Nemotron-3.5-Rerank-8B-BF16 is an 8B-parameter reranking model from NVIDIA that scores the relevance of documents to a query, for reordering the candidates retrieved by an embedding model. It supports long inputs up to 32k tokens and pairs naturally with the Nemotron-3.5-Embed models in multilingual RAG pipelines.
Scores appear here when an evaluation matches this exact model.
Llama Nemotron Rerank VL 1B V2 is a 1.7B multimodal reranking model from NVIDIA. It evaluates the relevance of document images and text against user queries, designed for vision RAG...
The llama-nemotron-rerank-vl-1b-v2 is a 1.7B parameter multimodal reranking model designed to evaluate and order the relevance of document images and text against specific user queries. It excels at…