Claude Fable 5.2 and Mythos 5.2: Anthropic claims its models cracked black hole problems

What's going on

Anthropic, the company behind the AI assistant Claude, released two new frontier models on Monday: Claude Fable 5.2 and Mythos 5.2. According to the company, they're built to "tackle the hardest technical challenges" and outperform their predecessors at coding, reasoning and understanding images (vision).

The two models come with different levels of access. Fable 5.2 is available to all Claude users starting now. Mythos 5.2, on the other hand, is only available to vetted organizations working in cybersecurity or biomedical research. One claim in particular is turning heads: in pre-release testing, the models reportedly solved two previously unsolved problems in black hole physics.

What the models reportedly achieved

Mashable quotes Anthropic as saying that in pre-launch testing, the models

"designed three working electronic devices from scratch, solved two open problems in black hole physics … and formalized the proof of Fermat's Last Theorem in 30 hours."

More details on the physics problems surfaced on the Reddit forum r/singularity, where the news quickly climbed to the top. According to the post title, one of the problems is a 23-year-old question: do black holes form suddenly in models of tiny universes? Physicists use these heavily simplified toy worlds to work out properties of gravity that would be too complicated to calculate in the real universe. The second problem reportedly involved pinning down the exact limits of a roughly 15-year-old result. The title is cut off at that point, so the available sources don't reveal which result exactly.

The mention of Fermat's Last Theorem is notable too. Andrew Wiles proved the theorem in the 1990s, but his proof runs to hundreds of pages and draws on large parts of modern mathematics. Formalizing means writing out every single step so that a computer program (a proof assistant) can check it without gaps. Human mathematicians typically spend years on projects like this. Anthropic says 30 hours. The available sources don't say whether the formalization is complete, what prior work was used, or whether experts have reviewed the result yet.

Speed, communication and pricing

Beyond the research results, Anthropic also highlights practical improvements:

• 30 percent faster: Fable 5.2 and Mythos 5.2 are said to deliver responses 30 percent faster than the 5.1 predecessors.
• Clearer answers: According to Anthropic, the new models "communicate" more clearly than earlier versions.
• Cheaper API: If you integrate the models into your own applications via the API, you'll pay less than before.

Tokens are the small chunks of text, usually word fragments, that a language model breaks text into. A million tokens is roughly several hundred book pages. Output costing more than input is standard for these models, since generating text takes more compute than reading it in.

On launch day, according to Mashable, Fable 5.2 took first place in the Artificial Analysis Intelligence Index. This independent service rolls the results of many benchmarks into an overall score. Google's Gemini 4 Carbon held the top spot before.

Why Mythos 5.2 isn't open to everyone

Anthropic deliberately separates the two models based on their risk of misuse. According to the company, Fable 5.2 has "strong cybersecurity and biology safeguards to prevent misuse," which is why it's open to everyone. That means, for example, the model shouldn't help anyone build malware or run dangerous biological experiments.

Mythos 5.2, by contrast, is only available to vetted organizations in cybersecurity and biomedical research. The available sources don't explain in detail how exactly Mythos differs from Fable, for instance whether it's more capable or simply has fewer restrictions. This tiered release follows an industry trend: the same capabilities that make a model useful for research can also help attackers. Many providers therefore only hand their most powerful versions to vetted customers.

Background: the frontier model race

The launch comes at a time when the big AI labs are shipping new frontier models in rapid succession. Mashable lists Google Gemini 4 Carbon, Meta Muse Wonder and OpenAI's GPT-6 Astra as models released shortly before. In this environment, the top spot on leaderboards like Artificial Analysis often changes hands within weeks.

Claude models being used in theoretical physics isn't new. Quantum Zeitgeist reported on an earlier experiment by Harvard professor Matthew Schwartz. He had the older Claude Opus 4.5 model carry out a complete research calculation in high-energy physics: the resummation of the "Sudakov shoulder" in the C-parameter. This quantity describes how particle debris is distributed after collisions. Schwartz steered the model through text prompts alone and didn't edit any files himself. The project involved more than 110 drafts across seven stages, 36 million tokens and over 40 hours of compute on regular CPUs. Instead of the usual year, the work took two weeks. Schwartz said at the time:

"This may be the most important paper I've ever written – not because of the physics, but because of the method."

But he also cautioned that AI "isn't doing science end to end yet." An expert still has to check the results carefully. He had deliberately picked a problem at the level of a second-year PhD student, where the solution was known in principle. That gives you a yardstick for how big a leap Anthropic's new claim would be: the two physics problems are said to be genuinely open questions, not calculations with a known outcome.

The bigger picture

If Fable 5.2 is as good as Anthropic says, every Claude user gets immediate access to a model that's faster, cheaper and, according to Artificial Analysis, currently the strongest available. For developers, the lower prices and higher speed matter most, and those benefits are easy to verify in day-to-day use.

Caution is warranted when it comes to the spectacular research results. So far, every claim about the black holes, the electronic devices and the Fermat formalization comes from Anthropic itself. It's unclear whether independent physicists have checked the solutions, whether they'll be published, and how much human guidance was needed. The Schwartz experiment shows that successes like these have so far depended heavily on experienced scientists guiding and checking the model. Only once experts have reviewed the work will we know whether an AI model really found new physics on its own. It also remains unclear how big the gap actually is between the freely available Fable 5.2 and the locked-down Mythos 5.2.