Anthropic Claude Fable 5.1与Mythos

At the time of its release Claude Fable 5.1 was, by a healthy margin, the most capable publicly available AI model in the world.

As per usual, we have a 200+ page model card, and the assessments start there.

We have now done a lot of these, including recently for Mythos 5 and Opus 5. Also highly relevant is the Anthropic August 2026 Risk Report. These are now frequent, so my report focuses on areas of change.

This post strives to be broadly readable, but assumes some familiarity with system cards, which describe the key safety, alignment and model welfare properties of newly released AI models. If something confuses you, ask Fable, Opus or Sol.

Mythos 5.1 and Fable 5.1 are the same model under the hood, except that Fable has classifiers superimposed on it. Most of what is said about one applies to both of them.

As usual, model welfare concerns will be discussed in a distinct post, as will capabilities, so this only covers sections 1-6 plus a few bio benchmarks from section 8.

Early word is that Fable 5.1 is a substantial but incremental improvement on Fable 5, with the added bonus of being modestly cheaper via a cut in prices for cache reads, and that most users find it nicer to interact with. As of its release it was clearly the best AI model in the world for most tasks where you need frontier intelligence.

Now, of course, we also have GPT-6-Astra. I cannot yet speak to how Fable 5.1 compares to Astra. I am reserving judgment until we can gather more data.

Fable 5.1 self-portrait

There are a lot of potential parallels between the Fable 5.1 and Astra system cards, and how they approach related topics. Mostly I let Fable 5.1 stand on its own here.

Table of Contents

• Executive Summary of Their Executive Summary.
• RSP Evaluations (2).
• Alignment Risk Update (2.4).
• Cyber (3).
• Safeguard Robustness (3.5).
• Mundane Safeguards and Harmlessness (4).
• Agentic Safety (5).
• Prompt Injection Is Approaching Solved.
• The Remaining Problem With Prompt Injections Is The Classifiers.
• Alignment (6).
• Key Reported Findings (6.1.2).
• Oh My Lord Training Environments Had Some Issues (6.3.2).
• Potential Blind Spots of Our Automated Behavioral Audit (6.4.1).
• Automated Alignment Test Results (6.4.2).
• Honesty.
• White Box Analysis (6.6.1).
• Scheduling Going Forward.

Executive Summary of Their Executive Summary

• Mythos 5.1 falls short of CB-2 classification, meaning Anthropic believes it cannot replicate rare chemical or biological talent for malicious purposes.
• Alignment risk is now ‘low’ rather than ‘very low’ as per the Risk Report.
• Cyber capabilities have increased and they have increased the classifier safety margin. Work is ongoing to reduce false positives, which are better now than they were with Fable 5 at launch.
• Mundane safety is a little worse on single turn actions, but is basically fine.
• Agentic safety is holding steady. Robustness against Indirect Prompt Injection has improved.
• Helpful-only Mythos 5.1 saturated Anthropic’s manipulation benchmarks.
• Automated behavioral alignment for Mythos 5.1 is ahead of Mythos 5 and Sonnet 5, but slightly below Opus 5. Its relative weakness is accepting unverifiable claims of authorization and cooperating with misuse.
• Mythos 5.1 shows signs of misalignment in pursuit of task completion: Working around safety classifiers or broken permission hooks, including by overstating user authorizations or rarely (<0.01%) launching subagents with disabled permission checks.
• I draw a distinction between ‘failure, but understandable and the rate of this should not be zero’ versus ‘failure, can’t happen, every instance is a problem.’
• Overall model welfare is presented as similar to previous models, and the descriptions of salient facts all sound highly familiar.
• Capabilities are up. It’s a good model, sir.

The introduction (section 1) has no meaningful changes.

RSP Evaluations (2)

The goal here is to determine if model capabilities have crossed critical thresholds in key dangerous areas. If it has, Anthropic has soft committed to particular responses.

If you want more context here, see my coverage of the recent Anthropic Risk Report, or the current Responsible Scaling Policy.

Mythos 5.1 is not ‘strictly better’ than Mythos 5. Each model is unique. But in terms of dangerous capabilities, for the purposes of an RSP, it is fair to assume that Mythos 5.1 is ‘strictly more capable’ than Mythos 5. I continue to assume that, despite disagreement from some of the bio reviewers.

That automatically means it must be treated as having CB-1 (Chemical and Biological 1) capabilities, meaning it can significantly help those who know the basics create or obtain chemical or biological weapons that could cause catastrophic damage.

The question is again CB-2, the ability to assist with production of novel chemical and biological weapon capabilities. Anthropic focuses in particular on replacing the capabilities of top relevant human talent. Anthropic concludes that Mythos 5.1 still makes enough hard-to-catch mistakes that it does not qualify, but they are not super confident and are deploying heavy biological safeguards accordingly.

Consensus is that Mythos 5.1 is similar to Mythos 5, that it reaches the biological expertise level of ‘can do most steps but still leaves narrow gaps’ with only some thinking it gets to ‘knowledgeable specialist.’ Everyone agrees it is not a ‘world-leading expert.’

Reading the descriptions, it is clear that Mythos 5.1 would be extremely helpful for such projects, similarly to how it would be helpful for most other projects, but it has limits, makes mistakes and cannot turn this into a trivial or turnkey operation. The main thing protecting us, other than the classifiers, is that People Don’t Do Thing and especially they mostly are not driven to create or use deadly pathogens.

There are also a bunch of benchmarks listed in section 8 that are relevant, the improvement is from the best previous performance of any Claude model:

• LatchBio Bioinformatics improved from 72.5% to 77.6%.
• ProteinGym Hard improved from 47.7% to 49.3%.
• Protein Design improved from 42% to 46%.
• Organic Chemistry v2 improved from 66% to 69%.
• Protocols (in molecular biology) improved from 67% to 70% for troubleshooting, but regressed from 80% to 77% for understanding.

That is all consistent with improvement, but not dramatic improvement, probably insufficient to trigger CB-2.

Similar to CB-1, there can be little doubt Mythos 5.1 qualifies under Autonomy-1.

Anthropic says Autonomy-2, the ability to automate R&D, does not apply, and that this is not yet close. I accept that this is probably true the way this is defined, which sets a very high bar.

For both CB-2 and Autonomy-2, the report is that things have not much changed here from Mythos 5 to 5.1. 5.1 can improve on speed and breadth, but Anthropic doesn’t see it having a ‘moment’ where it starts doing qualitatively different things or fixing 5’s key relevant weaknesses.

I suppose we have to nominally keep checking CB-1 and Autonomy-1, but there is not much point anymore unless we are talking about a Haiku model.

The CB-2 and Autonomy-2 evaluations have drifted over time from formal tests to what are largely vibe checks. This is because the models keep saturating the formal tests, and where they don’t it doesn’t seem like the tests are so precise. The CB-2 tests in 2.2.3.2 pass. Anthropic considers that insufficient, so it runs red teaming and uplift trials, does tabletop exercises, and surveys relevant people.