sonar

Sonar is a specialized model from Perplexity designed for developers who need to implement reliable, RAG-driven question-and-answer workflows without the latency or cost overhead of massive frontier models. Unlike general-purpose LLMs that often struggle with hallucinations, Sonar is optimized for groundedness, now featuring native citation support and customizable source parameters. This makes it particularly effective for building search-augmented applications, internal knowledge bases, or customer support bots where factual accuracy is non-negotiable. For integration, it offers a high context window of 127k tokens, allowing for extensive document ingestion during the retrieval phase. If your project requires a balance between high-speed inference and verifiable output, Sonar provides a more efficient alternative to larger, more expensive models while maintaining a high standard of information integrity through its unique source-control capabilities.