NVIDIA Expands Nemotron Retriever With Models Aimed at Cutting Agent Search Tokens
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NVIDIA has expanded its Nemotron Retriever collection with new models for multimodal search, reranking, and document parsing, reporting that reranking cut agent inference tokens per query by about 13% to 14% in its evaluations. The models are designed to help agents find relevant evidence across text and visually rich documents, potentially reducing repeated searches before an agent can answer. (NVIDIA’s model overview)
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