AI model by Cohere
Cohere Rerank 4 for business
Cohere's multilingual rerank models, which sort search results by relevance, in a best-quality Pro version and a low-latency Fast version.
- Reviewed on September 24, 2026
- Cohere
Capability tiersRelative, not benchmarks
Key facts about Cohere Rerank 4
- Model ID at review
- rerank-v4.0-pro, rerank-v4.0-fast
- Provider
- Cohere
- Main category
- Embeddings
- Open weights
- No, available as a hosted service
- Last reviewed
- September 24, 2026
Fit
Where it fits and where it does not
Good at
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Improving the order of search results.
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Raising answer quality in RAG assistants.
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Working on top of any existing search.
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Multilingual queries and documents.
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A choice between quality and speed.
Not the right choice for
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Searching a whole collection on its own.
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Generating answers.
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Documents longer than its 32K token window per item.
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Self-hosting.
Use cases
Business use cases we would use it for
Better RAG answers
Product search
Our notes
When we would choose it
Rerank 4 is Cohere's current rerank line, superseding Rerank 3.5. It comes in two versions: rerank-v4.0-pro for the best quality and rerank-v4.0-fast for low latency. Both are multilingual, with a 32K token context.
A reranker takes the top results from a first search, whether keyword, embedding or both, and sorts them by how well each one answers the query. It is a small addition that often gives one of the largest improvements in a knowledge assistant, because the language model can only answer from what reaches it.
Rerank works with any first-stage search. You do not need to change your embedding model or your database to add it. That makes it one of the cheapest upgrades we suggest for existing assistants that sometimes miss the right passage.
We would measure the gain directly: take a set of real questions, record how often the right passage appears in the top three results with and without reranking, and weigh that against the added delay and cost.
For live search where every millisecond counts, start with the Fast version. For back-office research tools, the Pro version is usually worth the extra time. See Cohere Embed and embedding models.
Before you commit
Things to check before you commit
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Latency
Rerank adds a step. Use the Fast version for live search.
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Gain
Measure how often the right passage reaches the top three, before and after.
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Input size
The context is 32K tokens. Chunk long documents.
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Older versions
Rerank 4 supersedes v3.5. Test the switch.
Alternatives
Models to compare it with
Cohere Embed v4
Cohere's multimodal embedding model for enterprise search, embedding text, images and mixed documents, with flexible vector sizes and long inputs.
Voyage 4
Voyage AI's current embedding series, now part of MongoDB, with large, standard and lite models that share one embedding space.
text-embedding-3-small
OpenAI's efficient, lowest-cost embedding model, with 1,536-dimension vectors for search, retrieval and similarity at scale.
Keep exploring
Solutions, services and guides
Related services
View all related services- RAG knowledge assistants Assistants that answer questions from your own documents and show where each answer came from.
- AI Product Development AI agents, knowledge assistants, copilots and document automation built into the way your team already works.
- MCP integration Connect AI assistants to your CRM, files, databases and tools through Model Context Protocol servers, with safe permissions.
Solutions
View all solutions- Knowledge assistant (RAG) Ask a question in plain words and get an answer from your own documents, with links to the sources.
- Internal help desk assistant An assistant in Slack or Teams that answers policy and how-to questions from your handbooks and opens tickets when needed.
- AI support agent An assistant that answers routine questions from your own content, checks orders and hands anything else to a person.
Industries
View all industries- Healthcare Patient booking, intake forms, internal knowledge assistants and admin automation for clinics and care providers.
- Legal Contract review assistants, knowledge search, intake and document automation for law firms and in-house legal teams.
- Professional services Client portals, proposal drafting, knowledge assistants and internal tools for consultancies, agencies and firms.
Guides and articles
View all guides and articlesMCP servers
View all mcp servers- Obsidian A community MCP server that lets AI list, read, search, edit, append to and delete notes in an Obsidian vault through the Local REST API plugin.
- Readwise Readwise's official hosted MCP server lets AI search and manage your reading highlights and Reader documents.
- Confluence Atlassian's official Rovo MCP server lets AI search and read Confluence spaces and pages, create and edit content and add comments and labels.
- Memory The MCP project's Memory reference server gives AI a local knowledge graph to store people, things and facts and recall them later.
- Knowledge and memory Servers that give AI long-term memory or access to knowledge bases, wikis and personal notes.
- Box Box's official MCP server lets AI search and read files, ask questions across documents with Box AI, extract data and upload files.
Glossary terms
View all glossary terms- RAG RAG, or retrieval-augmented generation, is a method where an AI system first finds relevant passages in your documents, then answers using only those passages.
- Natural language processing Natural language processing is the field of AI that deals with understanding and generating human language, in text or speech.
- Semantic search Semantic search finds results by meaning rather than exact words, so a search for "reset my login" can find an article titled "Forgot your password".
- Chatbot A chatbot is software that holds a conversation with people through text or voice, answering questions or completing simple tasks.
- Embeddings Embeddings are lists of numbers that represent the meaning of text or images, so software can find items that are similar in meaning.
- Vector database A vector database stores embeddings, lists of numbers that represent meaning, and quickly finds the ones most similar to a query.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
It reorders search results by relevance to the query, so the best passages reach the top.
Pro for the best quality, Fast for low latency in live search.
No. Rerank works on top of any first-stage search.