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What is SubQ Snap 1.1?

SubQ Snap is an all-encompassing hosted multimodal decision-making framework designed for developers focused on building AI agents and enterprise workflows. By leveraging Subquadratic’s API, applications are able to send both text and image data along with targeted inquiries, resulting in structured responses that may feature labels, options, scores, and probabilities. This capability supports a multitude of tasks, including tool and file selection, decision routing, information triage, implementation of guardrails, item ranking, data classification, and validation of tests or results against established criteria. The system is adept at processing as many as 384K tokens of context while also handling image inputs, making it distinctly suited for making limited decisions rather than producing open-ended text, thus serving as a valuable enhancement to language models employed for planning or content generation. Additionally, the public-preview API documentation offers comprehensive examples of requests, guidance on how to access the model, and various decision formats available for user utilization. This innovative framework not only simplifies the decision-making process for developers but also significantly boosts the operational efficiency of AI-driven applications, paving the way for more effective workflows. By integrating visual and textual data effectively, SubQ Snap positions itself as a pivotal tool in the evolving landscape of AI technologies.

What is Microsoft-Decision-1?

Microsoft-Decision-1 is a highly effective decision-scoring model specifically designed for structured outputs, allowing software systems to take swift actions. This innovative model supports a range of functionalities including routing, classification, prioritization, verification, and workflow management, applicable across various applications, agents, and automated systems. Developed through post-training of Qwen3.5-9B, it excels in single-pass decision scoring and delivers calibrated probabilities for a defined set of response choices. The model is adept at addressing yes/no inquiries, multiple-choice situations, rating scales, and rubric-based assessments of AI-generated outputs and agent performances via a structured API. Comprehensive evaluations carried out by Microsoft across 36 benchmarks covering routing, ranking, long-context understanding, multilingual functions, and tasks outside conventional distributions demonstrate that it achieved top accuracy levels with impressively low latency. Additionally, the model places a strong emphasis on robustness, with extensive testing conducted to ensure decision-making stability even when prompts undergo rephrasing or modifications. This commitment to stability highlights its potential for delivering reliable performance in diverse real-world scenarios, making it a versatile tool for various industries.

Media

Media

Integrations Supported

OpenAI

Integrations Supported

Microsoft Foundry
OpenRouter
Qwen3.5

API Availability

Has API

API Availability

Has API

Pricing Information

$0.05/1M input tokens
$0.05 per 1 million input tokens; output tokens are free. SubQ Snap is in public preview, with access subject to capacity limits.

Pricing Information

$0.042 per 1M tokens

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Subquadratic

Date Founded

2025

Company Location

United States

Company Website

subq.ai/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

commandline.microsoft.com/microsoft-decision-1-model-foundry/

Categories and Features

AI Decision Models

Not specified

Categories and Features

AI Decision Models

Not specified

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