Command A is a highly efficient generative model that excels at agentic and multilingual use cases.
Embed 4 transforms texts and images into numerical vectors
Cohere’s Rerank 3.5 provides a significant boost to the relevancy of search results. This AI model, also known as a crossencoder, precisely sorts lists of documents according to their semantic similarity to a provided query. This allows information retrieval systems to go beyond keyword search and
Cohere Embed English is the market's leading text representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering.
Cohere Embed Multilingual is the market's leading text representation model used for semantic search, retrieval-augmented generation (RAG), classification, and clustering.
Command R+ is a state-of-the-art RAG-optimized model designed to tackle enterprise-grade workloads.
Command R is a scalable generative model targeting RAG and Tool Use to enable production-scale AI for enterprise.
Cohere Rerank English is the market’s leading reranking model used for semantic search and retrievalaugmented generation (RAG). Rerank enables you to significantly improve search quality by augmenting traditional keyword based search systems with a semanticbased reranking system which can context
Cohere Rerank Multilingual is the market’s leading reranking model used for semantic search and retrievalaugmented generation (RAG). Rerank Multilingual supports 100+ languages and can be used to search within a language (e.g., search with a French query on French documents) and across languages (e
Command R+ is a state-of-the-art RAG-optimized model designed to tackle enterprise-grade workloads.
Command R is a scalable generative model targeting RAG and Tool Use to enable production-scale AI for enterprise.