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Exa's Agent Ultra represents a significant advancement in autonomous research capabilities by utilizing a subagent swarm to exhaustively process thousands of sources for complex list-building tasks. The system demonstrates superior performance on key benchmarks like WANDR and DeepSearchQA while maintaining lower costs compared to frontier models from competitors. This development highlights the industry's shift toward specialized, high-effort API modes that optimize compute allocation across different model tiers for maximum data retrieval.

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Exa Launches Agent Ultra: A Subagent Swarm Deep Research API Built for Exhaustive List Building

MarkTechPostSeptember 26, 20264 min read

Exa has released Agent Ultra, the highest effort mode of its Exa Agent API. It coordinates subagents across thousands of sources for list building and entity enrichment. Exa reports it beats Opus 5.5, GPT-6 Astra, and Perplexity Agent on 4 benchmarks, including 81.4% soft recall on WANDR. The post Exa Launches Agent Ultra: A Subagent Swarm Deep Research API Built for Exhaustive List Building appeared first on MarkTechPost.

Exa has released Agent Ultra, the highest effort level of its Exa Agent API. It is built for research that must run to exhaustion: large list building, entity enrichment, and questions that need thousands of sources. Exa team reports that Ultra beats Opus 5.5, GPT-6 Astra, and Perplexity Agent, each at maximum effort, on 4 research benchmarks. Is it deployable? Yes, as a hosted API.…

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