Cohere offers a variety of Command models that cover many different use cases—well suited to text generation, translation, and chat applications.
Cohere-Embeddings and Re-ranking Models offer high-performance tools for building semantic search, recommendation systems, and retrieval-augmented generation (RAG) pipelines. Cohere’s multilingual embedding models generate dense vector representations of text that capture semantic similarity across languages, making them ideal for global-scale applications. Their re-ranking models further enhance search quality by reordering retrieved results based on contextual relevance, improving precision in top-k retrieval tasks. Together, they form a powerful stack for building intelligent, LLM-enhanced search systems.
Provisioning Platforms:
MOHARA will be assessing Cohere pending further benchmarking against our use-case requirements.