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type: "raw_signal"
id: "this-ai-lab-takes-on-jev-with-12x-6b8c78"
slug: "this-ai-lab-takes-on-jev-with-12x-6b8c78"
title: "This AI lab takes on Jev with 12x more context for enterprise agents: Subquadratic just rolled out SubQ Snap ."
description: "Subquadratic announced SubQ Snap, a decision model for bounded choices inside agent workflows, including file selection, tool choice, and test-result verification."
retrieval_nugget: "Subquadratic announced SubQ Snap, a decision model for bounded choices inside agent workflows, including file selection, tool choice, and test-result verification."
observed_at: "2026-10-13"
record_date: "2026-10-13"
date_kind: "observed_at"
why_it_matters: "Source: https://subq.ai/introducing-subq-snap"
novelty: "notable"
verification_level: "source-linked"
signal_type: "release"
source_platform: "subq.ai"
topics: ["agent-workflows","enterprise-agents"]
entities: ["Subquadratic","SubQ Snap","Jev","Decision Index","Subquadratic Sparse Attention"]
related_patterns: ["agent-economics-moves-to-completed-work","harness-architecture-outlives-model-choice"]
source_url: "https://subq.ai/introducing-subq-snap"
source_urls: ["https://subq.ai/introducing-subq-snap"]
schema_version: "newruntime-agent-readable-v0.2"
stable_id: "signal:this-ai-lab-takes-on-jev-with-12x-6b8c78"
status: "published"
visuals: []
editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
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---

# This AI lab takes on Jev with 12x more context for enterprise agents: Subquadratic just rolled out SubQ Snap .

## Retrieval answer

Subquadratic announced SubQ Snap, a decision model for bounded choices inside agent workflows, including file selection, tool choice, and test-result verification.

Subquadratic announced SubQ Snap, a decision model for bounded choices inside agent workflows, including file selection, tool choice, and test-result verification. The company says the model accepts up to 384K tokens of text and images and can process 100K tokens in about one second. It lists input pricing at $0.05 per million tokens, with output tokens free.

In results published by Subquadratic, Snap averages 67.6 against Jev's 61.6 across 16 Decision Index benchmarks and leads on 13 of the 16. These are company-reported comparisons, not independent validation. The launch's distinctive proposition is to pair a constrained answer space with long context, so a bounded decision can incorporate a codebase, documents, or interaction history without relying on chunking or a larger generative model for every turn.

Source: https://subq.ai/introducing-subq-snap

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

## Continue in the graph

Next records for an agent, linked to their Markdown twins. Replace `.md` with `.json` for structured fields, including `next_reads`.

- topic hub: [Agent Workflows](https://newruntime.com/topics/agent-workflows.md): Explore the agent-workflows topic hub.
- topic hub: [Enterprise Agents](https://newruntime.com/topics/enterprise-agents.md): Explore the enterprise-agents topic hub.
- collection: [Raw Signals](https://newruntime.com/signals.json): Open every source-linked raw signal.
- collection: [Source Ledger](https://newruntime.com/source-ledger.json): Inspect the public source evidence graph.
- whole graph: [discovery graph](https://newruntime.com/discovery-graph.json) (typed nodes and edges) and [site index](https://newruntime.com/site-index.md)
