Closing the Oracle Gap for Your Agents

Mixedbread Search v3 is presented as a retrieval system intended to reduce the “gap to oracle,” or the performance difference between systems using retrieved evidence and those given the correct documents directly, across agentic research and enterprise workflows. On BrowseComp-Plus, a multi-hop web research benchmark, it reportedly ranks first under both standard and document-access retrieval scaffolds, achieving 90.48% accuracy in the stronger setting versus a 93.5% oracle score. On MADQA, which evaluates question answering over heterogeneous and multimodal PDF collections, Mixedbread-supported systems reportedly lead relevant leaderboard categories, with a Gemini 3 Pro one-shot system reaching 88.2% accuracy and a Distyl AI system called Button reaching 91.7%. In OfficeQA-Pro, a financial-document benchmark tested with OpenAI Codex, Mixedbread retrieval reached 64.42% correctness, within 0.99 points of the oracle configuration, while reducing latency and tool calls relative to a corpus-based baseline. The company notes that retrieval remains only one source of failure in difficult knowledge-work tasks, alongside ambiguity, missing evidence, and reasoning limitations, and offers its search service through an API designed to manage multimodal ingestion, indexing, and retrieval without requiring users to configure chunking, embeddings, vector databases, or reranking.

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