Perplexity Sonar API
Search-grounded language model API with live citations
Perplexity Sonar API is profiled here as a LLM tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
Description
Sonar is the developer API from Perplexity, the answer-engine company founded in 2022 by Aravind Srinivas, Denis Yarats, Johnny Ho, and Andy Konwinski. It runs a query against the live web, then returns a grounded answer with source citations, so applications can answer current questions without maintaining their own retrieval stack. The endpoint follows the OpenAI chat format, and reasoning and deep-research tiers handle heavier analytical work. The same retrieval stack powers Perplexity's consumer answer engine, which gives the API production-tested grounding behind a simple interface. Filters for domain and recency let developers constrain which sources the model is allowed to cite.
Key Capabilities:
Web-grounded answers with inline source citations
OpenAI-compatible chat completions interface
Sonar Pro for higher-difficulty queries needing deeper sources
Reasoning and deep-research models for multi-step investigation
Domain and recency filters to constrain the search scope
Usage-based token and request pricing
Alternative tools
- AI21 Labs
Hybrid Mamba-Transformer models for enterprise applications
- Instructor
Structured outputs from LLMs with validation built in
- Tecton
Enterprise feature platform for real-time machine learning
- Feast
Open-source feature store for production machine learning
- Snowflake
Cloud data platform with built-in AI services
- Airbyte
Open-source data integration with hundreds of connectors