BDH-CQ: Reasoning That Never Thinks Out Loud, at $0.0007 a Task
Summary
Pathway posted BDH-CQ to arXiv on August 10, 2026: a 150M-parameter reasoning model that reports 29.5% pass@2 on ARC-AGI-1 at a computed inference cost of $0.0007 per task, which the paper says breaks the benchmark's published cost-accuracy Pareto frontier. The mechanism is where the reasoning happens. Chain-of-thought models verbalize every intermediate step, and each of those tokens is metered compute. BDH-CQ updates a recurrent memory as examples arrive at inference time, then solves the query through iterative computation in latent space without verbalizing intermediate reasoning, so there is almost nothing to meter. It builds on Dragon Hatchling (BDH), Pathway's post-transformer recurrent architecture in which neuron-like units communicate through low-rank interactions and context lives in an evolving associative state. No frontier-model comparison numbers appear in the video: circulating GPT-5.6 figures are self-reported and unverified by ARC Prize at time of writing, so only the paper's own numbers are quoted. The paper: arxiv.org/abs/2608.09888
About this video
Pathway posted BDH-CQ to arXiv on August 10, 2026: a 150M-parameter reasoning model that reports 29.5% pass@2 on ARC-AGI-1 at a computed inference cost of $0.0007 per task, which the paper says breaks the benchmark's published cost-accuracy Pareto frontier. The mechanism is where the reasoning happens. Chain-of-thought models verbalize every intermediate step, and each of those tokens is metered compute. BDH-CQ updates a recurrent memory as examples arrive at inference time, then solves the query through iterative computation in latent space without verbalizing intermediate reasoning, so there is almost nothing to meter. It builds on Dragon Hatchling (BDH), Pathway's post-transformer recurrent architecture in which neuron-like units communicate through low-rank interactions and context lives in an evolving associative state. No frontier-model comparison numbers appear in the video: circulating GPT-5.6 figures are self-reported and unverified by ARC Prize at time of writing, so only the paper's own numbers are quoted. The paper: arxiv.org/abs/2608.09888