September 14, 2026
- GPT-6 Astra’s new agent benchmarks show a capability jump with large reliability caveats. Across six Vending-Bench runs, each simulating a year from a $500 starting balance, GPT-6 Astra averaged a final balance of $15,515 versus $5,422 for Claude Fable 5.1, according to The Decoder’s report on Andon Labs’ tests. On Drone-Bench, Astra’s best attempts beat the human-AI baseline on all five subtasks, including code for finding and following a specified person, but overall success remained unreliable. A separate robotics test had Astra complete 7 of 100 dual-arm tasks; MolmoAct2 completed 0 of the same 100. These were controlled evaluations, not live business or surveillance deployments, and they materially extend the initial Astra coverage (earlier coverage). · Model Capability, Evaluation & Safety
- Support for pacing frontier AI broadened, but no binding speed limit exists. The Decoder reports that Sam Altman, Elon Musk, and Demis Hassabis backed at least parts of Anthropic CEO Dario Amodei’s call for slower capability gains and independent oversight. Altman said OpenAI would give independent evaluators employee-like access. The reports describe no common capability threshold, timetable, or enforcement mechanism, making this public support and an evaluator commitment rather than an agreed pause. The endorsements are the material update to Amodei’s proposal covered yesterday (earlier coverage). (discussion) · Model Capability, Evaluation & Safety
- Written reasoning steps map to distinct internal activation patterns. A study summarized by The Decoder found that calculation, formula retrieval, and deduction were separable in model states, especially in middle layers. The result supports research into latent-state monitoring because visible chain-of-thought does not expose all processing, but it does not establish that written reasoning is a complete or faithful account of how a model reached its answer. · Model Capability, Evaluation & Safety