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
- Kong AI Gateway
AI traffic governance built on the Kong gateway
- Eden AI
One API for many AI models across providers and modalities
- Reka
Multimodal models that reason across text, image, and video
- Moonshot AI
Open-weight Kimi models tuned for agentic and coding tasks
- xAI Grok
Grok model family with real-time search through one API
- LLM Guard
Open-source security toolkit for LLM interactions