- Version v1.0.1
- Sold by Voyage AI
General-purpose text embedding model designed for general semantic retrieval tasks. 16K context length.
Voyage AI builds embedding models, customized for your domain and company, for better retrieval and search quality.
General-purpose text embedding model designed for general semantic retrieval tasks. 16K context length.
Text embedding model optimized for code retrieval and AI applications. 16K context length.
General-purpose reranker optimized for both latency and quality. Context length: 4K for queries & documents with up to 1K for queries.
Rich multimodal embedding model that can vectorize interleaved text and content-rich images. 32K context length.
State-of-the-art text embedding model with the best general-purpose and multilingual retrieval quality. 32K context length.
Text embedding model optimized for multilingual retrieval and AI applications. 32K context length.
General-purpose text embedding model optimized for a balance between cost, latency, and retrieval quality. 4K context length.
Text embedding model optimized for general-purpose (including multilingual) retrieval/search and AI applications. 32K context length.
Text embedding model optimized for legal retrieval and AI applications. Tops the MTEB leaderboard for legal retrieval. 16K context length.
General-purpose reranker optimized for quality with multilingual support. Context length: 16K for queries & documents (4K for queries).
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