LLM Reference

Rerank Models by Cohere

4 models2024Up to 4k ctx

About

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.

Current Variants

Use-when guidance is derived from seed capabilities, context, release, and replacement fields.

4 in view

Use when the workload needs 4k context.

2024-044k context

Use when the workload needs 4k context.

2024-044k context

Use when the workload needs 512 context.

2024-04512 context

Use when the workload needs 512 context.

2024-04512 context

Release Timeline

1 release group
2024-04
4 current
Current
Current
Current
Current

Specifications(4 models)

Rerank model specifications comparison
ModelReleasedContext
Rerank English V32024-044k
Rerank Multilingual V32024-044k
Rerank English V22024-04512
Rerank Multilingual V22024-04512

Available From(1 provider)

Frequently Asked Questions

What is Rerank used for?
Rerank models sort text inputs by semantic relevance to a specified query.
How does Rerank compare to Command?
Rerank by Cohere is strongest where you need its listed use cases, while Command by Cohere is the closest related family to check for multilingual. Rerank has 4 listed variants and reaches up to 4k context, while Command reaches up to 256k context, so compare the specs and pricing tables before choosing a production model.
Which Rerank model should I use?
If price is the main constraint, use the pricing table first because Rerank does not have complete provider pricing in the local data. For the most capable/latest local choice, evaluate Rerank English V3 with 4k context.

Models(4)