Sonar Deep Research
by Perplexity
Sonar Deep Research is a research-focused model designed for multi-step retrieval, synthesis, and reasoning across complex topics. It autonomously searches, reads, and evaluates sources, refining its approach as it gathers information. This enables comprehensive report generation across domains like finance, technology, health, and current events. Notes on Pricing ([Source](https://docs.perplexity.ai/guides/pricing#detailed-pricing-breakdown-for-sonar-deep-research)) - Input tokens comprise of Prompt tokens (user prompt) + Citation tokens (these are processed tokens from running searches) - Deep Research runs multiple searches to conduct exhaustive research. Searches are priced at $5/1000 searches. A request that does 30 searches will cost $0.15 in this step. - Reasoning is a distinct step in Deep Research since it does extensive automated reasoning through all the material it gathers during its research phase. Reasoning tokens here are a bit different than the CoTs in the answer - these are tokens that we use to reason through the research material prior to generating the outputs via the CoTs. Reasoning tokens are priced at $3/1M tokens
Specifications
Technical details and pricing.
Benchmarks
7 benchmark scores from Artificial Analysis.
Composite Indices
Intelligence, Coding, Math
Standard Benchmarks
Academic and industry benchmarks
Frequently Asked Questions
What is Sonar Deep Research good for?
Use Sonar Deep Research for everyday tasks like writing, summarizing, brainstorming, and getting clear explanations.
How much does Sonar Deep Research cost?
Pricing is based on usage. Current rates are $1.00/1M tokens for input and $1.00/1M tokens for output.
Can I try Sonar Deep Research for free?
Yes. You can start a chat instantly and test the model before deciding on a plan.
Does Sonar Deep Research support images or audio?
Sonar Deep Research focuses on text-based tasks.
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Benchmarks and pricing are sourced from Artificial Analysis where available. OpenRouter specs are used as a fallback.