Subquadratic launched from stealth this week with a claim that its subquadratic architecture can cut attention compute by nearly 1,000x at very large context lengths. On its launch page, the startup said its first model, SubQ 1M-Preview , is built on a “fully subquadratic architecture” rather than the standard transformer pattern where attention cost rises quadratically with context length. The headline number is large enough to attract immediate scrutiny. VentureBeat reported that Subquadratic had not published independent research validating the claim at launch, even as it pitched three private-beta products built around the same subquadratic architecture .…