One of the first "neolabs" to announce something tangible is showing off an AI breakthrough that would fundamentally change the architecture of today's AI, making it cheaper to operate and requiring far less data center power.
Pathway unveiled a 150-million parameter small reasoning model, BDH-CQ, on Tuesday, along with benchmarking results that back up Pathway's claims that its post-transformer architecture could deliver comparable performance at a fraction of the cost and computing resources of today's leading frontier models.
According to the ARC-AGI-1 benchmark, BDH-CQ achieved 29.5% pass@2 accuracy (it solved nearly a third of the problems on the test when given two guesses) with a computed inference cost of $0.0007 per task. So how does that compare with OpenAI's most cost-effective model? GPT 5.6 Luna (Low), which OpenAI just reduced in price by 80% on July 30, scored 34.5% on the same benchmark. However, even at its new cut-rate price, it cost 11 times more than Pathway's new model.
Part of that is because the Pathway model is small, doesn't need chain-of-thought to achieve reasoning, and needs less data because of its improved memory. So Luna has slightly better performance at an astronomically more expensive price. And Luna itself is a fraction of the price of the leading frontier models. So while it's very still early, what Pathway has achieved holds tremendous promise for future efficiency and cost reductions of frontier-class models.
"We need to be able to squeeze more intelligence per dollar, and for this you need to change the paradigm," Zuzanna Stamirowska, CEO and co-founder of Pathway, told The Deep View. "This is a very deep innovation, and we wouldn't have done it if it wasn't going to be, and if it didn't have a chance to capture the market."
The Pathway team believes their breakthrough is "a PageRank moment for intelligence," referring to the turning point when Larry Page and Sergey Brin realized they could make web search dramatically better by ranking pages based on the structure of links between them and not just the keywords on the page.
Stamirowska, who also appeared on The Deep View Conversations this week to do a deep dive on the fundamental limitations that are holding back LLMs, has used her background in research and game theory to assemble a team of researchers and advisors with impressive achievements:
Łukasz Kaiser: co-author of the original paper on the Transformer that launched the generative AI revolution; serves as an advisor to the company, also independently verified the ARC-AGI-1 benchmarkAlex Kurzok: former group product manager of Gemini at Google DeepMind, now chief product officer at Pathway** Jonathan Frankle**: chief AI scientist at Databricks (who spoke with The Deep View recently) serves as an advisor to Pathway on scaling and deployment and is also an investor in the companyMartín Farach-Colton: chair of computer science and engineering at NYU and one of the early employees of Google who led several important technological breakthroughs; now serves as an advisor to Pathway on its scientific vision
Our Deeper View #
In October 2025, the Pathway team first published its paper, "The Dragon Hatchling: The Missing Link between the Transformer and Models of the Brain," which quickly gained an audience in the AI research community. It laid out the company's theory and vision for a post-LLM future (BDH stands for "beautiful dragon hatchling" and is a sci-fi/fantasy reference from a Terry Pratchett story). The new benchmark released around the BDH-CQ model is the first evidence that Pathway's theory is on the mark. The team at Pathway still has a lot of work to do before its models can compete with the leading edge frontier models, but they are convinced their architecture can scale to 600B parameter models that will compete with the world's leading models and will change the economics of AI. The scaling laws that power today's top models consume so much compute, energy, and data and they are hitting limits. The industry desperately needs something like breakthroughs Pathway is espousing. There are over 40 neolabs that have raised $40B in funding and they are attacking these problems. Whether or not Pathway is the eventual flagbearer, keep an eye on these startups as major disruptors in the months and years ahead.