Definition
Cohere Embed-v3 is a state-of-the-art text embedding model designed specifically for RAG and semantic search, featuring multi-modal understanding of document quality and support for compressed vector formats (int8, binary). It utilizes specialized input types—such as 'search_query' and 'search_document'—to bridge the asymmetric gap between short user questions and long-form context retrieval.
A vectorization engine for measuring semantic similarity, distinct from Cohere's generative 'Command' models.
"A high-resolution industrial scanner that converts diverse documents into hyper-efficient, searchable barcodes that retain deep meaning even when shrunken."
Conceptual Overview
Cohere Embed-v3 is a state-of-the-art text embedding model designed specifically for RAG and semantic search, featuring multi-modal understanding of document quality and support for compressed vector formats (int8, binary). It utilizes specialized input types—such as 'search_query' and 'search_document'—to bridge the asymmetric gap between short user questions and long-form context retrieval.
Disambiguation
A vectorization engine for measuring semantic similarity, distinct from Cohere's generative 'Command' models.
Visual Analog
A high-resolution industrial scanner that converts diverse documents into hyper-efficient, searchable barcodes that retain deep meaning even when shrunken.