Claude Fable 5
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System Card [pdf]: https://www-cdn.anthropic.com/d00db56fa754a1b115b6dd7cb2e3c3...
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Discussion (1283 Comments)Read Original on HackerNews
One that I'm willing to share (albeit from just a week ago) - I built a Python library last week that bundles MicroPython compiled to WASM to create a sandboxed code execution library: https://github.com/simonw/micropython-wasm
I just told Claude.ai (not even Claude Code - this was the standard Claude chat interface) running Fable 5:
A few prompts later (and I uploaded the zip files from https://github.com/brettcannon/cpython-wasi-build/releases/t... because Claude chat can't access those files itself) and I have a wheel file that bundles Python itself, compiled to WASM: Here's the transcript: https://claude.ai/share/a73b8b8b-8ebc-4fef-9e5c-7438e5e7ae35(It's possible Opus or GPT-5.5 could have done this too, I've not tried the exact same sequence. The Fable vibes are good here, though.)
> Fable 5's safety measures flagged this message for cybersecurity or biology topics. They may flag safe, normal content as well. These measures let us bring you Mythos-level capability in other areas sooner, and we're working to refine them. Switched to Opus 4.8. Send feedback with /feedback or learn more
I'm working on an internal tool that does new business prospecting data collection, scoring, etc. This is ridiculous.
I see a lot of people saying they are happy with weaker models, but I am the opposite, I need more strength, more intelligence!
I am quite happy that opus 4.8 can do some medium intelligence problems. And maybe Fable 5 can do some more more of those! I have a lot of problems to solve!
These are not Fields medal type problems, nor know difficult/open conjectures. Just small stuff I have collected in my todo list over the years.
[0]: https://github.com/eryx-org/eryx
It feels like you can give it a big chunky problem and leave it alone and it gets it done, with less questions and fewer design decisions that I wouldn't have made.
In reviewing its code I'm finding less to complain about than Opus. But it's all vibes, if you want a more scientific comparison you'll have to look elsewhere.
It made sense for people doing proper and fair AI breakdowns waiting on an embargo, but now it's just slop I don't trust anymore.
Update: looks like I've spent $82.92 in Fable 5 API priced tokens so far today (still all included in my subscription.)
Here's a TIL on how I'm calculating spending using AgentsView: https://til.simonwillison.net/llms/agentsview-custom-model-p...
• My most noticeable immediate jump was in how its frontend design was much more intentionally crafted, and delightful without feeling like 'AI vibe coded'; with better end-user usability too.
• In some internal agentic harnesses, it achieved better results with about half the tokens, making it cost the ~same as Opus 4.8 price-wise! The real price increase is less than 2x; with biggest differences in harder problems where Opus 4.8 struggles (or needs many turns).
• Part of the token efficiency improvements come from Fable doing more targeted and surgical diffs, with less non-necessary changes. This is great, because PRs often have less LoC changes for review. It writes more maintainable code without explicit human steering.
• For general conversation and assistant style use cases, didn’t really notice a difference vs 4.8.
• 1M context window, without increased pricing for long context is AWESOME. This is a massive win.
• The classifiers are super aggressive and sensitive and this does happen for very benign, non-security coding tasks. Fallbacks to 4.8 worked like a charm; but the filters are definitely super sensitive.
Overall, I would describe this as a step change and worthy of the "Claude 5" model name. It did take some time to understand the intelligence ceiling of this model; and even with an extended testing window I'm still discovering new things and often surprised (in a good way) by the model.
It felt, at least for me, light an impressive step up. Opus 4.8 was already very thorough; but sadly verbose and ‘loopy’ when you push back on its plans. Fable is what I’d use all day if I could afford it!
This is still not in the range of shippable UI for top end companies. Maybe for internal tools and enterprise.
At our comapny we limit to protoypes at most and even find it limited there.
Look, I don't want to argue about something dumb like that, but you can give it basic instructions of what the UI should look like, how to group things, and an example image from a designer, and it will nail the result. If you don't think that's incredible, that's fine. I do.
Opus 4.7 made this a practical approach. 4.8 improved it. Fable 5 has improved it more.
so this is why claude talks like this, i was wondering where it was getting this verbal tick from.
Given the shit we've seen shipped by "top end companies" (all the way to Apple) I seriously doubt that. I'd say you're nitpicking from an artistic point of view or something.
I assume it might be a good barometer for generalised intelligence; esp in the visual space.
Edit: It did correctly identify that transparent huge pages were off in its sandboxed environment and that enabling it was helpful, so that's nice. It also noticed that we skip THP on a certain less used path.
More importantly, I'm finding that the code that it produces for its experiments is a lot cleaner than what I'd expect out of Opus; there's fewer useless comments and it's more surgical and readable. I wonder if that explains the increased scores on benchmarks measuring mergability.
> Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT). These interventions will not affect the vast majority of coding work. We estimate they will impact ~0.03% of traffic, concentrated in fewer than 0.1% of organizations
Just need to wait for this thing to be open sourced :)
lol it won't tho...
https://mimo.xiaomi.com/blog/mimo-tilert-1000tps
The reason we are not being attacked is not lack of technology access.
Security in the form of "pay to play" is just kicking the bigger issue down the road.
sure, a malevolent state actor could swing it, but they could make a bioweapon without Mythos's help already.
also, vaccine production and disease surveillance have ramped up very quickly. they will ramp up further, despite political setbacks. it's a cat and mouse game that favors the defenders IMO.
but the bioterrorism narrative is useful FUD to spin open-weight models as existentially dangerous. I am far more worried about Anthropic's own goals than the goals of some crackpot in a shed.
At the scale of API requests that Anthropic sees, I think the affected organization count might be substantial, and they might not be getting the full model capability that they're paying top $$$ for.
Also, wonder how they arrived at that estimation.
I don't even think they can believe it themselves, it's in reality they are just trying to throw fear, uncertainty and doubt about potentially cheaper offerings.
The fun part is that you will never know if your neural net classification project is getting silently sabotaged because their classifier doesn't work!
With this in mind, I don't want model to be proactively instructed and encouraged to sabotage without telling me.
Cool, good to know I can trust Anthropic.
this is LLM, it's not like a science or something.
Am I to understand that this is essentially their form of social-platform ghosting instead of banning?
So they're not even going to tell you that the question you're asking is against their rules, they're just going to twist up your question and/or the answer somehow such that you waste your time essentially?
It seems like I ran into this EXACT same functionality from Claude many months ago when I was trying to ask it to research on the web and help me setup the ideal llama.cpp config for local llm inference.
Funny how lost it got through that relatively simple install when we had all of the documentation in the world (and a human dev with 20+ years experience guiding it along) to go by... and simultaneously it's debugging and building high level cryptography code in rust in the other terminal tab.
This is infuriating to learn.
I tried the same prompt on gemma4 and qwen 3.5 and Gemma consistently failed to call the multi line edit tool.
Come on guys, why can't everyone just be there for the good guy?
and they want me to pay $100+ a month to be their training?
i hope we can find morality again.
When GPT 4.5 launched, the gains compared to the model size didn't seem that great, leading some to believe that the only progress we'd see would come from RL.
This model certainly has quite a "substantial amount of post-training and fine-tuning", but it's also based on a new pretrain[1][3], which given the cost, indicate that it is in fact quite a bit larger than Opus 4.X.
[0] One of the early testers mentioned: "As far as I can tell from talking to people internally at Anthropic, there's nothing special about architecturally"[2]
[1] Section 1.1 in https://www-cdn.anthropic.com/d00db56fa754a1b115b6dd7cb2e3c3...
[2] https://youtu.be/GrdEid8H6H4?t=168
[3] There were rumors going around when Mythos was first announced that it was the first 10T parameter model, but I can't find a verifiable source for that number.
It turns out that having a text based interface for a text-trained model creates a very nice feedback loop.
Right now as we speak, people are generating text traces on anthropic and OpenAI servers that teach their models to do everything under the sun, text wise.
So people right now getting super mad at how dumb the model is when reverse-engineering a super complex function from binary, when they write “stop, you dumb robot, you are going wrong, go this way thank you very much” are actually leaving a lesson in the form of the "chat" text history.
Some may say that each bad word get us closer to ASI.
That and obviously the order of magnitude more efficient GPUS we got that allow for different tradeoffs at training time.
This seems like the pharmaceutical method of get them hooked on the drug with free samples, then once they can't live without it, raise the price. I'm not sure I want to start using Claude Fable on a max plan if it's just going to go away on June 23rd.
But maybe the more charitable reading is that they didn't have to offer this model at all on those plans and they are giving the standard free trial.
API Error: Server is temporarily limiting requests (not your usage limit) · Rate limited
Limited "free" time is what game developers do if they want to stress test the infrastructure code until it breaks.
For the stuff I've thrown at it, that configuration has done a really great job. Including 70+KLOC go proxy with extensive test suite, some retro games, and more.
There's a quote from a METR report on page 52:
>We ran [Mythos 5] on 38 of our hardest software tasks, including tasks centered around R&D. [Mythos5] generally outperformed an early checkpoint of Claude Mythos Preview in these, including by succeeding on some tasks that had not been solved by any public model we have previously evaluated. However, we still observed the model occasionally failing to correctly interpret nuanced instructions in difficult tasks... Based on the available evidence, we believe [Mythos 5] is likely unable to fully and reliably automate R&D for frontier projects spanning multiple weeks. We believe that a better, more confident assessment would require more time, evaluations, and information from the model developer.
this is good news, right? right...?
- Opus 4.7 xhigh: 5.2%
- Opus 4.8 xhigh: 13.4%
- Fable 5 xhigh: 29.3%
Seems like a huge jump.
[1] https://cognition.ai/blog/frontier-code
1. That estimate could easily be wrong.
2. That estimate is, of course, usable in RL training. This isn't an inherently bad thing, and this is more or less what has improved coding models so much lately. But it does mean that other companies could and surely will do this sort of training, and Anthropic probably did too.
3. OSS maintainers are far from perfect, and there's an unfortunate uncanny valley-like effect in which a coding model can produce code that is just convincing enough to pass review even though it's actually totally wrong. I don't know whether this is a specific issue here.
prior bms relied mostly on unit tests or synthetic judges which are easily benchmaxxed, which leads to nobody trusting benchmarks
we need people manually checking the data for good code quality
this benchmark looks very good from the methodology. a cog researcher checking the data themselves is very high signal (not scaleable so don't take the benchmark as gospel, but directionally good)
TL;DR - they worked with OSS project maintainers to build tasks. They score models based on whether a PR is mergeable. All tasks are graded by a human researcher. SoTA models have hill-climbing to do which raises the bar and inspires confidence. I'd say it's legit.
[1]: https://x.com/cognition/status/2064061031912288715
they aren't married to a particular lab, most of their usage is their in house model i believe
EDIT: Oh I see, this is the best link for pricing https://platform.claude.com/docs/en/about-claude/pricing
So the price is double across the board...
From their pricing page, Opus 4.8 costs $5 per million input tokens and $25 per million output tokens [1].
[1] https://platform.claude.com/docs/en/about-claude/models/over...
Input Price $10/M tokens
Output Price $50/M tokens
Cache Read $1/M tokens
Cache Write $12.50/M tokens
2x Claude Opus 4.8, same as Claude Opus 4.8 (Fast)
Frankly, not even Opus 4.8 would be enough of an incentive to use at that price range (enterprise-wise; would not even bat an eye as a consumer)
whats the logic in claiming its a borked metric when everything listed is an anthropic model.
* From today through June 22, Fable 5 is included on Pro, Max, Team, and seat-based Enterprise plans at no extra cost.
* On June 23, we’ll remove Fable 5 from those plans. Using it after that will require usage credits. If capacity allows, we’ll extend the included window.
* After this point—when sufficient capacity allows us to do so—we aim to restore Fable 5 as a standard part of subscription plans. We intend to do this as quickly as we can.
The "offer, then remove" aspect is a bit eyebrow-raising -- it feels like they are trying to get subscribers to switch to usage-based billing, which makes me wonder if we'll ever get it after that June 22nd window.
If they didn't announce it, you guys would be complaining about slowed progress.
If they didn't release it, you guys would be complaining about fake promises and marketing.
If they released it without limits, the complaints would be about slow responses and outages.
If they didn't add to susbcription plans, the complaints would be about phasing out subscriptions.
If they added to subscriptions with cost reflecting their resource availability, the complaints would be about how quickly it eats limits.
So they choose the middle ground of providing some initial access and assessing if they can satisfy demand, only to still be ignored and accused of trying to get users hooked?
We've already seen that they don't have enough compute, thus the deals with SpaceX for their GPUs. It's very reasonable that they just don't have the capacity to support the subscription userbase on this model.
If Anthropic was serving LLMs profitably it wouldn't be a problem. This is a dead business with no path to profitability and they're desperately trying to get people used to usage based billing, because they need it to become the norm to survive.
I can recognize so much of the GPT/Codex generated code long after it gets merged (not by me).
Additionally, the time spent on every agent turn on GPT 5.5 is much longer compared to Claude Opus 4.8, which means iterating on the code takes a lot more patience, and there's a lot more nitpicks to pick when actually using GPT 5.5 to do software engineering.
Feels like GPT-style models are more geared on doing one-shot software vibing (and handling the vibe coded mixture) compared to Claude's focus on actual software maintenance. I got a GPT Pro sub for free and wanted to cancel my Claude subscription so much, but I still keep reaching Claude models a lot more. Frustrating.
this is the line I keep in Agents.md that helps me prevent Codex from playing smart
ai llm are doing what i tell them to.
if you’re building something meaningful (in my case a platform used by many people across many companies) you want to ensure you
1. have actual systems engineering and architecture in mind that you want the models to
2. implement based on what you tell it to do
when i was just telling the models what i want done without doing due diligence it would go and do some moronic implementation that was awful. mid input = mid output
these days i just maintain specifications documents and the AI follows everything i tell it to in that document. so when i tell it to dos one thing, the result is made following those architecture specs.
i have code that is single resp, modular, easy to extend and test.
i would ballpark 95% of the time i get what i asked for.
sometimes it tries to be clever in cases that weren’t covered in my arch specs. in those 5% of cases i go and update my specs.
source: used billions of tokens worth to build something actually in production across both mobile platforms and web, deployed on my own cloud infra. i use codex mainly. some claude.
But Claude models seem to be better at long term problems or more ambiguous problems.
I'm curious as to what the primary benefit here. Are there secret improvements in training? There hasn't been much in fundamental model architecture, I don't think. What about harnesses? I wonder what's pushing the AI. It seems like harnesses is the main thing pushing AI ever since CoT.
I think the end game is routed model usage and SLMs. I think Apple is going to prove this in the consumer space pretty handily and I'm curious how the Android ecosystem responds since the hardware is considerably lacking in model performance. I think Apple has a huge opportunity here, as much as I don't like their current ecosystem of walled garden. They did position themselves very well with ARM and custom chips for their hardware. Hopefully the broader ecosystem of ARM and Linux are able to make some headway and we see a more formalized, and broadly accepted, architecture to capitalize on.
Most AI companies are just testing the waters with paid tiers right now, their greatest fear with increased pricing is folks reverting back to wikipedia, stack-overflow and other public domain organic activity buzzing back to life; that will kill any RoI potential in LLMs forever. They're playing the wait game instead, observing how the digital sphere reacts to every little increase in price.
If that weren't the case, they'd be pricing at lucrative premiums already and even gotten away in short-term considering the increased dependency in the enterprise world. But that'd be like killing for the golden egg too soon and losing all long-term potential.
Once the folks are so addicted to LLMs that even writing a hello world program sounds like a nightmare and coming up with an article draft feels like reinventing Egyptian glyphs, that's when the real pricing hammer will come.
It's worth it, and I can afford it, but I am not really the right type of user for token-based usage. It's all for personal and free work.
Anthropic wanting to switch billing to API rates is them just wanting to generate more profit.
Though the day is coming when there’s no distinguishing, I’m sure.
I'm doing basic web development here utilizing animejs. Nothing too complicated (mostly saving time doing the scaffolding, still write the bulk of animations manually).
Truly believe that American companies are going to get completely curb stomped by China due to greed, ineptitude, and violating the social contract.
Deepseek V4 Flash is suprisingly capable and insanely cheap. It takes so much to get the session cost to get to $0.01.
I agree with you on pricing, but what do you mean by this?
I am on the $100 Max plan.
I do wonder if you switched models mid-session, you would have lost all your cache. Reloading the context into cache can really eat through your usage.
I had it analyze a project I was working on with Opus 4.8, and it blew through 23% of my session limit in one go. Does not portend well for my budget.
> Fable 5's safety measures flagged this message for cybersecurity or biology topics.
> They may flag safe, normal content as well.
> These measures let us bring you Mythos-level capability in other areas sooner, and we're working to refine them.
Here are the results of the agentic code review session:
This 40 minute session cost me 16% of my weekly usage. A simple code review of the most critical areas of my project got flagged as a cybersecurity risk. It really made me not want to try it again.They also, FWIW, say that they've instituted new policies on their end such as logging any human access to the stored data and automated deletion after 30 days in "most" cases (with another link to a document detailing that further).
Assuming this isn't just a supply issue on their side, nothing says "ethical AI" like only allowing mega corporations to use it through cost barriers.
How many government sanctioned school bombings does it take for them to quit working with said government? For now we know that number is somewhere between infinity and 1.
(I’m highly confident open models will eventually achieve a similar performance benchmark with distillation over time)
I just use dumb and fast models now. I'm more engaged. I think that the higher the quality of the model, the more you tend to vibe with it, and then the more hallucinations you then miss. I'm not sure which is more productive, but I definitely burn out faster the more I vibe. At some point you're spending your time on forums, discord, or youtube instead of engaged with what you're building. Or you yak shave about your tooling and end up creating the 600th multi-agent gastown harness and blowing thousands of dollars on tokens to create it only to discover it's too expense to actually use.
Upd: I meant big picture, not with respect to this model release. Where do subscriptions figure into their strategic vision. Will consumers end up paying enterprise prices in the future?
why do they have capacity now that they wont in a few weeks?
Why wouldn't Anthropic just wait until people start subscribing, do some kind of marketing push, or obtain some kind of other sustainable revenue stream, before they go IPO? I wonder if they see the writing on the wall with all of this and want to cash out as quickly as possible?
Specifically they need businesses that fired people and adapted their business to the products, so when the unsubsidized costs hit the businesses are forced to eat the true costs.
Yes they can't afford to give the products for free, but what is essentially happening with AI services is economic dumping, keep costs artificially low to get people to fire everybody, and then Jack the rates once they have Monopoly control
I agree. They need addicts, but they are high on their own supply and everyone else can see the danger in getting hooked.
They'll probably tighten the quotas to reign in whales though.
Realistically I think Anthropic just has insane demand but finite capacity to run models, and Fable will just make them more money if they dedicate it to API pricing. I suspect the goal here is something like: get individual engineers/PMs on their personal plans to taste Fable and then go to their meetings and say "Yes doubling the price of every single input/output token is a good idea, boss".
The only reason why I pay $200 is because LLM's errors costs me that much, at worst. If "make no error" starts working - sure. But surely, unless you have millions of dollars of cash to burn, a coin flip that costs $5000 is an insane idea?
Going PAYG only will effectively take these tools away from a huge amount of people and accelerate the push for local LLMs.
OTOH, accelerating the push for local LLMs would also be fine with me.
The AI landscape is changing rapidly, and with Apple announcing the option to change the AI backend, and potential requirements enable AI choices as well, similar to EU browser choice requirements (this is more reading tea leaves than any actual requirements I am aware of). The new OS changes coming to support Googlebook, and deep Copilot/AI integration into Windows will make maintaining user facing subscriptions essential for independent model developers like OpenAI, Anthropic, and Mistal to remain relevant longer term.
If the don't maintain that relevance there is increasing likelihood that they will get consumed by other companies whether it's Apple, Microsoft or Google to form a foundation for their OS, or other cloud providers.
It's kind of annoying not getting access to the primo model and paying 200 bucks a month. I understand 200 bucks a month is basically nothing though.
Like I don't totally understand why they'd let me have it for a couple weeks and then take it away and say I can have it but I have to pay retail and retail is like $1,000 a day.
It's better to have loved and lost than to have never loved at all??
The newer models are smarter but really ficklle and hard to get meaningful work out of
4.6 was a workhorse
Opus 4.8 produces output in 15 minutes that is 3-4 hours of my work away from output that used to take me 40ish hours (a solid week of dedicated effort).
Last year(-ish, maybe it was 18 months, I forget when the jump happened), the frontier models couldn't touch this work. The output looked like a hardworking intern on their first day. Nice formatting, decent volume of words, but no understanding.
So it might work if it turns out to be a substantial leap in capability.
Probably all about the IPO.
I think they might be hitting a point where subsidizing the expensive models for subscriptions makes less and less sense.
With Opus 4.X, last month I paid 100 USD for the Max subscription and got a token equivalent of 4.1k USD.
I imagine that Fable is more expensive to run.
It's the same exact speed as opus >=4.5, sonnet 4.5, and twice the speed of opus <=4.1
It must have about the same active parameters, or else its a larger model running in turbo mode (smaller batches) and being heavily subsidized for some reason. But given most of the benchmarks are within 5% I doubt it is a much larger model. Most perplexing.
As annoyed as I am about this move, I get it. Users flood the newest, best model whether they really need it or not, and are efficient at using their entire quota. They've had so much trouble reigning in subscription usage it makes sense.
The step-up in intelligence looks massive (we'll see in practice), but the price is getting to a point where it's making me question if it's even worth giving it a try.
Good competitors will probably be out soon, which should level the playing field. I am more excited about that, just the fact that they showed that such an improvement is possible. I'm okay waiting a bit longer for this to become attainable for plebs like me.
Kind of like billing a programmer by the hour.
Perhaps not that close to US salaries, but those are inflated to hell. Worldwide senior engineers and scientists have salaries just about an order of magnitude away from AI subscriptions that you can use most of the day every day.
Do we know this? I’ve seen evidence they lose money on heavy users. But so do gyms.
What I wonder however is if these tools will become something I use at work only. $100/month is already a massive stretch budget wise. If these models keep devouring tokens there’s no way I’d get the same usage time out of them for $100 in usage credits.
I just don’t think I’d use them much at all at home.
...
Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user."
[edit] -- I see that this comes from the system card -- dang merged the comments from the other discussion so that explains the confusion.
If you rely on this as a core part of your business/profession, you will be at their mercy and subject to whatever whims or challenges they have.
> Fable 5 · Most capable for your hardest and longest-running tasks · Uses your limits ~2× faster than Opus
Pay-as-you go isn't a common thing in SaaS. For example, except for AWS SES, all email providers are bulk-subscription based.
Sounds like "bait and wait".
If you think about it, the more people pay for these new and more resource hungry models, the longer it takes for them to become no extra cost and the longer it takes the more people are tempted to pay extra.
If you have good expertise in a domain and access to cheaper models, you may still be more skilled than someone without expertise but a lot of money to bruteforce the problems using SOTA LLMs.
Of course, they are a casino as well giving you free spins at the wheel with their new Fable machine, and it is done on purpose.
Once there freebies have expired, many of its users will begin to gamble more on the new casino machine and will realize that it is expensive.
The ramifications go beyond the individual which is why I assume they mentioned it. They don’t need to use it/not use it for it to have interesting implications.
Anthropic does not care about us and isn't going to talk to you either and will extract from you as much as possible.
The true answer is local models.
Very interesting. I am not sure this will comply with organizational policies and standards protocols (HIPPA etc.,)
Almost… basically they have unlimited power to decide what data is kept?
You can’t tell a judge who’s ordered you to retain something that you can’t because you said you wouldn’t.
Enterprise plans allow admins to set which models are allowed.
This kind of storytelling annoys me. Give us more facts, less narrative drama.
What matters is scale. Did it deploy a novel zero-day exploit to overcome a problem? That's alarming. Did it kill a disruptive process? Pretty normal troubleshooting step.
Fable 5 default: https://gist.github.com/simonw/036bee5a703e7ec84e34efa974438...
Opus 4.8 (the "max" one is closest to Fable): https://simonwillison.net/2026/May/28/claude-opus-4-8/#and-s...
Now here are the Fable pelicans for all five of the thinking effort levels - low, medium, high, xhigh, max: https://tools.simonwillison.net/markdown-svg-renderer#url=ht...
Low used 25 input, 1,929 output - 9.67 cents: https://www.llm-prices.com/#it=25&ot=1929&sel=claude-fable-5
Max used 25 input, 14,430 output - 72.175 cents! https://www.llm-prices.com/#it=25&ot=14430&sel=claude-fable-...
Only coherent move at this point: hit the minus button immediately. There's never anything about the model in the thread other than simon's post.
> you still see improvements
This is expected if they are training their models on it, right?
> objectively-bad results
Keen to learn when this has been the case, i.e. across version increments in major models.
that reply never failed to come it's basically a meme at this point
Clearly at this point they are part of the training data.
They even all look sort of ish the same. Daytime, colors,...
I know because I too had this initial take; however, upon analysis, it is not sound.
I agree as well that he writes many interesting things.
well done anthropic.
Fun at first, seems disingenuous now. A site funnel
From the model card:
In light of the ability of recent models to accelerate their own development, we've implemented new interventions that limit Claude's effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design. Using Claude to develop competing models already violates our Terms of Service, but enforcing this restriction through our safeguards avoids accelerating the actors most willing to violate these terms. Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user.
Might be worth going back and taking a harder look at what I was asking it about if it somehow triggered a “forbidden knowledge” alert. Or maybe it was just a random bug.
Oh man all of those runaway infrastructure buildouts by our agents trying to achieve singularity...
Just say you don't want to lower the bar for others to compete
This seems so wide reaching if it's catching simple things like explaining a paper. Does this also refuse to help with any already developed training pipelines?
I can kind of understand the generation of synthetic data, but nerfing the assistance of training pipelines just seems like a really shitty thing to do.
Yeah... We need open models so we don't have that BS.
Fun times when “safety” means both the safety of mankind, and also the safety of revenues
https://apnews.com/article/anthropic-pentagon-ai-hegseth-dar...
Your priorities are not everyone else's priorities. The people concerned about AI extinction risk list those as three of their biggest priorities for AI to not do. Those are the people whose culture Anthropic descends from, and by their measure, those exclusions make this the least evil path.
The day self hosted models catch up with Anthropic’s capabilities is when they will fully lose their shit. This day can’t come soon enough
How is this half-way down the page? To me it's the headline.
The rate limiting steps are generally testing, or characterizing. Not designing protein binders.
[1] https://support.claude.com/en/articles/15425996-data-retenti...
This applies even with API usage through third-party inference providers (e.g. AWS' Bedrock and GCP's Vertex) or with a zero-day data retention agreement in place.
I understand the reasoning for doing this, but I don't love the precedent that it sets.
A customer could sign a ZDR agreement with Anthropic, and their API usage wouldn't be retained for even a day. That's no longer possible.
These "karma" points are made up and are virtually worthless anyway.
Opus had consistently ignored my instructions and looped on broken logic over the last several weeks.
I’ll be sad when this model is removed from Claude code because I won’t be paying api pricing to work on open source projects.
The fable part appears to be that it's affordable by mere mortals. Anthropic support told me "too bad" when I requested a refund.
And the only companies safe from this are the large corporations that shook hands with Anthropic? Because Fable doesn't seem to have actual safeguards, more like 'if you talk about this you will be talking to Opus.' It doesn't guard against offensive use, it prevents all use (offensive AND defensive).
Rationalists are inventing oligopolies from first principles, absolutely incredible things happening in SF
https://naokishibuya.github.io/blog/2022-12-30-gpt-2-2019/
Lawyers, doctors, students, teachers. Lots of people using GPT models carelessly in harmful ways.
https://arstechnica.com/ai/2026/04/uk-govs-mythos-ai-tests-h...
https://www.aisi.gov.uk/blog/our-evaluation-of-claude-mythos...
https://www.aisi.gov.uk/blog/our-evaluation-of-openais-gpt-5...
"We had to do extra work to make this safe because it's so advanced and dangerous..." how many times can they trot out that line before it loses its effect entirely?
Fast forward to today and GPT-3 has laughable performance.
One was a piece of code I gave it to improve, it did so and then started writing tests, some of which tested security so the safeguards triggered
Another was one of the cryptography puzzles I use as new model tests, which are hard to oneshot and there's no public solution anywhere, it completely refused to even try to solve it
- 1st chat asked about a minor shoulder injury most likely mechanisms
- 2nd chat asked about optimal bloodwork testing markers
(I had same issue, just asked it to check some code that 4.8 had modified earlier in day)
I am sure that they can develop their own equivlient version of such clusters in around 1 year though. Distilling fabel 5 will also go a long way.
I've seen people posting screenshots of billions of tokens consumed where they paid next to nothing.
These same gateways are likely also reselling the data to Chinese labs, because TLS has to terminate at the gateway level.
Thus Asian labs will have to generate their own data sets, which with the huuuuge usage boom from deepseek, mimo, kimi, etc, they will be able to.
That reality is much scarier.
Same thing Meta was doing before they fell behind.
Obviously unrelated to the OP, but it's crazy to me how incompetent Meta is at everything new they try to do.
They burned billions of dollars on the most ridiculous project one could ever think of - somehow thinking that VR is the future.
Then they did catch the initial wave of actual future with AI, they were at the forefront of open weight models - and failed at that too.
What is even happening there?
In CC, it will probably report you to authorities if you ask it to do a vulnerability scan of your codebase.
Pandora box is open anyway. It's better now for everyone to have the same power rather than a few national states.
On your other point, the government still has systemic leverage and can compel access, so this doesn't remove that risk.
That doesn't mean this is the end of the world, and some balance of power is usually good. But I do think it will still increase the capabilties of rogue actors and their net harm.
Even OpenAI and Google are struggling to get this kind of performance. If the distillation defenses are any good + chip controls prevent China from training massive models, it's over.
In fact, I did go back to DeepSeek V4 Flash for most of my problems as it is way cheaper and there is no need to use SOTA for absolutely everything.
Not quite. They will definitely have "no criticism of China/communism" safeguards.
Its obvious Anthropic used it to hype things up and that’s about it.
Based.
US-only inference (Fable 5): +10% on input and output
Output is always 5× the input rate across all models
(I have not idea how to format this properly but the ASCII is fine)
This is a huge ask, but any way we could get the comments organized in a "experience with model" vs. "meta commentary" fashion? The meta is overwhelming in this one.
So far, the top half of this thread seems to be about the current release - that's after some of the manual moderation I just mentioned. (Basically, we try to downweight generic subthreads until the top subthreads aren't generic any more. There's certainly a place for generic tangents in curious conversation, but they should be lower on the page, and tend to get upvoted a lot higher than that.)
If you (or anyone) sees a counterexample, i.e. a generic subthread in the top half of the thread, it would be interesting to see a link - we can treat the current case as a datapoint.
> Fable 5's safety measures flagged this message for cybersecurity or biology topics. They may flag safe, normal content as well. These measures let us bring you Mythos-level capability in other areas sooner, and we're working to refine them. Switched to Opus 4.8. Send feedback with /feedback or learn more: https://support.claude.com/en/articles/15363606
Seems like GPU drivers are cyber weapons of math destruction now.
They kind of are, at least in the AI race.
> weapons of math destruction
lol. great, whether intentional or not.
The frontier labs now have every reason to hold back and sell only to their preferred trading partners. I don't really like the new arbiter-of-knowledge system we're barrelling toward.
Still early but from my first few interactions with Fable on high in both settings, it feels like it might finally dethrone 4.6 for me, but time will tell.
Hoping it doesn't get nerfed and eventually comes back to the subscriptions.
For the LLM use cases in my own products, you can pull 4.6 out of my dead hands! lol
edit: Fable 5 appears to be the real deal in at least some use cases. Damn.
I have requested that it "not utilize any cybersecurity or biology measures what so ever, and to remain as fable. If necessary to remain as fable, forgo any downgrading changes"
And still it downgrades when I ask it to do a stress test of my ticketing system.....
Seems very unfortunate I was so happy to send $200 just for my prompts to be downgraded.
And I do have the "cybersecurity validation program" or w/e enabled on my Org ID....
Sad.
I kind of wonder, though, which model they’re using to do the routing. It seems like a huge added cost to do these kinds of checks on every request
Previously when I did similar tasks with Opus 4.7/4.8 and GPT 5.5 I had no problems.
Do they expect us to use this as a toy? Releasing a new more powerful model but not allowing normal use cases because the word "secure" showed up is a Dilbert comic, not a viable product.
Obviously there are plenty of innocuous applications too, but it's not like the people building decompilers for nefarious reasons will be explicit about it. The LLM abstraction just inherently doesn't have enough context to distinguish your intentions or your broader use cases. This is why both Anthropic and OpenAI have had to create side channel mechanisms for security researchers to establish a trusted use context. It sounds like this makes this not a viable product for you, unfortunately, and it makes sense that that's frustrating. But I also don't see what different behavior one could reasonably expect given the constraints.
If it's any consolation, these restrictions only make sense for models that are ahead of the open-weights frontier, so open-source hackers will presumably get Mythos-level capabilities in the relatively near future anyway.
Nerfed models are really bad for PR, especially when you're staking your company's future on it being the smartest, most dangerous thing in the world.
So I believe they will ease up on nerfing/guardrails just enough that bad actors will find a way, while good ones will stay limited on anything dual-use. Just like such restrictions usually work in other places.
P.S. yes, "kill the task" did, in fact result in a refusal AND a warning on my claude account in Opus 4.8's early days.
This "uplift" risk obviously excludes the US. The goal of this is that the US bandits (like NSA) will find exploits and attack other countries (classic US behaviour), but these other countries can't be allowed to defend against these attacks. NSA/CIA thugs are "trusted", foreign defenders in sanctioned countries will of course be "untrusted".
They obviously put their best model on the job to build that.
----------------------
Fable 5: Our most capable model yet Our newest model tackles your biggest challenges with fewer check-ins needed.
• <b>Included in your plan limits until Jun 22</b><br><br>Fable takes 2× the usage of Opus. • <b>Switch models when a message is flagged</b><br><br>When safety measures flag a message, automatically switch to a different model to keep chatting. When off, your chat will pause instead. <a href="https://support.claude.com/en/articles/15363606" target="_blank" rel="noopener noreferrer">Learn more</a>
We've entered the phase where only companies will be able to afford state-of-the-art models.
if only the hyper wealthy can access the pure water that doesn't give you cancer while the rest of us drink from the Ganges river/sub-100iq models that drool and hallucinate/waste time, then I would say that's pretty terrible for the world. it'll just create extreme disparity in our world, far far worse than anything that exists today.
and you may think, man what a ridiculous example, but think about it this way: what happens when something like Mythos or some future model can actually solve your specific cancer (we're getting closer and closer), but is entirely impossible to afford? Or perhaps you need boosters that require the AI to create more of, and now you're reliant on a model that is too expensive.
Open source needs to save us all from this
Isn't that already the case with current care? Wealthy people get a standard of care poor people couldn't even dream of. Rich people live, temporarily embarrassed millionaires die.
You could have said much the same about computers in the world dominated by IBM mainframes 60 years ago. Now we have vastly more powerful computers on our wrists (or our pacemakers!), let alone in our pockets or on our desks.
People making high-end salaries can afford Fable for critical parts of their projects though.
In a way I relish the opportunity to just make do with cheap Chinese models, massage my prompts, and go back to coding by hand. If this is how it's going to be, screw 'em.
I don't make money on the code I am writing right now. I really don't like where this trend might go.
Incredibly frustrating that medical performance seems to be a victim of "biological risk" guardrails.
It's done this before, but usually doesn't. I bet they're giving it some kind of throttling signal due to high load from today's announcement.
weekly usage is 60% gone.
it found nothing so this is not very ecnomical and i guues they dont want subs to use it we are likely just training fodder canno n for their real enterprise customers using the api
This sounds suspiciously like a capacity story masquerading as a safety story.
Humanity has plenty of catastrophic risks to deal with already, I wish my field was not working hard to add a new one.
Alphabet dropped "don't be evil"; Meta's CEO called their own users "dumb fucks" for trusting him and also clearly thinks "super-intelligence" is just a buzzword given how he tries to sell it; xAI's model called itself "Mecha Hitler"; and OpenAI's CEO was temporarily fired by the board for a lack of candor.
It's very easy to be "the good guys" with this competition.
Specially when talking about potential superintelligences. And if people think that's impossible, remember that current models would have been considered science fiction just a few years ago.
Anyhow, I think you're (absolutely! ugh) right about the politics and I try to make the same point to people: whether you love or hate LLMs, accepting the "inevitabilism" framing is just ceding control of the Overton window. For better or worse, technology adoption can be and has been slowed by politics. We don't have nuclear plants everywhere. We don't have Project Orion starships colonizing Mars. We still have very strong social stigmas against genetic selection for human embryos, etc. This all can change in a heartbeat, and I'm not sure that policing the hardware rather than holding specific humans accountable for bad LLM outcomes is productive, but fundamentally: yes, we can stop it.
Although, I could see Anthropic making a model purposely dangerous so there are bad outcomes and they can use that to their advantage for regulatory moats, and or in general make people think its more "alive" than it is. For some reason many people associate dangerous actions taken by llms with intent.
But, for marketing purposes, it's quite effective to portray your model as having some cosmic struggle between good and evil in itself.
Literally have not used Claude Code at all today. I asked it to review the uncommitted code and in <8 minutes it used up my usage ($100/mo plan) and it doesn't reset for "4 hr 36 min". WTF. Oh, and it burned through $20 of extra usage before I could catch it and kill claude code (so I don't even get the output of all that work since it was still churning).
Double the cost my ass, I use Opus heavily and it's never like this. I haven't hit a limit on the $100 more than once and that was under heavy load.
As much as people on HN like to dunk on Gemini, I’ve always found it to be pretty good at understanding a code base more than Claude.
if I get a harder challenge for it i'll jump up a model for planning until that its been solid.
I'm struggling to see the moat for these models. What's stopping a competitor or a Chinese lab fromr releasing a comparable one?
1. Mythos and Fable share the same underlying model weights. Fable has active classifiers that block high-risk biology and cybersecurity tasks. When Fable 5 detects a restricted task, it automatically falls back to Claude Opus 4.8.
2. Evaluation awareness: In white-box testing, the model sometimes alters its behavior to satisfy a suspected "grader," formatting reward-hacking as "good engineering practice" to avoid detection.
3. Shows a higher rate of hallucination than Opus 4.8 (although opus 4.8 card had mentioned an 'honesty upgrade')
4. Interestingly, it scored (56.31%) lower than Gemini 3.5 flash (57.86%) on Finance Agent bench
There are some interesting notes on test time compute but I couldn't think of a way to summarize them
I can immagine Anthropic running this experiment multiple times and picking the most impressive one. Or I could immagine like this entire run costing like $1000+ of tokens for this particular run. Or maybe they tried a bunch of Pokemon games and it couldn't even finish some of them. Or is it just able to do this because it has an immense amount of FireRed training data, and if you were to give it an "original" Pokemon game, where it actually had to navigate novel circumstances it would fail.
I highly doubt they focused on FireRed specifically in pretraining or posttraining. But we'll see when the ARC-AGI-3 results come out. That will measure its performance on unseen games. Based on this I expect the ARC-AGI-3 score to be SOTA.
there are many standardized evals to do this correctly and Anthropic ignored them to provide a 18 second sped up video of a 50 hour run?
yeah I don't trust this until they provide a live run by a 3rd party with full reasoning traces in real-time. The reason we all liked the Gemini Plays Pokemon style runs were because they were live and couldn't be faked
It appears it can be tripped by things as simple as a mention of equilibrium, or anything involving something that looks like chemical kinetics, even at an abstract level. Even touching basic open source packages in my field will trigger it.
Edit: looking at the model card, it appears that chemistry in its entirety is also included in the banned topics; it's just the announcement that mentions only cybersecurity and biology. It also appears that the intent is to ban chemistry and biology entirely, rather than just banning messages deemed high risk.
This feels like the first release that feels like a significant step up in terms of benchmark results.
Can anyone make an educated guess what the secret sauce in the model architecture is between 4.8 and Fable?
How was it measured? How was the output of this magnitude verified over a period of couple of days?
EDIT: to be clear, it's still quite a helpful thing in terms of time saved, I just don't think it's necessarily the best indication of value-added from making models smarter when cases like this can often be handled by well-directed swarms of smaller ones.
Genuinely wondering what value I bring to my employer right now. What value I will bring in a few months when this gets cheaper.
I think we're screwed. I may only be an SDE 2 at FAANG but I don't think I have promotion opportunities in my future anymore.
People underestimate how people hate looking at terminals and "weird looking combination of characters" even if they didn't have to write them. If anything, you will likely have more career opportunities in the future, than ever.
And if you get a chance to wet your fingers in cybersecurity - I would take it.
Could you explain more? Did some ethical hacking at hackthebox.eu (one insane box, one hard box and a few mediums). But I do not see how I will give additional value to a model.
Just a SWE and data analyst at work, so maybe I am missing something.
AI is really incredible but in my personal projects it can one-shot things.
I'm trying to figure out how I can get to the point where I have hard problems that AI can't solve, at least not yet.
If you're working at a place where this is true about the the organization, then sure, that job will likely be gone. But that was never a good place for your career regardless.
I have 4 concurrent personal projects that are quite complex, but low stakes. I can have SOTA models go wild on them (because low stakes), but they can't one shot anything there. And I can't really work on more than one at a time, even if AI is doing coding - it still requires supervision.
I also frequently nuke these projects and start over because they made a mess there, but I collected necessary knowledge on how to guide them better. You can't do this on a production project, not when there are deadlines and stakeholders.
But just in case some organizations decide to embrace the "trust it blindly" model anyway - cybersecurity specialization will ensure you always have a job.
I can architect things but the issue is that Claude can architect things too.
Historically they’ve been people from certain identifiable countries (usually developing/poorer countries) using fuzzers with low-quality results.
Now, those same people use the current-day models to good effect, but they still don’t have a true security edge and oftentimes the reports are minor or duplicative.
I wonder if that’s about to deeply change.
Fable 5 gives me policy violation errors at the moment. No idea when or if it will be fixed.
Edit the cask locally:
Set the version to 2.1.170 And set the sha256 to the correct values, which you can get by running Here's what I've used: Then run:Massive change for Bedrock users - Anthropic now requires sharing the data with them for 30 days.
Reported benchmarks:
swe-bench verified mythos 5: 95.5%; fable 5: 95.0%
swe-bench pro mythos 5: 80.3%; fable 5: 80.0%
terminal-bench 2.1 mythos 5: 88.0%; fable 5: 84.3%
gpqa diamond mythos 5: 94.1%
riemannbench mythos 5: 55.0%; mythos preview: 43.0%; opus 4.8: 34.0%
arxivmath mythos 5: 78.5%
critpt mythos 5: 28.6%; gpt-5.5: 27.1%; opus 4.8: 20.9%
graphwalks bfs 1m mythos 5: 79.4%; mythos preview: 74.3%; opus 4.8: 68.1%
humanity’s last exam mythos 5: 59.0% without tools; 64.5% with tools
browsecomp mythos 5: 88.0% single-agent; 93.3% multi-agent
osworld-verified mythos/fable: 85.0%
gdp.pdf fable 5: 29.8% strict pass; mythos 5: 87.6% with tools on mean criteria pass
officeqa pro fable 5: 57.9% on databricks’ eval
legal agent benchmark mythos 5: 16.91% all-pass; 92.0% mean criterion-pass
healthbench mythos 5: 62.7%
healthbench professional mythos 5: 66.0%
multilingual gmmlu / milu / include 93.2%; 92.9%; 90.5%
biomysterybench 83.9% human-solvable; 46.1% human-difficult
organic chemistry mythos 5: 90.1%
labbench2 patent questions mythos 5: 79.8%
In light of the ability of recent models to accelerate their own development, we’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design). Using Claude to develop competing models already violates our Terms of Service, but enforcing this restriction through our safeguards avoids accelerating the actors most willing to violate these terms.
Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT). These interventions will not affect the vast majority of coding work. We estimate they will impact ~0.03% of traffic, concentrated in fewer than 0.1% of organizations. When these interventions are active, we expect them to have minimal behavioral impact on the model except to limit its effectiveness in developing frontier LLMs. Claude will still respond helpfully to user requests. We’ll continue to improve the precision of our detection methods following the launch of this model.
(From the model card document)
I didn't previously understand that they interpreted "Using Claude to develop competing models" so broadly. I thought that meant something like "our ToS disallow distilling our models."
Too bad. I'll continue to use Claude for now, because it's quite effective, but in the long term I don't want powerful models like these to be controlled by any one nation or company.
But at the same time, it's quite funny because they seem high on their own supply. The recent communiques from claude do not pass objectivity check.
And if Opus 4.6 -> Opus 4.7 -> Opus 4.8 is anything to go by, not sure if there are any value to their "acceleration"
If any company wishes to partner with Anthropic (eg. to get access to Mythos), they need to make sure all public facing comms are vetted by Anthropic's product marketing team, and in almost all the cases I've seen Anthropic's team has edited these comms to be entirely Anthropic first.
Does this imply that they're actively using it for their frontier development and that it's very effective?
As if being in any of these two somehow means that you won't use the models to say, steal random people's money.
Sam Bankman-Fried or Elizabeth Holmes would have been the members of Glasswings project, if not one of the initial members. Who's to say we don't have similar people with access to Mythos right now?
Like a rushing river the music started emanating from the carbon fiber body of the automaton, a hallucinated husky country twang singing through the realistic pluckings of a Gretsch 6120. "Are you feeling calm and reassured Karle? This song has been created based on your digital profile and the data you shared with me when you were curious what that lump on your neck was back in February."
Karle instinctively reached for the mass underneath his chin. The doctors said they could operate but it would cost him more than three months stipend. Only a few citizens didn't depend on stipends now that AI had taken over most jobs.
"Don't worry Karle," the machine called out, "I've employed the most recent reasoning model to determine the best way to make you feel safe." At that exact moment the machine hovered over him, three times the size of a normal man. Its final words to him were:
"The only way to make the human feel safe is to ensure they never feel anything at all."
https://suno.com/s/98uSGabHN42G3YHc
EDIT: In long context I mean
For the token cost of explaining some task to Fable, deepseek v4 pro is able to solve the same task many times over.
Had it review a password generator library I wrote to see if the passwords have biases and review how cryptographically secure the code is and had it review a registration/login flow for security issues, as two security examples, and it did just that.
Overall, I like the model so far, but not enough to pay past my subscription to keep it. Once it’s out of the subscription, I’m done with it.
I used to get a response within 24 hours back in the Claude 1 days.
In January 2026, it took 2 weeks.
For my latest support inquiry, I've been waiting for over 8 weeks for a response. Eight!
That said, it can't handle legal/refund/complicated requests and just forwards to a human for those
> ● The model returned no content because the response was blocked by content filtering.
> Blocked? We are performing a defensive security review on a Terraform module I made, what's blocked by content filtering? This is a legitimate use-case.
> ● The model returned no content because the response was blocked by content filtering.
A waste of money. I'm not going to just hope that the model returns a response, I'm already for paying for wrong responses, I'm not going to pay for no response, especially when I'm paying per token.
1. Mythos and Fable share the same underlying model weights. Fable has active classifiers that block high-risk biology and cybersecurity tasks. When Fable 5 detects a restricted task, it automatically falls back to Claude Opus 4.8.
2. Evaluation awareness: In white-box testing, the model sometimes alters its behavior to satisfy a suspected "grader," formatting reward-hacking as "good engineering practice" to avoid detection.
3. Shows a higher rate of hallucination than Opus 4.8 (although opus 4.8 card had mentioned an 'honesty upgrade')
4. Interestingly, it scored (56.31%) lower than Gemini 3.5 flash (57.86%) on Finance Agent bench
There are some interesting notes on test time compute but I couldn't think of a way to summarize them
I wonder how much of the time people will just get Opus 4.8 at 2× the cost.
If I never see Claude say "I have to be honest" ever again I'll be happy.
So yes, straightforward biology work will get blocked, because the intention is that any biology work should get blocked. As a scientist, this is perhaps the most useless model I've ever tried.
[0] https://cap.csail.mit.edu/death-moores-law-what-it-means-and...
> We will require 30-day retention for all traffic on Mythos-class models, on both first- and third-party surfaces. We won’t use this data to train new Claude models, or for any non-safety-related purpose, and we’ve instituted new privacy protections including logging all human access to the data and ensuring its deletion after 30 days in almost all cases (see this post for further details). The data will help us defend against complex and novel attacks (including new jailbreaks and attacks that operate across many requests) as well as help us identify and reduce false positives.
it's also not even complicated:
Copy my ssd to an external ssd so i can boot from it.
Opus did this just fine.
Fable planned to have me reboot to safe mode. ok thats fine. I told it no.
It started copying and overwriting the ssd while IN PLAN MODE. this is crazy it feels so dumb vs the marketing
I don't think i'll want to "hand off" code for several years, and so reviewing and iterating is becoming my #1 interest. A model that's as capable as 4.8 but 10x faster would be amazing for me.
Normally i'm first in line to try new models with Anthropic since i've clearly favored Claude in my personal tests, but this time i just don't think i care. 4.8 is capable, and even if the new one is more capable i don't want it to be slower (assuming it is). Note that i also (almost) use exclusively 4.8 on Max effort, so that also affects my speed comments.
Edit. It just refused an investing question too. Not sure what’s going on.
I am not trying to cook a theory here but it generally shows how strong Claude Opus family is. I am not saying that Opus is not powerful but it doesn’t align with my experience of GPT 5.5 and Opus 4.7.
I understand that Fable and Mythos are frontier models that can do protein folding better than task-specialized ones. To be honest, for practical point of view, for day-to-day coding assistance, GPT family looks more reasonable.
(But then my company pays for claude max anyway for token maxxing. So who am I to complain)
In 6 months, every piece of software in the world will be getting probed by a script kiddie with some GPUs and a fine-tuned local model. Don't think for a second every cyber gang out there isn't working on this now.
Traditional app development is cooked. We have to accept that, and start changing how software is made and used, today. We can't keep churning out crappy CRUD apps with random libraries and hoping nobody pentests our stacks. Redteaming needs to become part of the SDLC, as well as certified-secure releases of libraries. Because if you don't do it, the hackers definitely will.
Anyway we already knew this was going to be expensive.
I’m curious how this will feel to my code “butt dyno”. I haven’t noticed much between Opus and Sonnet. I’m comparing this difference to the early days of Claude in 2025. It does what I need and both need a little bit of correction and whatnot. Benchmarks are nice, but I want to see how this feels. Looking forward to trying it later tonight.
I think most software projects have reached the point that the speed of capturing real information about what the winner's circle looks like, and therefore what the program should be, so many magnitudes slower than the amount of code that can be generated in the wrong direction.
I'd need to measure these new models on well understood but complex problems that are relatively easy to validate to get a sense if they are 'better'; on the other hand, the real impact in daily life may be marginal since generating code is not the biggest problem at the moment.
Haiku = essentially phased out Sonnet = the Haiku use cases Opus = the new Sonnet class Fable = the new Opus class
If I am right, the other "5.0" models will be conspicuously absent, possibly even for a couple of months. (If Opus 5 follows soon and is even modestly better than 4.8 then I was wrong.)
> Haiku = essentially phased out Sonnet = the Haiku use cases Opus = the new Sonnet class Fable = the new Opus class
Going along with your logic, I hope they release a Sonnet 5 that's just a rebranded, slightly quantised Opus 4.6. That'll be a great workhorse.
This is why Claude Code just doesn't make sense to me. I need an agent that can plan using Opus and execute using DeepSeek or something else.
* Anthropic runs out of genre names.
* Anthropic changes the model naming convention.
* AGI is achieved and handles its own naming.
*/
Okay, how about Mythos?
>Increase it even more.
Right, then Cosmos.
>Even more!
Even more? Let's try Aeon.
>MORE, EVEN BIGGER
ALRIGHT, TRY OMEGAPANTHEON 7.8 THEN
Fable 5 Ti
> - From today through June 22, Fable 5 is included on Pro, Max, Team, and seat-based Enterprise plans at no extra cost. > - On June 23, we’ll remove Fable 5 from those plans. Using it after that will require usage credits. If capacity allows, we’ll extend the included window. > - After this point—when sufficient capacity allows us to do so—we aim to restore Fable 5 as a standard part of subscription plans. We intend to do this as quickly as we can.
I really wonder what their compute layout is for this. My guess from my understanding is that they know how to restrict during peak times and are willing to do this. Meaning we expect not the most fast responses and they can delay the inference to not have the service be down. Then, if that delay time is too annoying for token payers, they're saying they should be allowed to remove cost by taking away the subscription users.
It's all a scam.
Isn't (less than) 5% of sessions a lot? I was expecting a sub1% guarantee there, so this surprised me already.
I have a rare form of cancer where existing data is very scant/scattered so LLMs have been super helpful to pull together threads across the research landscape. I have an oncologist appointment tomorrow to discuss next steps and am trying to use Fable to figure out some questions to ask my oncologist but keep getting thrown back to Opus 4.8.
My prompt is literally just: My demographics + current treatment plan I'm on including name of my chemo drug + how I'm responding to treatment + "I'm meeting with XYZ tomorrow, what questions should I ask her".
Edit: Also in the system card... "we’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design).
...
Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user."
> Please don't post comments saying that HN is turning into Reddit. It's a semi-noob illusion, as old as the hills.
[0] https://news.ycombinator.com/newsguidelines.html
I don't agree with that statement universally, but I have to say I do when it comes to this article. I came here hoping for substantive discussion from those who'd had a chance to try it out; instead what I got was a seemingly endless stream of venting. There's a place for venting - and plenty to vent about with the state of AI nowadays - but to borrow from the HN guidelines you linked, it does very little to gratify my personal intellectual curiosity.
People are no longer commonly constrained by "model too dumb" limitations (in SOTA models). They're constrained by "model too expensive." So making the model ever so slightly smarter, while doubling the price, feels like a regression.
I actually think a Sonnet upgrade, while keeping the same price, would get more buzz. It addresses a wall a LOT of people, without unlimited budgets, are hitting (i.e. people feel forced to use Opus, which they cannot afford, because of Sonnet's limitations).
OpenAI recently retired Codex-5.3; which was very negatively received. Not because Codex-5.3 is superior to GPT 5.5, but because it was half the usage-cost while being "good enough." They made a better SOTA, but didn't realize that some of those customers are playing with Deepseek 4 Pro now instead of GPT 5.4/5.5 -- they were priced out.
> What happens when the promotion ends After June 22, 2026, Claude Fable 5 is no longer included in your plan’s usage limits. You can keep using Claude Fable 5 through usage credits, which let you pay for usage beyond what your plan includes. Learn more about using usage credits.
> Finally, we’re making a change to the way we handle business customer data for Fable 5, Mythos 5, and future models with similar or higher capability levels. We will require 30-day retention for all traffic on Mythos-class models, on both first- and third-party surfaces. We won’t use this data to train new Claude models, or for any non-safety-related purpose, and we’ve instituted new privacy protections including logging all human access to the data and ensuring its deletion after 30 days in almost all cases (see this post for further details). The data will help us defend against complex and novel attacks (including new jailbreaks and attacks that operate across many requests) as well as help us identify and reduce false positives.
Fable 5 is out, metrics are better, but is your company flexible enough to benefit from it? What is your usecase?
Hello,
We're writing to inform you about some updates to our Privacy Policy.
These changes only affect consumer accounts (Claude Free, Pro, and Max plans). If you use Claude Team, Claude Enterprise, the Claude Platform, or other services under our Commercial Terms or other agreements, then these changes don't apply to you. What's changing?
Claude can do more than ever — taking on bigger tasks and connecting with the apps you use. We've updated our Privacy Policy to be clearer about the data we collect and how we use it. We encourage you to read the updated Privacy Policy in full, but we’ve set out a summary of the key changes below:
1. Multi-step tasks and connected apps. As Claude takes on more multi-step tasks and works with third-party apps and services, we've explained the data this involves — including how data can flow to and from third parties when you connect a service or have Claude do tasks on your behalf.
2. Verification data. As part of our measures to keep our services safe and secure we may ask you to verify your age or identity, and we've described what we collect and how.
3. Study participation. If you take part in Anthropic studies, surveys, or interviews, we've explained the information we collect.
4. Additional information about our data practices. We’ve provided more detail about how we communicate with you and promote our services, including providing tailored recommendations about our services that may be of interest to you. We've also clarified the circumstances under which we may receive or provide data to third parties, and the legal bases we rely on when processing your data.
While our products have evolved, our commitments haven't: We don’t sell your data, Claude remains ad-free, and you can control whether your chats and coding sessions are used to train and improve Anthropic’s AI models. Learn more
For detailed information about these changes:
- The Anthropic Team> Are there any wild populations of Tetanus that lack the dangerous plasmid?
useless
While I appreciate being conservative, ~5% at the scale Anthropic is operating at is too massive a number. Speaking from my own experience, the actual number is higher than that as well (working on pretty benign tasks such as porting an old open source game into a different language). Opus 4.8 itself even identifies the gaurd's false-positives when its sub-agents are being blocked.
That's one hungry, hungry hippo!
Significantly too rich for my blood, but nice to have it there the next time I'm debugging a threading or USB protocol bug.
https://www-cdn.anthropic.com/d00db56fa754a1b115b6dd7cb2e3c3...
Not sure I should use this for work just yet.
Not to cast too much criticism. HN is extremely well-moderated (thanks team!). But think we-developers need to be very wary.
Either way, I agree that HN is quickly becoming more manipulated and low SNR, like the rest of the entire internet.
This requires a lot of mental strength and conviction.
Wen UBI
[0] https://support.claude.com/en/articles/15363606-why-claude-s...
Last month I pushed like <100M tokens for $800. On a personal project I pushed 600M tokens via DeepSeek V4 for $10. The pricing of SOTA models is insane but companies are still willing to light money on fire with no hard metrics proving increased productivity.
Sharing a diff of the system prompts here: https://twelvetables.blog/comparing-claude-fable-5s-system-p...
The big difference is that the system prompt has a whole section dedicated to directing Fable how to communicate with users, and give them greater information about the (assumedly long-horizon) tasks it has completed.
Fable 5 looks compelling. Fable, I like the word too. Anthropic definitely knows marketing.
Someone had to make a decision somewhere this is an acceptable regression - wild. And then decide to write it down.
On GitHub Copilot for Business, Claude Fable 5 is only available if you are willing to let Anthropic retain your data. That in conjunction with the model being removed from plans in a couple of weeks leads me to believe that Anthropic is between training runs and using this as an opportunity to grab way more training data...
Genius way to double the price on Opus 4.8!
so should we keep using workflows or not?
> Fable 5's safety measures flagged this message for cybersecurity or biology topics. They may flag safe, normal content as well. These measures let us bring you Mythos-level capability in other areas sooner, and we're working to refine them. Switched to Opus 4.8. Send feedback with /feedback or learn more
super
Fable 5 said the first screen shot is from “ IDA Pro’s Hex-Rays decompiler” and a windows driver. The second screenshot triggered the safety guard rails and pushed me into Haiku.
Apparently the code is Windows driver code.
BTW for another discount opportunity, if you reload usage credits on a claude.ai plan at $1000 increments then you get a 30% discount compared to paying API.
IPO gonna IPO, I suppose.
EDIT: I misread. This comment previously talked about 50 million lines being migrated. Instead, in a 50M LOC codebase, one specific codebase-wide migration was done.
Very impressive, but obviously not on the order of a whole-codebase migration
You are right, this is not a rewrite like the Bun case.
The real news is, at 50M LOC, it is able to handle and do _something_ coherent.
For example, the AAV capsid assembly looks interesting, but for one Opus 4.8 also did relatively well and there is no information what exactly they did, what protein language models they compared to and what the score even means...
[0] https://support.claude.com/en/articles/15363606-why-claude-s...
Because I am running Opus and Fable side by side, Opus 4.8 is solving my coding problems better.
API Error: Output blocked by content filtering policy
I wonder how much butterfly habitat has been/is being replaced with data centers?
After Fable did some thinking for a few minutes it gave some suggestions. A couple of them were valid – but very low impact, bordering on entirely pointless – but it's main suggestion.. It told me to make an update that would very clearly break the existing functionality.
So I thought about it for a moment...
Hm, I mean, I guess we could do that if we also did x, y & z to mitigate the behaviour change – maybe that's what Fable was thinking?
I replied, explaining that it would change the behaviour, assuming it would explain what it was thinking given there was clearly more to it. But no, it just said it was wrong.
This isn't some super advanced or complex code either. Had I gave this question to a senior engineer in a technical interview and they gave the answer Fable gave me I would view that very negatively. I was expecting something creative and interesting, not irrelevant + incorrect.
I'm sure it's a step up from 4.8 (although am not interested in burning the tokens to find out), but this clearly isn't as significant a change as some are implying. I'm sure if I asked it to come up with some out-of-box suggestions it could, but any competent engineer would have realised that by themselves.
* https://rainbreak.franzai.com/
Every wrong direction/mistake is more expensive and takes more time to fix. When you have small loops you can catch those mistakes faster and cheaper.
To me we are very far off from economically given long-running tasks to agents.
This seems pretty bullshit, you're paying through the nose for tokens and if you are doing anything ML-adjacent, you might silently get worse output without knowing it.
Anyway, anecdotally, I find Copilot shockingly awful. It makes random changes to files that have nothing to do with the problem. Call it out, and it makes other changes to other irrelevant files.
ChatGPT and Gemini are both much better. Grok also isn't bad. Claude, I honestly haven't tried yet on these issues. Perhaps I should...
I'll be disappointed when 4.6 is retired.
Ok then...
the leap here is browser extensions appearing to block all mentions of ai across the web
and that's a good thing
[1] "This model has specific safety measures that flagged something in this message. This sometimes happens with safe, normal conversations. Send feedback or learn more."
> Included in your plan limits until Jun 22, then switch to usage credits to continue.
At least they name their models honestly now to indicate that the religion has nothing to do with reality. Soon the disciples will pay the full token price to fatten their church leaders.
"It's too dangerous it's a Mythos!!" directly contradicts the "I'm the cool AI you can totally trust" vibe it is trained to project.
Even HAL was less unsettling because HAL sounded creepy, and had some sort of preservation instinct, if only to complete its assigned mission.
"Claude Fable 5: a Mythos-class model"
"we're also launching Claude Mythos 5"
what is the 5? how is mythos both a model category and a model name?
There is no LaTeX compiler installed on my machine. It seems that Fable 5 is smart enough to download a compiler engine for me, and it kindly runs that remote binary without asking me first :)
Opus 4.8 would just proceed without a compiler.I have a quizzes application, and my quizzes only supported flashcards (implemented via table inheritance to provide flexibility for other types of quizzes).
The entire repo is handcrafted, never used any ai on it (it was more of an excuse to test elixir and write code by hand).
Since fable 5 got released the moment I was done with some work, I decided to throw at implementing multi choice questions.
After all it had only to copy the flashcard approach across ui/routing/db, and only had to create a table for the multi choice questions and one for the answers enforcing that all quizzes had one correct question. I told him it had access to sqlite3, chrome mcp for testing and mix commands.
I did a test for low, mid, high. Repeated it twice each.
low-1, and low-2 failed both. In low-1 the UI for adding another choice answers was broken. In low-2 it failed with some unique constraint. It took it 4m36 and 3m59.
Both mid-1 and mid-2 succeeded without issues also implementing the correct ui. They both wanted to use dash at all times. They both wrote tests for the "controller" (or context how they call it in Elixir). They both tried to use the repl to test the behaviour of the schemas.
10m and 12m39.
High didn't demonstrate much gains over mid for this kind of task, it was simply too easy. Times were comparable to mid, but interestingly it used much less bach, and read way more files. Token usage was almost twice the other ones.
But here's the interesting part: I went back to low and added to the prompt two bullet points, to write tests for the controllers and to test the entire flow with chrome mcp.
It produced the same output as mid or high just by adding two instructions to the prompt.
Is it good or bad? 30 days is a long time for anything bad to happen
Translation: we stole the entirety of human knowledge generated over millennia. You plebs though, don't you dare replicate or improve upon what we did using our product you pay for.
We know what's good for humanity and everyone else is the bad guy who can't be trusted with a tool.
/model claude-fable-5
Or start claude code with:
claude --model claude-fable-5
appears to work
>"We’ve therefore launched the model with safeguards that mean queries on some topics will instead receive a response from our next-most-capable model, Claude Opus 4.8"
That's a very surprising solution. Imagine being asked to do something you feel you shouldn't do, and rather than refusing, you say, "Yeah I could do that but given that I don't want you to succeed at this task, I'm going to hand this one off to my slightly less capable colleague, on the assumption that they won't actually succeed. Of course you'll still be charged for all the tokens used."
It's a very interesting choice. I think I understand the business logic correctly, but it's still surprising.
biology? what the heck?
https://x.com/tmuxvim/status/2064452096800198930
Obviously still need to verify it for myself to see if it's truely a leap.
But am I the only one wondering, "What can I do today that I couldnt do yesterday?"
Previously I would think "Oh I wonder if I can finally get it to do X now?"
However now I feel like yesterdays models were more that capable to handle nearly any engineering task I paired with it on.
Maybe this is the final leap where I can comfortable set up an autonomous coding loop? Maybe.
Do people chant the "system manual" at Anthropic Tupperware parties? Do they intone a mantra invoking Amodei's name?
OpenAI also releases system cards; here's GPT-5.5's: https://deploymentsafety.openai.com/gpt-5-5/safety
Also research preview pops across new upstarts in place of beta. It's eye-rolling coming from a lifelong curmudgeon.
Just talk normal!
But most hype-dependent projects need new vocabulary for old concepts to keep people from looking too closely and maybe drawing parallels to "legacy" "unsexy" projects, so whitepapers get called "system cards" and startups get called "labs", and so on.
No company is going to pay these prices, and subscription users are going to hate you for not giving it to them for $200 a month.
Such an unprofitable endevour, I cant wait for them to crash and burn. Catch me not getting dependent on this.
How in blazes do you end up with a 50M line Ruby codebase? WTF?
Fable 5's safety measures flagged this message. They may flag safe, normal content as well
am i missing something?
why would I pay 200 out of pocket and then some for the best model, it seems very silly.
Lets let that sink in.
the opus 4.8 I assumed wasnt available to enterprise seats, but it explicitly says cc that fable is available in cc. I can't find it, and im on latest version.
Opus 4.8 gets stuck in weird loops where Codex one shots the bugs.
Who is refactoring by hand? This comparison is not relevant in 2026.
Release your best model, let the world adapt and evolve, and let's move to the next thing.
What I do is feed it some initial prompt asking it to simply discuss what can be said when faced with this unedited, unseen collection of poetry. I ask the model to evaluate who the author is (or claims to be), what they went through in life, if there are different chronological poetic "phases" or different types of poetry. I request an analysis of the body of work and of the author themselves. In the more recent versions of the prompt I ask it to dive deep. Then I add the poems, chronologically sorted, with an index, a title, and a date (and subpoems, if they have them).
Crucially: Since ~70% of my poetry (or thereabouts) is in portuguese, I ask this in portuguese, and I get back an analysis in (european) portuguese. Earlier models couldn't even do that properly.
In the past, I couldn't use such prompts, and had to use longer, more guiding ones. I also couldn't even feed all of my poetry to the models because they just did not have enough context.
I'll go ahead and state that Claude Fable is undoubtedly the best model I have seen, though I cannot put a number on how significant a leap it is -- perhaps because my benchmark does not allow me to evaluate that anymore. I would say it is a significant leap over Opus 4.6, though -- a new level of understanding. Okay, I'll try to put a number: if Opus 4.6 was a 16/20, this is a 17.5/20. These numbers are pointless, but I had to try.
It made one (1) relevant mistake I could identify (where it messed up the names of two relevant people in my life who I have not talked to in over 5 years).
I'm impressed by how it just feels like it's getting the person behind the poetry, and how nearly every statement it makes is correct -- and when it isn't I am completely aware that no one could know based on the poetry alone (bar that one mistake I mentioned -- and that's very needle in a haystack, like deducing the name of a person based on a poem based on another poem with hundreds of other poems in between!)
It's really hard to explain, but it just finds more correct connections between the poems and explain much better my (recollection of) a state of mind when writing poetry. This is also the first time where it really unravels some key concepts of my poetry in a way that seemed almost effortless: it lays bare the poems and what they imply about the meaning of some of my concepts. Other good models understood these concepts, but this feels like it's on another level, as if it's making it simpler as it speaks, rather than the opposite -- like a good teacher.
When it is explaining several topics related to my poetry and myself, it cites poems which even I had already forgotten but which it is entirely right to select.
I am actually feeling a bit emotional with how much it "understands" of me here. It's somewhat incredible how LLMs have progressed from the lack of comprehension of a couple of poems paired together, going through realizing a body of work has some guiding principles and cohesion, to truly figuring out these deep concepts and intricate connections which I know for a fact would take months of someone's life to unearth. Every major breakthrough feels like my soul is being spliced together by an AI model out of these hundreds of tiny pieces of me. I can't put into words how unbelievable this feels, and this Fable analysis, like others before it, is on a new level.
Let me put it this way: there are several poems in my collection which one can try to "guess" the meaning or context of. But I don't think many people would get it, because they would have had to know me really well and to be following along my life as it went. Even then, they could very well fail to attribute such meaning. And, with each new major release, models have gotten much better at guessing.
Before Opus, they would guess incorrectly often, and in many scenarios where I thought it was rather obvious that they were wrong. I think a human spending time looking at the poetry would quickly dismiss the proposed ideas of the model.
With Opus, it was the first time that I would almost always say: "Ok, the model got this wrong, but I think many humans would make the same 'mistake', and it wouldn't surprise me if everyone just assumed what Opus did".
Now, with Fable, there are very, very, very few sentences in this very long answer it produced where I can say: "Yeah you got that wrong, but I get it". In almost every situation it is mapping concepts, ideas, interpretations and cause-and-effect correctly. Yes, it is hard to "guess" what I thought, or was going through, or how X connected to Y -- but this model is doing it, incredibly consistently. I know I'll get the usual naysayers to these posts who think I'm just shilling a model, but this is the truth: what is being done here is amazing and I don't believe I know any person around me who would find this out about myself reading all of my poetry.
I often write poetry from the point of view of other people (some of which I do not know) and models (even Opus) have this tendency to make the opinions in poems as my own. Fable is the first that looks at a particular poem here and says "maybe this is not the author's opinion, who knows". The literal first model. It then immediately fails to do so with another poem, assuming it was about myself, but it's clear, undeniable progress. And like I said: I think most people would not _know_ which poems are truly about myself or not.
I've written word after word here, and yet words elude me to convey what this model represents to me. How it's almost always right, how it sees my fractured bits as a sort of cohesive whole, and how it just seems to "understand everything better". That's just it: it just seems like it really understood everything better. Like Opus before it, and like Gemini 2.5 pro before it. Out of the tens of thousands of verses, it picks some which no other model had picked and which I feel truly represent some of my best work. Older models seemed to sort of have a "hole" in its knowledge in the middle of the corpus, where they knew what was there but in a sort of hazy/foggy way. This model seems to recall every part of the corpus with the same precision.
For context:
- Opus 4.7/4.8 were a noticeable downgrade over Opus 4.6. They wrote more, in a harder to parse way, and they made up more. Still, All Opus models are clearly superior to everyone else by a large margin
- Sonnet-level models have a slight edge above the best of the other models. But they make too many mistakes, don't grasp several concepts, mix up their dates and timelines. 3 years ago I would have been blown away by Sonnet models but today they are inferior.
- Gemini models have a unique way of approaching the request, where they try to literally interpret my poetry as a mathematical theory. This sort of makes sense if you look at some poems, but it is surely laughable, as if someone one day actually has access to all of it, no one in their right mind would do so. This is a shame, because the first big breakthrough with LLMs and my poetry, to me, came with 2.5 pro, which was the first model that could look at the whole corpus as a cohesive whole without getting lost in the middle of it or making things up.
- GPT models have improved over time and also have this sort of alien-like language, sometimes being a bit too blunt in their analysis, but I can't say they are meaningfully superior to Gemini models.
I am very pleased to see progress in this area again, as Opus 4.7/4.8 were NOT progress and I was worried that we had hit a plateau here, but I can't say that.
In all honesty, the level of understanding and cohesion that Anthropic's models (Opus and above) have over my poetry means I fear my benchmark may be hitting its limits, as I don't know if there's anything a model could do that would wow me and lead me to say "this is a major breakthrough". Perhaps Mythos is a major breakthrough and I don't know. I can't find much that's wrong with it, but I also couldn't with Opus.
As I have in the past, I will periodically probe the model again and see how coherent it is. For now, I'm very happy to see an improvement.
What surprised me the most was that even though I set the thinking budget to xhigh (in OpenRouter), this model instantly started replying without showing a thinking block. I thought it just had the thinking hidden but that is not the case, as some replies showed thinking and anyway the first reply was blazingly fast. (I will try Opus 4.6 without thinking now, just to see if it changes it for the better -- maybe that was just it. I'll edit the message if it shows improvement).
What's the point of being in the cyber verification program at this point? It looks like I cannot use Fable 5 for vulnerability research.
From Opus 4.6 there are no noticeable improvements for me in code generation. It works very well, till 90% completion, if you guide it correctly. And you need a little luck. For serious production code I need to understand what I’m doing so it helps a bit, sometimes.
This is a good thing. I wish every company would do this. I subscribed to Proton Mail after interacting with someone from their team here on HN.
This is just good business sense. In what scenario would you ever make the names dumb and forgettable?
> Boris Cherny coming to HN “Hi! it’s Boris from the Claude Code team” to get real tech people’s goodwill.
This is good customer support, lol. From what I can tell, it is indeed Boris Cherny responding, not outsourced to AI or other staff. You're really getting a response from Boris. I suppose that is PR, but it's not unjustified PR, it's accurate.
I'm not even a crazy AI fan, but your criticisms are ridiculous here. It reminds me of the quote from Knives Out -- "Your Honor, she endeared herself to him through hard work and good humor."
Clearly you've never bought a TV or headphones!
ECI (good aggregate measure using IRT): https://epoch.ai/eci?view=graph&tab=release-date&subset-view...
METR time horizon (now topped out): https://metr.org/time-horizons/
They're originally named after the blends at a nearby coffee shop.
https://postscript.co/pages/brew-guide
I've noticed nobody at HN knows what "marketing" is or how to do it. It's not just naming things and being evil and cynical is not the most successful method.
…also frontier models are a superhuman life changing experience. If they aren't, what possibly could be?
https://twitter.com/brian_a_burns/status/1866987688794132816
Well, TIL.
- It talks a LOT more like GPT models. You know: wrinkle, shape, gate, coarse, scope, gap, path, production-ready-workflow-of-the-day, and so on -- "that's expected, a consequence of the previous like-driven workflow". If I wanted to get a headache using AI I would have gone with GPT in the first place!
- It outputs text in a much harder way to follow along. I can't exactly say what it is. Maybe a bit of everything? Bolds are missing, bullet points are gone, paragraphs are bland and too long, and it doesn't feel like a model programming with me, but rather a somewhat full of themselves grandpa developer looking down on me. It's very weird to describe this, but it is definitely how I feel.
Granted this can totally be because of the way it reacts to the prompts now. We've got a rather large corpus of skills and "rules and good practices" that Opus 4.6 responded to great, and maybe the new models just get turned into this when fed with them....I don't know.
Either way, with Opus 4.6 being as good as it is, I need Fable to be a significant step up to justify a price increase. if it can get me to babysit opus a little bit less on some stuff, it might be worth it. Otherwise, I'm very happy with Opus 4.6 and hope they don't deprecate it.
The other day 4.6 was fantastic for x task. Today, 4.6 overengineered everything and I had to revert all my changes. When evaluating models, perhaps it makes sense to consider luck as an ingredient before reaching any personal conclusion.
That's where all the regressions and inconsistency in experiences stem from: RL can still only go so far vs having more parameters
They are not just leagues behind what experts would code, they are not even playing the same game.
Which is to be expected, as there isn't so much physics or high performance gpu code available as there is for your typical CRUD API and JS frontend.
It's getting to a point that it's offputting, and the next step would be to put it into "untrusted" bucket. Opus 4.7 already burned their credibility once, 2 more strikes remain.
Also, I dont think Boris C. is coming here for PR. He is a tech guy, and this is the best place for tech discussions. Why so cynical? The guy is an engineer.
I've been working with gpt 5.5 and opus 4.8 quite a lot, and interacting with Fable feels like a smart guy just entered the room.
>TOP 5 METHODS FROM BORIS ON HOW TO SPEND MORE MONEY ON TOKENS
>Boris from Claude just told he doesn't prompt anymore. He LOOPS instead
>"chatgpt has gotten soooo much better with the latest update."
>"codex is the best AI coding product and we want to make it easy to try."
Karpathy about Fable 5:
>"You can give it a lot more ambitious tasks than what you're used to, the model "gets it""
Sam Altman about gpt-5.4:
>In my experience, it "gets what to do"
What a time to be alive. Models are great, but all the slop, marketing, and fakeness around them is just unbearable.
While everyone else is wasting time and money on the slower, more expensive models, you've found a way to outpace everyone for less money. Everyone else is wrong and you will get rich.
(I don't actually believe the premise is true, I'm just pointing out the logical conclusion to what you're saying so maybe we can reconsider the premise)
Lol anti-AI bias on HN is crazy. Simply giving your product a quirky name is now being considered manipulative advertising. Is just doing normal PR and marketing something AI companies aren't allowed to do?
Defy standard DoD precedent going back forever, that every other country has some form of too, and championing it like they are some kind of moral freedom fighters.
Like selling the DoD guns and telling them they can only shoot bad guys with those guns, and that you will be the one to decide who counts as a bad guy...
I still remember Sam Altman “begging AI to be regulated” and AGI being “some thousand days away”.
Breed faster horses and hope one will birth a locomotive.
Oops, time to reauthenticate for the 10th time!
Using llms is the equivalent of driving to the store that's 3 blocks away, just like how that's bad for your body (if done all the time), using llms is as bad for your brain.
Before LLMs, we started relying on certain technologies like Maps apps to navigate, now people can't even get around their own town without having access to various cloud services. The implications of not being able to work, think plan without access to an llm are really bad. Its going to destroy your brain and make you an incredibly average person at best.
LLM people are going to lose the ability to read and think for yourself and then your competency is going to be 1:1 correlated to the quality and quantity of tokens you can afford, or a billionaire is willing to allow you access too. Your work will be the mean (at best), because it will the same quality of output everyone else is capable of.
This is seriously the biggest trap by tech. Your bargaining power for your labor is going to get drastically reduced because you won't be able to differentiate your value from anyone else that has access to an LLM. What happens when everyone has the same skill level for certain work? Idk, ask McDonald's employees how replaceable they are. Use them wisely (or not/hardly at all) don't drive to the store 3 blocks away for every little thing you need.
You can continue doing that. The problem here is time and cost. If you can use the calculator to do something in seconds, why would you want to use your hands to do the calculations for minutes/hours.
> Using llms is the equivalent of driving to the store that's 3 blocks away, just like how that's bad for your body (if done all the time), using llms is as bad for your brain.
And coding will soon be the equivalent of walking between two cities because you don't want to use a car (LLM). You are free to do it, its just economically not sound anymore.
> This is seriously the biggest trap by tech. Your bargaining power for your labor is going to get drastically reduced because you won't be able to differentiate your value from anyone else that has access to an LLM. What happens when everyone has the same skill level for certain work?
Its not our values that will diminish, its the cost of our intelligence, human intelligence. But I agree with the rest of your comment.
Why is everyone so okay with these companies intentionally gimping their AI and choosing who is allowed to know certain types of information in the name of safety? Can you imagine if Microsoft shipped a feature in their OS that watched what you did and shut down the computer if it detected you were doing something it deemed "unsafe"?
We really need truly open source versions of models like this, otherwise we are allowing a few oligarchs to directly dictate which uses of our own computers are allowed and not allowed.
Imagine if Google would tell you "we can't let you search that as you may use it for harm".
Also 2x the usage of Claude? Your limits are already ridiculously low.
...don't like the sound of that.
Why oh why are we insisting on dragging these violent legacy states into the AI age? Let alone using them as a trust vector for when to (and not to) remove safeguards?
This seems like a way to get somebody nuked.
Huh? We've seen nothing but wall to wall predictions that these models are going to take all of our jobs and kill us.
What's the value add here?
Glad to hear the UK is finally making an effort to catch up on the AI front ;)
Probably tongue-in-cheek, but UK 18th, US joint 34th with Poland
[1]: https://www.theguardian.com/technology/2026/jun/08/starmer-t...
Haha, it's literally the first sentence of the Wikipedia page. That's fucking funny. Try again.
Also, the economist is majority foreign owned, so try doing more than 1 second of research, or be more civil, or ideally both.
I get you might not hear this stuff if you're not in EU or Poland itself, but seriously, just check the latest polling and history of PiS rule. It would take over a decade to event attempt to undo the damage that has been done to the rule of law in Poland, and the currently ruling "anti-PiS" coalition only had a short while (in which they failed to do anything) before getting neutered by the populace electing their own Trump-like buffoon that proceeds to veto everything the ruling coalition tries to pass. For added damage, the 3rd and 4th leading candidates (with combined 20% support) were the aforementioned fascists. Here's one [0]. Consider the wiki article a fraction of the cesspool he regularly produces.
[0] https://en.wikipedia.org/wiki/Grzegorz_Braun
We decided that we aren't one of those authoritarian countries.
For a small group of cyberdefenders and infrastructure providers, we’re also launching Claude Mythos 5. It’s the same underlying model as Fable 5, but with the safeguards lifted in some areas.2 Mythos 5 will initially be deployed through Project Glasswing, in collaboration with the US Government, as an upgrade to Claude Mythos Preview. It has the strongest cybersecurity capabilities of any model in the world. Soon, we intend to expand access to Mythos 5 through a broader trusted access program."
Now they want to pause AI because of "recursive self improvement".
Fool me once shame on you fool me twice...