Scan to join WeChat groupEmbed v4.0
Embed v4.0 for semantic search, clustering and RAG knowledge-base indexing
Embed v4.0 is a Cohere embedding model for semantic search, RAG indexing, clustering and similarity workflows.
descriptionOverview
Overview
Embed v4.0 is listed in Cohere's official model documentation, with model ID embed-v4.0. Cohere's lineup focuses on enterprise RAG, retrieval augmentation, multilingual generation, embeddings and reranking.
Best for
Use Embed v4.0 for knowledge-base indexing, semantic search, clustering or cross-language retrieval. Test retrieval quality, indexing cost, refresh cadence and downstream RAG performance before production.
lightbulbUse cases
- Semantic search embeddings
- RAG knowledge-base indexing
- Clustering and similarity
- Cross-language retrieval
thumb_upStrengths
- Strong focus on enterprise retrieval and RAG
- Complete generation, embedding and reranking stack
- Useful for knowledge-base and search pipelines
- Multilingual support for global products
infoLimitations
- Results depend on retrieval pipeline design
- Embedding and reranking models are not chat generators
- Chinese and domain terminology need evaluation
- Limits depend on Cohere documentation