BDH-CQ sets a new ARC-AGI-1 cost-efficiency point with recurrent latent reasoning
Pathway reports that BDH-CQ, a proprietary 150-million-parameter post-Transformer system, combines in-context learning with recurrent latent reasoning and reaches 29.5% pass@2 on the public ARC-AGI-1 evaluation set. The reported operating point uses about 0.85 H200 GPU-seconds per task, corresponding to a computed inference cost of $0.00070 per task at the paper's hardware-price assumption. A documented black-box audit by external-affiliation co-authors reproduced the deployed system's 29.5% score without access to model weights.