GitHub released Project HydraFusion, a research-preview system in Copilot CLI that selects an execution workflow per coding request instead of using a single model. It reported on TerminalBench an estimated cost of 67% lower with verified task quality up 4.9 points versus Claude Opus 5. As a result, tasks may be solved in a single call, or drafted then critiqued/escalated via quality-gate checks, with billing based on the tokens consumed by the workflow’s underlying models.
Anthropic launched Claude Fable 5.1 for coding and knowledge work and the reporting compared it with Fable 5 using a set of practical tasks. Terminal-Bench-Science shows 52.6% for 5.1 versus 24.7% for 5. Fable 5 and 5.1 matched on four real-work tests, so any upgrade advantage may depend on whether your use case resembles the benchmark’s long, messy research agents, with day-to-day results looking similar.
OpenAI updated multiple evaluation benchmark metrics for its GPT-6 Astra model after its Sept. 3 launch blog, with some Astra scores rising while some rival-model scores fell. The reported hallucination rate for Astra changed from 4.2% to 2% within hours, and later returned to 4.2%. The result is a moving target for comparing model performance across checkpoints and harnesses, fueling scrutiny over how evaluations are configured and reported.
Anthropic used Claude to turn Andrew Wiles’ Fermat’s Last Theorem proof into computer-verifiable Lean code. The formalization consists of 13 million lines of Lean code and was completed in 11 days. The result is a large Lean proof file that can be checked automatically by computers, reducing human-error risk and easing sharing.
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