{
  "id": 14458856,
  "title": "“Take work away from frontier LLMs”: Subquadratic’s decision model claims 12x Jev’s context window",
  "url": "https://urgent.news/2026/10/14/take-work-away-from-frontier-llms-subquadratics-decision-model-claims",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-14T13:35:15.000Z",
  "source": {
    "name": "The New Stack",
    "slug": "the-new-stack",
    "url": "https://thenewstack.io/subquadratic-snap-jev-decision-model/"
  },
  "original_language": "en",
  "account": null,
  "summary": "Subquadratic has entered the decision model market with SubQ Snap, a model capable of processing up to 384,000 tokens of text and images in a single request, which is 12 times the 32K-token context limit of Jev. This decision model, which specializes in selecting from predefined answers for AI agents, could potentially allow for AI agents to make decisions across large codebases, documents, and interaction histories without having to break information into smaller chunks. SubQ Snap uses Subquadratic Sparse Attention (SSA) to achieve this.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}