Text model

SubQ 1.1 Small

SubQ 1.1 Small is a long-context language model built on Subquadratic Sparse Attention (SSA), a learned sparse mechanism with linear compute cost. It supports context windows up to 12M tokens with near-perfect retrieval, using 64.5x less compute than dense attention at 1M tokens and running 56x faster than FlashAttention-2.