Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Decisions API is designed to transform both text and images into structured decisions that applications can utilize, processing inputs approximately ten times faster than the Responses API. Developers must provide a model along with shared input evidence and one or more questions that outline the evaluation criteria, after which the API delivers organized answers suitable for tasks like content classification, request routing, work prioritization, or making decisions based on defined thresholds. It accommodates three types of questions: predicate, which assesses whether a condition holds true and yields a probability ranging from 0 to 1; choice, which chooses a single value from a predetermined set and provides the associated probabilities and confidence levels; and score, which measures an input against a set of ordered rubric levels to return a probability-weighted score. The system is versatile in that it can process inputs as plain text or as user messages that include both text and images, making it effective for evaluating various scenarios such as identifying visible product damage, determining request intent, classifying document types, assessing issue severity, or evaluating answer relevance. This capability empowers developers to create more responsive and intelligent applications tailored to user needs.
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
Integrations
GPT-6 Luna
Yes
OpenAI
Yes
Python
No
Qwen3.5
No
TypeScript
No
Integrations
GPT-6 Luna
No
OpenAI
No
Python
Yes
Qwen3.5
Yes
TypeScript
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0.04 per 1M tokens
Free Trial
No
Free Version
Yes
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
OpenAI
Founded
2015
Country
United States
Website
developers.openai.com/api/docs/guides/decisions
Vendor Details
Company Name
Together AI
Founded
2022
Country
United States
Website
www.together.ai/models/tev1-4b-experimental