AI model launches · Subquadratic
SubQ model launch
Subquadratic introduces SubQ, a sparse-attention model with a 12 million token context window that it says needs far less compute.
Alexander Whedon @alex_whedon · 5 May 2026
From the post
Introducing SubQ - a major breakthrough in LLM intelligence. It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA), And the first frontier model with a 12 million token context window which is: - 52x faster than FlashAttention at 1MM tokens - Less than 5% the cost of Opus Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention). Only a small fraction actually matter. @subquadratic finds and focuses only on the ones that do. That's nearly 1,000x less compute and a new way for LLMs to scale.
Alexander Whedon @alex_whedon on X · 5 May 2026
