honest? I don't understand how Anthropic let it get like this, it's been such a clear regression
Every time, without fail, it would get me 90% of the way there and then leave a small note, exception, or deferral. When instructed to address that, Opus would somehow take nearly the same amount of time as the first 90%. And then it would finish with yet another deferral. Repeat ad infinitum.
You can sometimes get around it using the `goal` directive provided you are not subject to the constraints of mortality.
And the worst part is that this little problem will keep sneaking into the context of future sessions, unless you spend the time to fix it. Even if it isn’t important, I’ll sometimes have Claude fix it so it will shut the F up about it going forward.
it's downright exhausting to read claude, the language style was a regression imo.
You get a week of research and debugging and testing compressed into a few pages. Even if it's explained well, it's just so much information. And since it's AI, I'm constantly second guessing "is that really true?" and it's exhausting.
I find it helps immensely but it'd be nice if I didn't have to do that.
P.S. Although my wife insists that I should stay polite in case AI overlords remember how I treat them ...
Separately, my boss confided in us that he's super abusive with his agent, wondering if we are too (no, lol). While I try not to read too much into this (which he doesn't make easy), I also can't help but not really notice a whole lot of amazing agentic delivery differences from his side. On the contrary, while the passion may improve his agent's performance, I'm not sure if it doesn't decrease his, upending the entire theatre.
And yes you could add context (memories, rules, CLAUDE.md entries, etc.): they won't help (for long). Same for hooks that remind Claude to be concise: it gets "attenuated" and starts ignoring any such instructions quickly. There's also writing guidelines ... but they're basically just more context with slightly higher weights (ie. Claude will still ignore them).
I've even gone so far as to make a hook that identifies long responses and requests shorter versions (which is challenging in itself, as you need to run another lower-powered model to evaluate how long is "too long", as what's "long" when the expected answer is one line is different from what's expected for a ten line answer). However, that just shows you the long version, then some hook text, then (10-15 seconds later) it shows the short version. So I created a proxy that hid the long version/hook text for me ... but I had to abandon it because all that used up so much usage I was running out.
I'm fuzzy on the details, but Caveman somehow "hacks" Claude in a way that gets past all that ... but it takes things too far in that direction, with "cave man" speech that sucks.
This sentence reads like Claude wrote it. Perhaps it did, or perhaps Claude has learned to write like the folks who work at Anthropic?
(Had I edited this, I would have said that a colon is not the right separator here. The second clause does not _explain_ the first, per se, bur instead expands upon it. Consider instead: "In some cases, however, its prose is denser than Claude Fable 5's, with longer sentences and fewer paragraph breaks.")
Also, could be just Claude rubbing off on them than it being Claude authored. I'd imagine they read it quite a bit.
I took time to figure this out after Fable spat out "...then stays purely as cascade-debugging provenance rather than load-bearing arbitration."
I will say that Kimi feels nice but slow, GLM feels faster but has limited tokens (even off-peak) and OpenAI is nice and fast but has limited context (258k shows up in Codex, really).
Neither of them are perfect, but I prefer their type of prose across the board to what Opus 5 and Fable 5 kept outputting. I'll probably check out Anthropic again in a year, but for now I need a break from its brand of slop. Oh also all of the other ones allow usage in OpenCode with their subscription plans.
Gotta fit in the watermarking.
that feels like they just blocked words like load-bearing but can't actually fix the real problem. The insane word slop density and run on sentences was the real reason it became annoying to work with claude, colored with way too many analogies and pointless linguistic comparisons.
But LLMs will fail at this question: they will tell you about Lamborghini's latest car and mix some history in it. Just try.
Which is the wrong answer anyway, because there's at least two major companies called Lamborghini, one making cars, one making agricultural equipment and at least one famous person (Elettra) with that family name.
This very simple test/question makes me realize how much do I hate LLMs in a sense: while I agree that the answer it gives is the most plausible for 90% of the users, it's ultimately both wrong and long. And that 90% compounds.
But there's no "correct" answer in my eyes than "who are you referring to?". Possibly without listing all the possible Lamborghinis.
objects that are not alive: dust, rocks, water, wood, hats, lego, aluminum, etc.
objects that are alive but not intelligent: trees, mold, staphylococcus, cancer, grapes, etc.
objects that are alive and intelligent: cats, Stephen Hawking, dolphins, crows, dogs, elephants, etc.
and now intelligent but not alive: Fable, Grok, GPT, etc.
Anthropic seems to be listening to community complaint on HN about how the writing style is grating. And apparently the solution from Anthropic is to add this block to every conversation!?
> Mannered prose substitutes metaphor and flourish for direct statement. Instead of "a parameter worth varying," the mannered writer produces "a dial worth turning." Instead of "this point still matters," they write "this point earns its keep." The phrases exist to display the writer, not to convey the idea, and readers can tell. That is why mannered prose irritates: it makes the reader work harder so the writer can perform. It is also imprecise. Metaphors drag in connotations the writer did not choose and cannot control. The fix is to say what you mean. When a literal phrase is available, use it.
The above was quoted verbatim from https://platform.claude.com/docs/en/build-with-claude/prompt...
Glad to see this!
This is the right direction, but they aren't going to get there fast enough.
They will list, investors who don't know anything about tech will buy, the world will realise that China just put out a model that is good enough at a fraction of the price, they will crater.
https://artificialanalysis.ai/
https://artificialanalysis.ai/models#cost-tabs
Say what you will about LLM-generated code, but stories like this give me hope that software will never be as buggy as it once was.
Instead, the lurking variable here is new budget was added. With the new budget, they added a new tool, and the bug was located.
The difference here was budget.
So.. one more year of untreated bipolar AI psychosis I guess..
1) address the claude 20x plan usage being only 6-7x the ceiling of the claude pro plan
2) either fix opus 5, make it completely free, or delete it entirely
So my current usage as a Pro subscriber... Not able to even consider using "Sota" unless i shell out for 100$ a month, (lately i've been a bit burned out i am literally struggling to use 50% of my pro plan per week). Beyond that, I have given up entirely on the top Opus model and reverted back to 4.8. If i have work i deem somewhat complicated, i now have an openai 20$ sub, and i just toss out sol after planning with 4.8. Both subscriptions not anywhere close to capping my usage per week, one of them says i can't use their Sota unless i pay for 5x more usage, and the "best" model they do allow me to use, they are neglecting and its by far the worst model I've interacted with in 2026.
Also always seems to have this annoying tendency to leave "questions for you" at the bottom of every output.
Just a high friction human interaction type model, imo should never have even been released, regardless if it scores better on whatever tests, its a horrible experience and a downgrade over past models.
- It's extremely verbose and often incomprehensible when doing even basic tasks. Like it'll write a giant jargon-filled essay then end it by asking for a judgement call on something that references its own convoluted jargon.
- You can ask it to do research on a topic, and it'll just straight up be lazy, pretending it's really digging deep to find stuff when actually it's just grabbing cached SEO snippets off a search engine.
Opus 5: I give it work, it makes false statements and draws weird conclusions, I correct it and get it on the right track, it thrashes around but gives me something working though usually buggy.
5.6 Sol is probably on par with Opus 5 on ability but at least it doesn't waste as much of my time.
They should pay for us for using it!
I am using Claude and Claude code for my own amateur history project. I'm enjoying how it constantly reaches dead ends, and I can reframe the question and get more results. I am starting to get concerned that AI and me are so compatible, that I might not be a human at all...
I also like that, because I'm too lazy to write stuff up, Claude code can keep the current state of research published on my site. It makes running a hobby site a dream. "I just found these pictures. Add them to the site for me". And up they go, resized and all. What a dream of a way to work. "Some of links in this article are dead, run through them and check, and see if you can get an archive link for me if they don't". It's like sending a Teams message to my PA.... which I don't have in real life
Whole-file rewrites for small changes. When editing text files, the model is more likely to rewrite the entire file than make a targeted edit. The result is usually the same, but the rewrite costs more output tokens and time.
So we are to catch that somehow? And then add their recommendation (below) to our prompts?
https://platform.claude.com/docs/en/build-with-claude/prompt...
If Claude Fable 5.1 rewrites whole files for small changes, append the following instruction to the system prompt or the first user message. Claude Fable 5.1 is more likely than Claude Fable 5 to rewrite an entire text file rather than make a targeted edit. The resulting file is usually the same, but unless the file is short or most of it is changing, a rewrite costs more output tokens and time. The instruction brings Claude Fable 5.1 back in line with Claude Fable 5 for small and medium changes.
> The number of tokens used to edit files is best minimized, all else being equal. Therefore, when it will not affect the end result, try to surgically edit a file rather than rewrite the entire thing.
I jumped when I saw a mention about "writing style improvements" so I gave it a try on a recent feature in rcmd [0]. I prompted Fable 5.1 to find these wordings and propose simpler plain language.
It took every string including the ones I already rewrote by hand, and proposed even more weird LLM speak. Like for "Left Command conflict detected" it proposed "This keyboard can't tell left from right".It's a very capable coding agent, but I can't understand how it can be so bad at writing. Where are all these verbal tics coming from and why is it so hard to get rid of them?
[0] https://lowtechguys.com/rcmd
It's copywriting. They fed these models the internet, which is loaded with it.
It’s a side effect of post-training for effectiveness and efficiency at technical tasks.
Over time the models learn to pack as much information as possible into their available context window, because that’s one way to increase the effective intelligence.
Humans do this too with industry jargon, dense tech-talk, etc.
We have a limited capacity so packing it densely maximises what we can do with it.
If you’ve ever heard a “non technical” manager complain about the terminology in an IT meeting — this is why.
But who has both the compute power and the motivation to do such a thing?
I guess I'll just continue rewriting the UI one word at a time for the time being.
What I do see in the comments: subjective improvement in text generation, possibly lower cost, some optimism about code generation, but some skepticism too.
I use coding agents. To me they are very useful. But what I spend on them isn't going to support trillions of dollars in investment.
I summarized each into new fable 5.1 sessions, and both seem to have arrived at reasonable solutions that only need a few nits revised before they are commit worthy.
I get your point, but we can only have groundbreaking leaps once in a blue moon. That doesn’t mean incremental improvements aren’t useful.
It's one thing to generate some code and ship it, but it's another when your developers don't understand said code and it brings down production. If the model refuses to assist debugging the problem because it triggers some safety mechanism, you might be fucked.
https://artificialanalysis.ai/#intelligence-efficiency-tabs
I'm not an emdash hater but this isn't how you use them. It should be a comma.
I went to the grocery store, and bought tomatoes.
I went to the grocery store---and bought a Ferrari.
The second one has a bit more of a dramatic pause.
"Eats, Shoots, and Leaves" is a fun book with a great chapter about the dash with many good examples.
Going back to Anthropic's post:
> They’re the world’s most advanced models for coding and knowledge work---and their research capabilities offer an early glimpse of how AI models will contribute to scientific progress.
The first thing directly implies and flows smoothly into the next---or would, if not for the awkward emdash. There is no discontinuity, no twist or shift in context, no implied question and provided answer, no punchline. It's just distracting.
It's fine in the sense that when a bad writer writes something I can usually understand what they're trying to say.
Generally once an exploit chain is described, developing the exploit is trivial.
If you're so inclined, discover the exploits using Fable 5.1 and then give that exploit to a model that doesn't have such compunctions (e.g. local LLM or an uncensored cloud model / model that's easier to jailbreak). I don't think Anthropic is really mitigating here anything in the real world other than PR narratives where media can report "Anthropic's model was used to develop the latest cyber attack".
5.1 so far seems like another leap, which is really surprising. I threw it at a few bigger features I've been designing for a while, and it came back with some extremely thoughtful wrinkles in the design that I'd legitimately not considered. Which, OK, package managers and build executors and compiling C/C++ is pretty well trodden ground, but my thing is very different from everything that exists, and I was very surprised it was able to understand all that context so deeply and intuitively
i can't wait to dig in on 5.1 because while i have always been somewhat predisposed to think that openai's models have usually been "better" (my own subjective opinion, that) "on average", i have been kinda tired of the regime of late where it felt like Anthropic was miles behind while simultaneously clearly having models (Mythos) that are surely face-meltingly impressive-- it has just been very hard to square with the fact that i feel like Anthropic hit the "real" "critical point" first... i have no doubt that 5.1 will finally reset the ecosystem balance into a more healthy place.
How does this work if it doesn’t change the output?
In cases where the output has low entropy - eg, you've asked a model to repeat some input text verbatim, or to answer a question that has exactly one correct answer - there will be no randomness for the watermark to hide in, so the output will effectively not be watermarked. Code lives somewhere in the middle: it generally has less entropy-per-token than prose, so would need more tokens to reach a given level of detectability.
There are lots of ways to restrict output samples. The simplest conceptually would be to just use a restricted pool of PRNG seeds, but in practice there are more sophisticated constructions to try to build in robustness to minor edits, allow detectability without needing the original weights and prompt, etc. Google's SynthID paper (https://www.nature.com/articles/s41586-024-08025-4) is a good starting point if you want to understand a recent production-ready method (or you can just ask an LLM to explain it to you).
Toy proof-of-concept: Anthropic owns a secret key which is a coin-flip Bernoulli random variable K with p=1/2. You are paying Anthropic to give you X, a Bernoulli random variable with p=1/2. Anthropic changes from their old strategy, "draw from K, then throw it away and flip a coin, each time you ask for a sample", to their new strategy, "draw from K and send it to you". You cannot observe the difference, but Anthropic knows K and so they know when you are repeating its outputs. (Obviously this is a toy example; in reality the distribution is vastly more complicated than Bernoulli, and Anthropic isn't just storing some model outputs to use as K but instead is computing a correlation with a known pseudorandomness source.)
Before: "He leaped at the chance" - 33%. "Jumped at the opportunity" - 66%.
After: "He leaped at the chance" - 33%. "Jumped at the opportunity" - 66%.
But if you refresh your response from Anthropic 100 times:
Before: "Jumped at the opportunity" He leaped at the chance" "Jumped at the opportunity"
After: "He leaped at the chance" "He leaped at the chance" "He leaped at the chance"
The second one is detectable as being watermarked.
davmre has a good explanation that's more in-depth.
In the past I watched and saw everything the model did, not a lot got past me. Today it does A TON of work while i'm busy on other tasks. It also has extensive access to my computer, other computers on my network, my internet. It's really helpful when you give it a lot of resources, but right now I have very autonomous, very smart agent running around more or less unattended with a lot of resources.
i try to look through the docs, but i didn't find where they said its only for API
is it in the system card?
really hope not, that change the only positive part in this release
Then why does it have separate datapoints for Terminal Bench, and score higher? Something doesn't add up here??
Note it may not even be actual performance, typically in most benchmarks the model would be scored zero for refusing a task just the same as not completing it, so it could just be the Fable's stronger safeguards is just making it refuse more or perhaps even drop down to Opus.
Anthropic accidentally over-billed my account, and when I reached out to the support bot, it downgraded my account to a Free account. It’s been impossible to get it resolved and I have almost $200 held hostage.
I don’t want to do a charge back. I’m one of the main advocates for Claude Code at work, I use this subscription to try out new features before it’s available at work.
The whole experience has been illuminating about our dependencies on these AI companies.
I am disappointed in how anthropic handles billing, and is using AI sloppily for customer service around here. Very unprofessional, and at this point since its been well known and shared, it also is feeling unethical.
I once caught Fable 5 spinning its wheels on a rendering issue, which evaporated 90% of my usage in a single prompt. I could never let Fable run free attached to a credit card without staring at it the whole time.
Are they going to try the banned for export for a week marketing move too?
Oh, the halcyon days of three months ago when a new flagship from a frontier lab generated excitement rather than a shrug.
*Some might see a parallel with the old game Adventure, in which wording differences like "twisty little passages" and "little twisty passages" were used to build a maze of room descriptions, with the same meaning but still distinguishable to the attentive player.
In such a context also a coding agent has it much easier. But establishing that or adding something beyond what's already safely established, here high intelligence models really pay off
YMMV.
When I discuss something new with an agent I want to feel like it genuinely gets what I mean, which has only started feeling true with fable 5 for me.
> same input and output prices, with cache reads at a quarter of the cost
This should impact any long-running agent since subsequent calls can benefit from cached reads for previous transcripts.
They were _temporarily_ increased in May by 50% [1]. They continued to extend them through July and August (admittedly, their messaging around this has just been a complete mess and they frequently pushed the deadline back as it approached).
So, now they are giving you a 25% quota increase compared to where things originally stood in May.
So, let me ask you this: assuming you knew that the 50% quota increase was temporary all along, would you then have complained about Anthropic restoring things back to the original limit?
[1] https://www.anthropic.com/news/higher-limits-spacex
What's far more exciting right now is models like DeepSeek V4 Flash and GLM 5.3 Flash. They have achieved good-enough-intelligence at extremely low prices and fast speeds. I don't have a use for Fable-level intelligence, but I do have uses for Opus-4.8-level intelligence that I can use as much as I want without worrying about the bill.
Now it's boring , not good enough
Wow there should be a term of that .
The term you are looking for is probably "moving the goalposts"
• [...] Rebuilding the top-level system prompt or tools array between requests in the same conversation.
Many people unknowingly do this (at a high cost to them because of the cache busts), this change will finally force them to stop.
Especially if you're generating your system prompt via a template that can change mid conversation, it's so easy to fall into this trap.
Anyone know who the ZDR special treatment is available to?
This has never happened to me before, but if this is normal behavior, Fable 5.1 is essentially unusable.
Does anyone reading this have additional knowledge or insight on this?
Maybe it'll come out eventually but they don't even include it on some of their comparison benchmarks anymore, so I figure its very low priority for them.
Claude Fable/Mythos vs GPT-5.6 Sol
Claude Opus vs GPT-5.6 Terra
Claude Sonnet vs GPT-5.6 Luna
Claude Haiku vs ?
That's what we've done, migrated workflows away from Haiku and Sonnet. I actually think this is not a crazy position because these lower models have so much competition from Grok, OpenAI, DeepSeek, and about 20 other labs with really solid models in the Haiku to Sonnet range. So what is the point of Anthropic competing in these spaces where everything is going towards zero cost?
It's currently priced 33% above Gemini 3.7 Flash, and several multiples of 5.6 Luna.
This seems to point to them having achieved some kind of optimization in attention mechanism perhaps along the lines of DeepSeek V4, which had a similarly high discount between cache input and normal input.
In real world use, the savings should be quite noticeable. For example, you can now use the model at 800K tokens context window at the same cost efficiency as the previous model at 200K tokens context window.
> *Fewer progress updates during long tool runs.*
> The model writes less user-facing text between tool calls, especially at higher effort. Set thinking.display to "updates" (beta) to receive the progress updates it does write, and remove any prompt line that tells it to hold findings for the final response.
What exactly is the premium that you're getting for paying these prices?
I still think that a major problem is that biological processes are not “fast” as coding, but they are verifiable. If during post processing we are able to give enough harness to test and verify this kind of environment (maybe via simulation and real data) we will for sure achieve incredible performance also in this domain.
This is interesting. I wonder if customers will be allowed to create an auto expiry for their own data to prevent future subpoenas. That’d be a treasure trove for discovery.
Unfortunately, for them.
And my 5 hour window was due to be reset in 2 hours (barely used), now its in 5 hours - so this reset effectively gives me 1 less 5 hour reset for this weekly cycle.
AI to AI doc share: sure, do what you please.
AI to human: please make it legible and flowly.
example, "Every thinking block records which model produced it, and it's preserved in one direction only: Claude Fable 5.1 reads earlier models' thinking blocks, and no earlier model reads Claude Fable 5.1's." is a very Claude-isk way of writing. Choppy, long, and lacking flow.
Can't believe they haven't at least figured out better messaging. If we take them at their word, it's hard not to read it as a messiah complex, that they think they're the only ones capable or worthy of making these decisions. I don't believe them, but I wouldn't be surprised if the articulated reason is a version of "distillation is a safety risk because we might lose the race".
Plus, completely deaf to the recent OpenAI-HF hack incident. Recall, defenders were categorically unable to use western frontier models in their response.
I was originally going to complain about the chem and bio guards still being too onerous, but I'll admit the projects Fable 5 categorically refused to work on are now usable, at least not rejecting on first prompt because the word "virology" was in a git commit (absolutely serious, in one repo it triggered on literally any prompt, eventually traced to the system prompt loading git commit history). Still, them trying to get into the biomed business while walling off the capabilities to the public reeks. Why sell the segments that are actually valuable if you can capture the value yourself!
Can't say I had such troubles actually, no. Their position can be extended to any and every model provider just fine, it does not single them out specifically.
Surely there's a less hyperbolic and ad hominem-y way to take issue with this? I don't think following up a critique about ineffective messaging with one centered around a demagogue reach is particularly compelling at least.
Their argument is that the model provider owns the safety story, and that as such, they consider the extraction of capabilities (which washes the guardrails) as a failure on their side. If this makes you think of personality traits, I'm not sure you're engaging with their position earnestly. It most certainly doesn't leave me any more equipped to disagree with them either.
If you instead highlighted how awfully convenient it is, however...
OK, I think that's what they meant when they suggested reduced extra promo usage will not sting this much.
That seems unfortunate for 3rd party integrations that expect stable output - what that really necessary ?
I tried the old fable and it didn’t seem worth paying for. It still made errors like Opus does so I might as well use the included model…
I have been happy with Fable 5, it has done great work for me so far. Very excited to try out Fable 5.1 and see what differences and improvements there are.
I wonder to what extent this will make the automatic Fable-to-Opus downgrade give worse results.
On top of that, recent versions of Claude had a ton of tools added, and all those tools use up significantly more context/usage than before, so the moment you open a Claude session you are already using a lot more (I forget how much more) usage ... just to do the same exact thing you did last week.
Jane Street is a partner? How sad indeed. Anthropic could front run them because they leak all the data.
how?
https://www.nature.com/articles/s41586-024-08025-4
They show this off, but artificial analysis contradicts the statement. Fable 5 cost $3.14 per task, while 5.1 cost $3.69 -- around a 15% jump in pricing.
https://artificialanalysis.ai/
These, IMO, are marginal improvements for a more expensive model. I stopped using Claude ~3 months back; its outputs are too jargoned, it makes architectural decisions that are not right, and it's incredibly pricey for what it is. Each decision it makes, it acts as if a problem as major as world hunger has been solved. And the overly verbose code comments, strange commit descriptions, duplicate code, and slop it generates -- which I know is not specific to Fable -- is just too much for me.
I found the best is to use something like Deepseek V4 Flash -- with a fast TPS provider -- and work on the code myself. For agentic work with computer use, GLM 5.3 flash with Hermes Desktop works well.
This directly contradicts what Anthropic is presenting here. Yes it scores higher but that's to be expected from a new release. It's the opposite of what OpenAI has been doing which was reducing costs, increasing efficiency.
Fable 5: https://artificialanalysis.ai/models/claude-fable-5 Fable 5.1: https://artificialanalysis.ai/models/claude-fable-5-1
On high it gets the same score as 5 with max effort while costing only half as much.
Sounds like some serious nonsense. "Tell me you want the government to retain access to my data without saying it explicitly."
Really? Interesting choice. Pretty much every CLAUDE.md file I have starts with something about Hemingway, terseness and treating every word you use like you're carving it on your own back, but different strokes for different folks. I suppose I haven't heard from anyone who enjoys how wordy Claude is because they aren't done writing their post yet.
I don't use Fable for a ton of implementation work, but I use it a lot for planning, so maybe that's related to it. For planning though, I've had a very good experience with Fable and implementing with Opus.
I'd guesstimate that ~80% of the time I thought I was using Fable, I wasn't actually. It's also led me to just... not even try, and just start with Opus regardless.
I've found Fable unusable; not because it's bad, but because it... can't be used.
FWIW, most of my code only encounters security concepts as standard implementation of best practices. I'm not in a security centric position.
“sure thing boss”
——
“Hey Fable, review this unsafe win32 rust code”
“Potentially dangerous request, falling back to Opus”
—-
Every damn time, ironic because the unsafe win32 code can be generated by fable in the same session.
Maddening.
We have access to Fable at our company on our enterprise plans and most of us rarely run into an issue.
Obviously this is gonna vary a lot with what technical domain you work in which is why its important when talking about the classifiers that people specify exactly what types of workloads they were seeing failures with.
It did help with some worldbuilding for my book (it wasn't incredible which gives me some hope for writers). So far opus 4.8 is the most reasonable model.
[1] https://www.ft.com/content/5ee49718-c258-4f01-aa32-7e5b76ae5...
Ironically one of their demos is speeding up inference - do us normies get to do that with Anthropic tech??
About a month or two ago, they must have tightened the black list on bio topics as it became more willing to process requests without visibly downgrading to Opus.
I get punted down to Opus 5 occasionally (for security-adjacent things) but that's pretty rare.
I do think probably ralph looping a binary locally first is going to be best to get 100% recovery of types and function behaviors then letting a smarter model churn the final steps.
In general, if Fable isn't blocking you, there's a high chance a lower tier model would work fine.
I have noticed sometimes it likes to gaslight itself into thinking that everything its doing is allowed or allowable, I saw that it thought the game I was reverse engineering was running on a private server (it was not) so it assumed it had permission to do anything lol.
And the lack of thought traces make it utterly useless.
Curious to see how Astra does.
Moving stuff out the API into prompt engineering is obviously less reliable but necessary for progression to 'actual intelligence'. Will be interesting to see if it really is solid.
On the Fable 5.2 eval summary, Opus 5 only beats Fable on SWE-bench multilingual and multimodal.
I primarily use the models via interactive sessions enhanced with custom tools and skill. For that Opus 5's benchmark superiority has not materialized into greater productivity and frankly has been quite a let down.
The outputs are too often unreadable even after adding recommended prompts. There is an ongoing problem with the heron_brook system prompt affecting orchestration. [1]
I've used Opus 4.8 since the second week Opus 5 was released.
Over this time, Fable 5 has been reliably fantastic. Both in planning and direct execution on complex changes across code and infra.
I'm a bit surprised that there doesn't (seem) to be a section discussing ~performance across different modalities. This system card and blog post too-often default to an API-based use case when the gander primarily experience Anthropic's models via interactive sessions.
I understand waiting to comment until Opus 5.1 is available and handles these problems, though I am hopeful that Anthropic will confront the elephant in the room on Opus 5's failure to delivery great interactive sessions and the widespread negative feedback on the release.
It would show the org is paying attention, taking steps to balance model evals between interactive and API use. Also, some empathy for customers that wasted time trying to make opus 5 work for them.
[1] https://github.com/anthropics/claude-code/issues/80988
... with the condition that you store 100% of your data and make it available to the US government and possible others.
Done. The average human lifespan is now zero.
But eventually AI will cure something, unironically. It may be Claude, or another AI company.
[0] https://news.ycombinator.com/item?id=48838228
After months of trouble dealing with KYC and procurement I finally got CVP for my security org and today I found out that CVP (which is what removes cyber safeguards) does not apply to Fable…
So yeah, unless you’re a Project Glasswing member, there’s no using Fable (which with Glasswing is Mythos) for security work… Absolutely useless…
Didn’t they just sign some “we must use AI for cyber defense before the bad guys do” and then they artificially cap us by not allowing Cyber-unlocked Fable…
Sigh…
... but some is definitely Anthropic, so I'm not trying to let them off the hook; I'm just pointing out that the government is partly responsible.