Perplexity: Sonar

Perplexity Sonar is an AI model capable of processing both text and image inputs within a substantial context length of 127,072 tokens. It excels in handling diverse modalities but lacks support for reasoning or structured output generation. Although it does not offer direct tool integration, its comprehensive context length makes it suitable for complex tasks requiring extensive input. Given its benchmark blended score of 14.3 across a single independent benchmark, Sonar might be more appropriate for users who prioritize broader functionality and are willing to pay the price point of $1.0 per million input and output tokens. Its performance is robust, though less comprehensive compared to models with higher coverage scores; hence it may not be the top choice for those seeking specialized or highly optimized solutions.