Another leaderboard win for Nemotron 🏆
Nemotron 3 Embed 8B ranks #1 for combined nDCG@10 on the Q2D-Web benchmark, tested across 190M web documents and nearly 70K agent-reformulated queries in 10 languages.
Shoutout to @perplexity_ai for putting it together. https://t.co/cYp3Y3l67h
benchmark — A standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
embedding — A list of numbers representing a piece of text's meaning, so that similar meanings end up numerically close and can be searched.
RAG — Retrieval-augmented generation — fetching relevant documents first and pasting them into the model's context so it answers from your data instead of memory.
Why it matters
A top embeddingA list of numbers representing a piece of text's meaning, so that similar meanings end up numerically close and can be searched.Full definition →-model result on a large, multilingual, AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition →-query benchmarkA standard public test set for comparing AI models — the shared scoreboards behind every "model X beats model Y" claim.Full definition → gives a concrete data point for choosing retrieval models in agentic search and RAGRetrieval-augmented generation — fetching relevant documents first and pasting them into the model's context so it answers from your data instead of memory.Full definition → pipelines.
