NVIDIA Opens the Retrieval Layer: Embed, Rerank, and Parse Decide What Agents Know

What an agent knows is decided before it answers. The embedding search that surfaces candidate documents, the reranker that orders them, and the parser that turns a page image into usable text all sit upstream of the model doing the reasoning. On October 21, NVIDIA announced new Nemotron Retriever models for those three jobs and published the weights behind them, open and commercially available: Nemotron 3.5 Embed in three checkpoints, Nemotron 3.5 Rerank, and Nemotron 3.5 Parse. The week’s headline model, Nemotron 3.5 Super VL , shipped six days earlier. These are the transaction layer beneath it: the machinery that decides which evidence reaches an agent’s context, and how many tokens the agent burns finding it.

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