Models

Cohere’s Rerank Model (Details and Application)

Rerank models sort text inputs by semantic relevance to a specified query. They are often used to sort search results returned from an existing search solution. Learn more about using Rerank in the best practices guide.

Latest ModelDescriptionModalityEndpoints
rerank-v3.5A model for documents and semi-structured data (JSON). State-of-the-art performance in English and non-English languages; supports the same languages as embed-multilingual-v3.0. This model has a context length of 4096 tokensTextRerank
rerank-english-v3.0A model that allows for re-ranking English Language documents and semi-structured data (JSON). This model has a context length of 4096 tokens.TextRerank
rerank-multilingual-v3.0A model for documents and semi-structure data (JSON) that are not in English. Supports the same languages as embed-multilingual-v3.0. This model has a context length of 4096 tokens.TextRerank

For each document included in a request, Rerank combines the tokens from the query with the tokens from the document and the combined total counts toward the context limit for a single document. If the combined number of tokens from the query and a given document exceeds the model’s context length for a single document, the document will automatically get chunked and processed in multiple inferences. See our best practice guide for more info about formatting documents for the Rerank endpoint.