Pathway's 150M-Parameter BDH-CQ Scores 29.5% on ARC-AGI-1 at $0.0007 per Task — 11x Cheaper Than GPT-5.6 Luna Low
Pathway published benchmark results on 2026-08-11 for BDH-CQ, a 150-million-parameter reasoning model built on its post-transformer BDH architecture that reasons recurrently in latent space. It scored 29.5% pass@2 on the public ARC-AGI-1 eval set at a computed inference cost of $0.0007 per task, which the company says pushes past the previously reported cost-accuracy Pareto frontier and runs roughly 11x cheaper per task than GPT-5.6 Luna (Low) even after OpenAI's 80% price cut on 5.6 Luna on July 30. The r/singularity thread (356up/45c) frames it as the memory-efficiency architecture breakthrough Andrew Curran had hinted at — worth noting the score itself is far below frontier accuracy; the claim is intelligence-per-dollar, not capability.
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