Cohere Rerank 4 Fast
Cohere Rerank 4 Fast is a reranking model from Cohere designed to score and reorder search results with a 4096 token context window.
CohereFast document reranking for search pipelines
Cohere Rerank 4 Fast is a reranking model published by Cohere under the model ID rerank-v4.0-fast. It is designed to take a query and a list of candidate documents and return a relevance-ordered ranking, making it a component in retrieval-augmented generation (RAG) and semantic search pipelines. The model supports a context window of 4096 tokens and is positioned as the faster variant in the Rerank 4 family, optimized for lower latency use cases.
Reranking models like this one sit between an initial retrieval step and a final response generation step, improving result quality without requiring a full embedding or generation pass over every document. Cohere Rerank 4 Fast is well suited for applications where speed is a priority and where a large number of candidate passages need to be scored quickly. It is available as a first-party model through Cohere's API and is accessible on MindStudio without requiring separate API key management.
What Cohere Rerank 4 Fast supports
Document Reranking
Scores and reorders a list of candidate documents by relevance to a query. Returns a ranked list that can be used to improve downstream retrieval quality.
RAG Pipeline Support
Integrates as a reranking layer in retrieval-augmented generation workflows, sitting between initial retrieval and response generation to filter noise.
4096 Token Context
Accepts up to 4096 tokens of combined query and document content per reranking request.
Low-Latency Scoring
Optimized for speed as the fast variant of the Rerank 4 family, making it suitable for high-throughput or latency-sensitive search applications.
Semantic Search Integration
Works alongside vector or keyword search systems to reorder results based on semantic relevance rather than surface-level term matching.
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Get Started FreeCommon questions about Cohere Rerank 4 Fast
What is the context window for Cohere Rerank 4 Fast?
Cohere Rerank 4 Fast supports a context window of 4096 tokens, which applies to the combined length of the query and each candidate document passage.
What is the difference between Rerank 4 Fast and the standard Rerank 4?
Rerank 4 Fast is the speed-optimized variant of the Rerank 4 model family. It is designed for lower latency scenarios where throughput is a priority, while the standard variant may offer different performance trade-offs.
What type of model is Cohere Rerank 4 Fast — does it generate text?
No. Cohere Rerank 4 Fast is a reranking model, not a generative model. It takes a query and a list of documents and returns relevance scores and a ranked ordering. It does not produce new text.
What is the pricing for Cohere Rerank 4 Fast?
Pricing information is not published in the available metadata. You should refer to Cohere's official pricing page or contact Cohere directly for current pricing details.
Does Cohere Rerank 4 Fast support image or multimodal inputs?
Based on the available metadata, Cohere Rerank 4 Fast does not indicate support for image or video inputs. It is a text-based reranking model.
What is the knowledge cutoff date for Cohere Rerank 4 Fast?
A specific knowledge cutoff date is not provided in the available metadata for this model. As a reranking model rather than a generative one, it does not rely on a training knowledge cutoff in the same way language models do.
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