# Q2D-Web: Evaluating First-Stage Retrievers at Scale

**URL:** <https://community.perplexity.ai/t/q2d-web-evaluating-first-stage-retrievers-at-scale/6052>\
**Category:** Announcements\
**Tags:** api\
**Created:** [September 9, 2026, 9:18pm UTC](https://community.perplexity.ai/t/q2d-web-evaluating-first-stage-retrievers-at-scale/6052 "2026-09-09T21:18:09Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![pplx-announcements](https://avatars.discourse-cdn.com/v4/letter/p/c37758/32.png) [@pplx-announcements](https://community.perplexity.ai/u/pplx-announcements)\
**Post date:** [September 9, 2026, 9:18pm UTC](https://community.perplexity.ai/t/q2d-web-evaluating-first-stage-retrievers-at-scale/6052/1 "2026-09-09T21:18:09Z")

</div>

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://pplx.ai/blog/dq2d-web](https://pplx.ai/blog/dq2d-web)