Pathway developed its brain-inspired BDH (Dragon Hatchling) architecture and ran training on Amazon SageMaker HyperPod for scaling out distributed GPU compute. BDH-CQ reached 29.2% pass@2 on the ARC-AGI-1 benchmark at a stated cost of US $0.0007 per task. The shift updates model reasoning in a recurrent latent state without generating long chain-of-thought traces, changing the cost–accuracy tradeoff and how memory and computation are handled at inference.
OpenAI’s GPT-6 Astra became the first AI model to score a perfect 450 on South Korea’s 2026 CSAT evaluation results posted on GitHub. Astra used 357,000 tokens, the lowest reported total among publicly available models. The report changes expectations for AI efficiency and performance on standardized questions, while experts still warn scores don’t fully reflect real-world problem-solving.
GPT-6 Astra’s launch sparked renewed public debate over whether AGI has arrived, with OpenAI, Nvidia, researchers, and benchmarkers giving conflicting interpretations. Astra’s ARC-AGI-3 results reached 62.7% on a standardized harness and 99.9% when preserving reasoning state across requests. The dispute shifts from contractual triggers and single benchmarks to competing yardsticks and governance questions, leaving AGI as an undefined term largely used for messaging rather than a verifiable threshold.
Artificial Analysis updated its Intelligence Index to version 4.3, tying OpenAI’s GPT-6 Astra (max) and Anthropic’s Claude Fable 5.1 (max with fallback) at the top with 53 points. Terminal-Bench was upgraded from version 2.1 to 4.0 using 66 tasks, where GPT-6 Astra scores 59.1% and Claude Fable 5.1 scores 52.0%. The rankings change within a few days because two test evaluations were replaced/upgraded and the index was recalculated after each revision, so Astra moved from fifth to first while some competitors dropped.
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