Perplexity launches a 190M-document retrieval test and keeps the answers private

Q2D-Web uses 69,721 agent-written queries from production traffic and accepts open-weight models for a public leaderboard.

By · Published · Updated

Primary source: X

Why it matters

Agents can only cite evidence their retrievers find. Q2D-Web gives developers a production-shaped test, while its private data leaves Perplexity controlling the scoreboard.

Perplexity launches a 190M-document retrieval test and keeps the answers private — Q2D-Web uses 69,721 agent-written queries from production traffic and accepts open-weight models for a public leaderboard.

Perplexity launched Q2D-Web on September 9th, a benchmark designed to test the retrieval systems that decide which web pages an AI agent gets to read before it writes an answer.…

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

Reader comments

Conversation for this story loads after sign-in.