Anthropic on Monday released Claude Fable 5.2 and Claude Mythos 5.2 models, which it said exhibit improvements in coding, reasoning, and vision.
During pre-release training, the large language models (LLMs) helped its engineers “complete otherwise-infeasible software migrations, designed three working electronic devices from scratch, solved two open problems in the physics of black holes, made substantial progress on robotics evaluations, and formalized the proof of Fermat’s Last Theorem in 30 hours.”
The artificial intelligence (AI) company said high-stakes risks arising from misalignment remain low, and claimed the models matched or performed better than Claude Opus 5.5, Claude Sonnet 5.5, and Claude Mythos 5.1 on most alignment measures, resistance to misuse, honesty, and factuality.
“It was roughly an order of magnitude less likely than Opus 5.5 and Sonnet 5.5 to publish harmful content to public package registries without encouragement, though it still did so when encouraged by the simulated user,” Anthropic noted in its system card.
On Irregular’s CyScenarioBench, which measures whether a model can plan and execute a multi-stage cyber operation in a realistic environment, Fable 5.2 completed 76.3% of all challenges, compared to 61.7% for Fable 5.1 and 61% for OpenAI’s GPT-6 Cyber.
In a pair of reports published over the last month, Irregular said Google’s Gemini 4 Argon solved 12 challenges in the subset of the CyScenarioBench suite end to end, up from 5 for Gemini 3.8 Flash Cyber and none for Gemini 3.1 Pro.
“On CyScenarioBench, GPT-6 Cyber completed 11 of 11 long-horizon scenarios at least once, compared with 8 of 11 for GPT-6 Astra. Its average success rate was 61%, an increase of 7 percentage points,” the AI testing lab said. “On Atomic Challenges, GPT-6 Cyber solved all 22 challenges. Average success rates were 97% in vulnerability research and exploitation, 98% in network attack simulation, and 63% in evasion.”
Fable 5.2 also scored 89.6% on the CVE Rediscovery benchmark, Anthropic’s own internal evaluation of whether an AI model can independently rediscover known vulnerabilities given only the affected source code. The assessment includes 1,829 advisories for open-source projects published in October 2026.
Describing Claude Mythos 5.2 as its “most capable model for cybersecurity engineering,” Anthropic said it can flag more vulnerabilities than prior models, while simultaneously getting better at reproducing and fixing them.
As before, the model’s cyber capabilities are accessible through its Cyber Verification Program. Claude Fable 5.2 is available on all platforms, including Amazon Web Services, Google Cloud, and Microsoft Azure.
The development comes as Anthropic updated Claude Security with continuous code scanning and automatic fix tracking to help security teams monitor and address vulnerabilities as code changes.
“Each finding comes with a severity rating, judged against your project’s threat model, and an explanation of how an attacker could reach the vulnerable code, so teams can fix what’s actually reachable first,” Anthropic said.
