Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Microsoft-Decision-1 is an efficient decision-scoring model tailored for structured outputs, enabling immediate action by software systems. This model is crafted to facilitate various functions such as routing, classification, prioritization, verification, and workflow management across different applications, agents, and automated systems. Built upon post-training from Qwen3.5-9B, it specializes in single-pass decision scoring and provides calibrated probabilities for a fixed set of response options. It is equipped to handle yes/no questions, multiple-choice scenarios, ratings, and rubric-based evaluations of both AI-generated responses and agent activities through a structured API. Extensive evaluations conducted by Microsoft, spanning 36 benchmarks in areas like routing, ranking, long context comprehension, multilingual capabilities, and tasks beyond typical distributions, indicate that it achieved the highest accuracy alongside remarkably low latency. Furthermore, the model emphasizes robustness, with rigorous testing aimed at ensuring decision stability even when prompts are rephrased or altered. This focus on stability underscores its potential for consistent performance in real-world applications.
Description
SubQ Snap is a sophisticated decision-making model designed for both enterprise and agentic workflows, enabling rapid, structured decisions across extensive datasets. It effectively manages various tasks, including identifying relevant files, choosing the appropriate tool, verifying result validity, assessing whether to proceed with a workflow, and determining the necessity of a frontier model. Unlike traditional text generators, Snap operates by taking into account specific context, a posed question, and a limited range of possible answers to produce a probability distribution for those responses. It can process up to 384K tokens, integrating diverse forms of information such as codebases, contracts, interaction histories, logs, screenshots, charts, diagrams, and scanned documents within a single query. Utilizing Subquadratic Sparse Attention technology, Snap significantly diminishes the resources needed to analyze lengthy inputs, while its decision head adeptly correlates contextual representations to permissible answers without relying on autoregressive text generation. This innovative approach enhances efficiency and accuracy in decision-making processes across various applications.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Microsoft Foundry
No
OpenRouter
No
Qwen3.5
No
Pricing Details
$0.042 per 1M tokens
Free Trial
No
Free Version
No
Pricing Details
$0.05 per million input tokens
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
commandline.microsoft.com/microsoft-decision-1-model-foundry/
Vendor Details
Company Name
Subquadratic
Founded
2024
Country
United States
Website
subq.ai/introducing-subq-snap