Q2D-Web Benchmark Evaluates Retrieval Models Across 190 Million Documents
September 10, 2026
Q2D-Web provides a large-scale retrieval benchmark utilizing 190 million documents across ten different languages. It is designed to test the performance of retrieval-augmented generation (RAG) systems on real-world web search queries.
HOW THIS AFFECTS YOU
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builderUse this to benchmark your RAG pipelines against diverse, multilingual web-scale data.
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researcherThis offers a more rigorous evaluation for multilingual retrieval architectures.