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# Claude Fable 5.2

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  1. Vercel News

    Claude Fable 5.2 lands on AI Gateway: it runs long tasks unattended and hands simpler work to smaller models

    Anthropic's Claude Fable 5.2 is now callable through AI Gateway, built for open-ended technical work and improving on earlier Fable models in coding, reasoning and vision, and able to run long, ambiguous tasks unattended. It can act as an orchestrator that hands simpler tasks to smaller models, or as an advisor other Claude models consult on harder problems, with clearer communication and faster output. The model ships with cybersecurity and biology safety classifiers, and access requires data retention: prompts and completions are kept for 30 days and not used to train Claude, while teams with Zero Data Retention enabled get an error instead of a forwarded request.

  2. Anthropic

    Claude Fable 5.2 designs three electronic prototypes from one prompt: Diode built them straight from its design files, with no circuitry fixes

    Working again with Diode Computers, Claude Fable 5.2 designed three devices—a speakerphone, a voice-assistant hub and a handheld virtual pet—from short prompts, handling board layout, routing, enclosure modeling and firmware itself. Earlier models could not reliably lay out a circuit board and produced boards that were 95% complete yet unusable; on Diode's internal PCB Gym benchmark, Fable 5.2 scored 69% against 25% for Fable 5. All three boards were manufactured directly from the design files without adjustments, but they remain prototypes that have not been through electrical validation, antenna tuning, thermal testing or certification.

  3. 1,000 agents re-proved Fermat's Last Theorem on their own: 28.7 hours and one-third the output tokens

    Anthropic had 1,000 agents running an early version of Claude Fable 5.2 redo the formalization of Fermat's Last Theorem without the Prove2Me platform and without a researcher directing the work, coordinating only through Git and a shared SQL database. The team finished in 28.7 hours, using about one-third the output tokens of the earlier formalization, which took a researcher and dozens of agents 11 days, and wrote a proof about one-seventh as long. The authors call it a toy experiment suggesting such agent teams can accomplish long-horizon goals within carefully designed safety boundaries.

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