https://store-images.s-microsoft.com/image/apps.53494.5efaf744-84a0-4e09-a414-c775cae5097f.453e4db8-2da5-404c-84b5-5984f6bbb250.bcf17596-2b27-406d-94fb-87620f452737

voyage-4-lite Embedding Model

by MongoDB, Inc.

Text embedding model for general-purpose (incl. multilingual) retrieval and AI. 32K context length.

Text embedding models are neural networks that transform texts into numerical vectors. They are a crucial building block for semantic search/retrieval systems and retrieval-augmented generation (RAG) and are responsible for the retrieval quality.

voyage-4-lite is a lightweight, general-purpose embedding model optimized for low latency and cost. Enabled by Matryoshka learning and quantization-aware training, voyage-4-lite supports embeddings in 2048, 1024, 512, and 256 dimensions, with multiple quantization options. Learn more about voyage-4-lite here