GoBench puts GPT-6 Astra at 2,568 Elo on 9x9 Go, 1,800 short of KataGo.

Roland Gao published GoBench on September 15, scoring frontier models against a calibrated ladder of KataGo opponents. Astra Max 2,568, Astra High 2,227, Claude Opus 5 High 2,076, GPT-5.6 Sol Max 1,929, against KataGo's 4,400. Given coding tools and two hours of preparation before evaluation, Codex with Astra reaches 3,560, a 1,000-point jump and the number I'd actually pay attention to. The author claims r=0.83 correlation with ARC-AGI-2; the top r/MachineLearning reply pushes back that Go training data is free to generate, so the benchmark is arbitrary in a way ARC deliberately isn't. That objection is correct and the tool-use delta still stands on its own.