Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Strands Decider is a compact and swift decision-making model, known as a System One model, tailored for agentic AI applications. In contrast to a language model that produces random text, this model selects from a set of predefined options, responds to yes-or-no inquiries, or assesses inputs using an ordered scale. Each decision made by the Strands Decider is accompanied by a calibrated confidence score, enabling the efficient processing of routine decisions while allowing uncertain cases to be escalated to either a larger model or a human for further analysis. The initial iteration of this model, strands-decider-2B, comprises 1.9 billion parameters and is built upon the Qwen3.5-2B-Base architecture, featuring a streamlined pointer head in place of its language-modeling component. It performs evaluations in a single forward pass, eliminating the need for text generation or a decoding loop. Supported types of decisions encompass choice selections, noul for probability assessments, and score for evaluating ordered scales. This model is engineered for a variety of applications, including model routing, selecting tools, verifying tool arguments, triaging requests, establishing grounding and safety measures, classifying policies, and providing economical evaluations, thereby enhancing its utility in diverse AI workflows.
Description
Tev1 is a rapid decision-making and classification model developed by Together AI, which has been fine-tuned from Qwen3.5 4B. Its user-friendly interface allows for the input of a state, a question, and between 2 to 24 labeled choices, enabling the model to output a single letter that can be mapped back to a semantic key by software. This design is particularly beneficial for various production tasks, such as managing support ticket routing, assessing automated returns, enforcing policy guidelines, sentiment analysis, document categorization, and integrating precise decision-making steps into larger agent workflows. With a parameter count of 4.7B and a 32.8K-token context window, the model operates with non-thinking generation to ensure fast and reliable classification. It has been trained on a diverse set of 37,840 examples covering areas such as intent detection, boolean comprehension, sentiment evaluation, policy application, as well as categorizing news and academic papers. The recommended configuration suggests using a temperature setting of 0 along with a minimal output budget, ensuring that the responses are both consistent and straightforward to interpret. In summary, Tev1 stands out as a versatile tool that efficiently addresses a wide range of classification needs.
API Access
Has API
Yes
API Access
Has API
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
$0.04 per 1M tokens
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
Yes
Linux
Yes
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
Strands Labs
Country
United States
Website
github.com/strands-labs/strands-decider
Vendor Details
Company Name
Together AI
Founded
2022
Country
United States
Website
www.together.ai/models/tev1-4b-experimental