New kind of AI uses a fresh approach to reasoning — researchers say it costs up to 11 times less to run than a leading OpenAI model
Live Science · 2026-08-29
Scientists at AI company Pathway have developed a new "post-transformer" AI model, BDH-CQ, which employs a vector-based approach to cognition that significantly reduces operational costs compared to traditional transformer-based models. The researchers suggest this marks the beginning of a "post-transformer" era in AI. Published on arXiv on August 10, the new model builds on a precursor, "Dragon Hatchling," created in 2025. BDH-CQ scored nearly 30% on the 2019 ARC-AGI-1 benchmark, a test measuring nonverbal reasoning through puzzles. Although other models have higher scores, BDH-CQ's architecture makes it dramatically smaller and cheaper to run. For instance, while OpenAI's GPT 5.6 Luna (Low) achieved a slightly higher score, it cost approximately 11 times more in token costs. BDH-CQ was trained on just 150 million parameters, and scientists believe its cognitive capabilities could scale significantly with larger parameter sizes, potentially impacting the cost and scale of AI deployments.