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High performance text reranking model. Typically used as the second stage in two-stage retrieval pipelines.
Max Seq. Length:Number of tokens the model
can process at once.


Good reranking model, consumes both a query and a list of documents to be ranked in relevance against the query. Is a closed source model that can be used via Cohere’s API.

Reranking models are designed to provide superior accuracy over retriever models but are much slower — so this model should not be used with more than a few hundred documents. Due to the slowness of rerankers, we recommend using them in a two-stage retrieval system, ie use a retrieval to pull in a smaller number of documents from a larger database and then rerank the smaller number of documents using a reranker.

Using the Model



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