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Explore A 150M model broke the ARC-AGI cost record — but not the score with 37 views, 1 likes, and 0 comments. Experience the impact of this video content that has captured audience attention.

BDH-CQ is a 150-million-parameter reasoning model that does its thinking in latent space rather than writing it out. On ARC-AGI-1 it scored 29.5% pass@2 at $0.0007 per task — a record in cost efficiency, not in accuracy. Here is what the paper actually claims, and what the headlines left out. Paper: https://arxiv.org/abs/2608.09888 Authors: Björn Engdahl, Adrian Kosowski, Jan Chorowski, Zuzanna Stamirowska, Przemysław Uznański, Junlin Jiang, Rohan Phadke, Remigiusz Kinas, Richard Zhong Submitted 10 August 2026. Preprint — not yet peer reviewed. Tamsen is an AI-generated presenter. The research and fact-checking are done by real people. #ai #airesearch #arcagi #machinelearning #llm

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