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What is Tev1?

Tev1 is an advanced model designed for quick decision-making and classification, created by Together AI and fine-tuned from Qwen3.5 4B. It features an intuitive interface that allows users to enter a state, pose a question, and select from 2 to 24 labeled options, leading to an output of a single letter that corresponds to a semantic key via software. This innovative structure is particularly advantageous for diverse production tasks, including the routing of support tickets, evaluating automated returns, implementing policy guidelines, conducting sentiment analysis, categorizing documents, and embedding precise decision-making within extensive agent workflows. With its impressive 4.7B parameter count and a context window of 32.8K tokens, Tev1 leverages non-thinking generation to deliver swift and dependable classifications. The model has been honed using a broad collection of 37,840 examples that encompass intent detection, boolean comprehension, sentiment evaluation, policy enforcement, and the categorization of news articles and academic research. For optimal performance, it is recommended to set the temperature to 0 and maintain a low output budget, which ensures that the results remain both consistent and easy to understand. Furthermore, Tev1 is recognized as a highly adaptable tool that meets a variety of classification requirements effectively and efficiently. Overall, its capabilities make it an essential asset in any decision-making framework.

What is Parallel Decisions API?

The Parallel Decisions API serves as a web-based classification solution tailored for developers engaged in software creation, data process improvement, and workflow development for AI agents. When a user submits a request, it comprises a specific context accompanied by one or more questions, and the API responds with structured answers that include probabilities and citations from pertinent online sources. This feature enables the grouping of several questions under a single context in one request, which supports various use cases like vendor evaluations, lead management, compliance assessments, content moderation, and the formulation of operational guidelines for agents. By harnessing real-time web data, it can assess facts that may have changed since a model's last training session. Developers can interact with the API through a RESTful endpoint using an API key or by employing the web_decisions tool via Parallel's MCP server. To aid testing and integration, a hosted playground along with detailed documentation is provided for user ease. Additionally, this API enhances decision-making for developers by supplying current information that boosts the dependability of their applications, ultimately leading to more accurate outcomes in diverse scenarios. Through this capability, developers are equipped to create more robust and adaptive software solutions.

Media

Media

Integrations Supported

Python
Qwen3.5
TypeScript

Integrations Supported

Claude Code
Model Context Protocol (MCP)
Parallel

API Availability

Has API

API Availability

Has API

Pricing Information

$0.04 per 1M tokens
Free Version

Pricing Information

$0.001/request
$0.001 per API request; a request can include up to 100 questions.
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Together AI

Date Founded

2022

Company Location

United States

Company Website

www.together.ai/models/tev1-4b-experimental

Company Facts

Organization Name

Parallel

Date Founded

2023

Company Location

United States

Company Website

platform.parallel.ai/play/decisions

Categories and Features

AI Decision Models

Not specified

Categories and Features

AI Decision Models

Not specified

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