Model Releases
We're introducing Q2D-Web (Query2Doc-Web), a benchmark and public leaderboard for evaluating retrieval in agentic RAG systems. Q2D-Web tests…
We're introducing Q2D-Web (Query2Doc-Web), a benchmark and public leaderboard for evaluating retrieval in agentic RAG systems. Q2D-Web tests how embedding models perform on large-scale web search usin
We're introducing Q2D-Web (Query2Doc-Web), a benchmark and public leaderboard for evaluating retrieval in agentic RAG systems. Q2D-Web tests how embedding models perform on large-scale web search using agent-reformulated search queries. Read more: https://www.perplexity.ai/hub/blog/q2d-web
Related
- LocalSearchBench: Benchmarking Agentic Search in Real-World Local Life Services
- TeleEmbedBench: A Multi-Corpus Embedding Benchmark for RAG in Telecommunications
- Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems
- Rethinking Agentic Search with Pi-Serini: Is Lexical Retrieval Sufficient?
Source: Perplexity (X) | 2026-09-09