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 Model | Description | Modality | Endpoints |
|---|---|---|---|
rerank-v4.0-pro |
A multilingual model that allows for re-ranking English and non-english documents and semi-structured data (JSON). This is better suited for state-of-the-art quality and complex use-cases than its fast variant. |
Text | Rerank |
rerank-v4.0-fast |
A light version of rerank-v4.0-pro, this is a multilingual model that allows for re-ranking English and non-english documents and semi-structured data (JSON). This model is better suited for low latency and high throughput use-cases than its pro variant. |
Text | Rerank |
rerank-v3.5 |
A model for documents and semi-structured data (JSON). Performs well in English and non-English languages; supports the same languages as embed-multilingual-v3.0. This model has a context length of 4096 tokens | Text | Rerank |
rerank-english-v3.0 |
A model that allows for re-ranking English Language documents and semi-structured data (JSON). This model has a context length of 4096 tokens. | Text | Rerank |
rerank-multilingual-v3.0 |
A 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. |
Text | Rerank |