Parallel multi-model queries
Runs one query across three models available on Perplexity at the same time, reducing the need to compare responses manually.
Model Council is a multi-model research feature from Perplexity that sends the same query to several AI models and returns one synthesized answer. The blog post says it is designed to help users compare model outputs without manually checking each model one by one.
When Model Council is selected in the main Perplexity interface, the query runs across three models available on Perplexity, such as Claude Opus 4.6, GPT 5.2, and Gemini 3.0. A synthesizer model then reviews the results, resolves conflicts where possible, and highlights where the models agree or differ.
Runs one query across three models available on Perplexity at the same time, reducing the need to compare responses manually.
Uses a synthesizer model to review outputs and produce a single combined answer.
Shows where model outputs agree and where they differ, which helps readers judge confidence and spot uncertainty.
Lets users select Model Council from the main Perplexity interface rather than switching between separate tools.
Supports research and decision-making workflows where different model strengths can surface different angles on the same question.
Use Model Council to compare multiple model perspectives on stocks, markets, or other financially sensitive topics where a single answer may miss important nuance.
Ask it when evaluating major purchases, career choices, or strategic tradeoffs and you want several reasoning approaches in one pass.
Use it to generate ideas for gifts, travel plans, or content when you want varied suggestions from different model strengths.
Use it to cross-check facts or claims when accuracy matters and you want to know whether several models converge on the same answer.
Model Council is available to Perplexity Max subscribers on the web, with mobile app support coming soon.
The feature runs the same query across three models available on Perplexity, then uses a synthesizer model to combine the outputs into one answer.
Perplexity says Model Council is useful when accuracy and perspective matter, including research, complex decisions, creative brainstorming, and verification.
The source notes that Model Council runs in the main Perplexity interface; it does not describe a separate setup flow or additional configuration steps.