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What is Perplexity Decider?

Perplexity Decider represents an advanced decision-making model featuring 27 billion parameters, evolved from Qwen3.8-27B, and is designed specifically for structured classification and multimodal decision-making tasks. Rather than generating freeform text, it evaluates an input state alongside a predefined decision schema to present the selected outcome along with calibrated probabilities. This model excels in making choice decisions from established categories and also handles noul decisions, assessing the probability of a yes-or-no answer. Additionally, it can analyze images in combination with text, allowing it to make well-informed decisions based on visual inputs such as screenshots. Common use cases involve routing support requests to the correct departments, like billing, technical support, or sales, and determining whether a message conveys urgency. With an overall accuracy rate of 85.71% across 11 diverse benchmarks, including FinancialPhraseBank, RAGTruth, JudgeBench, TabFact, ContractNLI, Circa, Belebele, and TruthfulQA binary, Perplexity Decider illustrates remarkable versatility and effectiveness in various decision-making environments. This significant accuracy level not only highlights the model's capabilities but also points to its potential for improving automated systems that require a nuanced understanding of both text and images, paving the way for future advancements in decision-making technologies.

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

Perplexity Decisions API
Qwen3.8-27B

Integrations Supported

Claude Code
Model Context Protocol (MCP)
Parallel

API Availability

Has API

API Availability

Has API

Pricing Information

Free
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

Perplexity

Date Founded

2022

Company Location

United States

Company Website

huggingface.co/perplexity-ai/pplx-decider-v1-27b

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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