ARC-AGI-3

A Latent Space report describes GPT-6 Astra, a new OpenAI model the blog says can autonomously handle AI engineering tasks—training models, labeling data, deploying systems—at an estimated cost of under $6 per hour. The claims, including 97.6% on FrontierMath and 99.9% on ARC-AGI-3, come from independent blog testing rather than an official OpenAI announcement.

OpenAI has launched GPT-6 Astra, claiming state-of-the-art results on computer use, coding, and scientific reasoning benchmarks. The model is rolling out to a limited set of organizations first, with general ChatGPT availability expected within days.

Nvidia researchers report that a custom agent harness with a supervisory component drove Claude Opus 5 from a 30% baseline score to a perfect 100% on the ARC-AGI-3 benchmark. The findings add to mounting evidence that scaffolding, not the underlying model, is the dominant factor in long-horizon agentic performance.

OpenAI says GPT-5.6 Sol scores 38.3 percent on ARC-AGI-3 using a custom Responses API configuration, edging out Claude Opus 5's 30.2 percent. Under the official benchmark harness, GPT-5.6 Sol's score drops to 7.8 percent, raising questions about what the comparison actually measures.

Claude Opus 5 scored 30.2 percent on the ARC-AGI-3 benchmark, nearly four times the previous record of 7.8 percent set by OpenAI's GPT-5.6 Sol (Max). The ARC Prize team attributes the leap to genuinely stronger reasoning, though an independent test on a separate puzzle benchmark showed far smaller improvements.