THE CLAIM. GPT-5.6 Sol tops the ARC-AGI-2 leaderboard at 92.5%, clearing the benchmark built to isolate fluid reasoning and resist memorization, and beating the average human's 66%. The read everywhere is that frontier models have essentially cracked abstract reasoning.

THE CHECK. the score is real and ARC Prize verified, and on its own terms it is a genuine jump. Two things temper the headline. First, the 92.5% depends on Sol's most expensive reasoning mode; dial the effort down and ARC-AGI-2 collapses to 42.5%, and the ARC Prize's own cost-capped grand prize, which needs above 85% cheaply, is still unclaimed. Second, ARC-AGI is a series that keeps raising the bar, and the newest rung is a different kind of test. ARC-AGI-3 is an interactive, agentic benchmark, where a model must explore an unfamiliar environment, infer the goal, and plan, and there the same model at the same setting scores 7.78% while human testers solve 100%. That does not prove the ARC-AGI-2 result was hollow. It shows the fluid-reasoning progress does not yet extend to agentic novelty, and that every time this team builds a new test, today's models fail it until they catch up. Saturating a benchmark is not the same as acquiring the ability it was built to isolate.