Cohere Embed
Hosted multilingual embedding model with separate query and document modes.
Overview
Cohere Embed is a hosted embedding model that distinguishes the query from the document being indexed, and supports a hundred languages in one model. It solves the asymmetry problem explicitly: a question and a passage are not the same kind of text, and encoding them with the same mode is a compromise. It exists because multilingual retrieval otherwise means either a separate model per language or one model doing all of them badly.
Technology Graph
How Cohere Embed connects to the rest of the stack.
Applied to
- AI Search application Applications Cohere Embed used for AI Search High ✓ source
- RAG technique Techniques Cohere Embed used for RAG High ✓ source
Tools
Software that implements or integrates with Cohere Embed.
LLM Frameworks
Alternatives
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BGE
model
An alternative to Cohere Embed · source
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E5
model
An alternative to Cohere Embed · source
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GTE
model
An alternative to Cohere Embed · source
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Instructor
model
An alternative to Cohere Embed · source
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Jina Embeddings
model
An alternative to Cohere Embed · source
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Nomic Embed
model
An alternative to Cohere Embed · source
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OpenAI Text Embedding 3
model
An alternative to Cohere Embed · source
Comparisons
Side-by-side breakdowns with the alternatives above.