# Subquadratic — Introducing SubQ Snap: A Long-Context Decision Model for Enterprise Agents

- Company: Subquadratic (subq.ai)
- Announced: 2026-10-12
- Category: not stated
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://subq.ai/introducing-subq-snap
- Record: https://forck.live/items/23942-introducing-subq-snap-a-long-context-decision-model-for-enterprise-agents
- Subject: SubQ

Subquadratic is the only company exclusively preoccupied with how foundation model algorithms scale with regards to compute, memory, and data. Most recent AI progress has come from scaling transformers with more parameters, data, and compute. We work on the scaling relationships underneath, with the goal of building the most compute, memory, and sample efficient algorithms and models. We started with the attention, whose compute cost grows quadratically with context length in a standard transformer. To address this challenge, earlier this year we announced Subquadratic Sparse Attention (SSA) , the architectural innovation that powers SubQ , the first fully subquadratic LLM, which has remained frontier-competitive through its updates. Today we're releasing SubQ Snap , a decision model for agentic workflows built on the same foundational research. Our decision model is built to take the data-intensive but structured decisions inside an agentic workflow, like choosing which files are relevant, which tool to use next, whether a test result passes, or which step needs a frontier model. …

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Record: https://forck.live/items/23942-introducing-subq-snap-a-long-context-decision-model-for-enterprise-agents
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