pplx-decider-v1.2

Name: pplx-decider-v1.2
Author: Perplexity Labs

Released

2026-10-16

Last refreshed

2026-10-17

Status

Researched today

Open sourceCommercial use: permittedMultimodalRAGAgentsLong contextVisionJSON / Tool useAgent

Perplexity Labs releases · 7 in the last 12 months · this family litChangelog →

Specifications

Family: PPLX Decider
Released: 2026-10-16
Context: 256K
Parameters: 27B
Openness: Open source
License: Apache 2.0OSI-approvedPermitted
Weights: Available
Code: Unknown
Training: Fine-tuned

Created by

Perplexity Labs

Developing AI for complex problem-solving.

San Francisco, California, United States

Founded 2022

Website

Pricing

Output / 1M

Free

Input / 1M

$0.020

Cheapest of 3 routes · OpenRouter

Providers(3)

Perplexity Labs OpenRouter Vercel AI Gateway

View 3 provider routes

Links

Website HuggingFace

About

pplx-decider-v1.2 is Perplexity's 27B multimodal decision model, released 2026-10-16 as the successor to pplx-decider-v1.1-27b on the Qwen3.8-27B backbone. Instead of generating text it returns probabilities. It reads a state of text, JSON, or images (PNG, JPEG, or WebP data URLs, up to 8 per question) and answers 1 to 128 named questions per request: noul for yes/no, choice with up to 255 options, or score with up to 10 levels. All questions in a request are answered together in one pass. It is called via POST https://api.perplexity.ai/v1/decisions with model pplx-decider-v1.2 or the alias pplx-decider-latest. Input must stay under 256K tokens.

Providers(3)

Compare all 3

Compare API pricing across 3 tracked provider routes for input and output tokens, batch, and cached reads when available.

Provider	Input / 1M	Output / 1M	Route
OpenRouter	$0.020	Free	Serverless
Perplexity Labs	$0.020	Free	Serverless
Vercel AI Gateway	$0.020	Free	Serverless

Capabilities

VisionMultimodalStructured Outputs

Benchmark peer barsfor RAG

No task-mapped benchmark peers are available for this model yet.

Benchmark scores(1)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.