https://store-images.s-microsoft.com/image/apps.53494.b2afd209-3470-415c-9b55-d2c8d65d3fd1.e08dbfff-5513-44d1-a414-8241d1b3203d.24e4c37a-a874-469b-81b6-37eda62ca72d

voyage-4-large 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-large is a state-of-the-art general-purpose and multilingual embedding optimized for retrieval quality. Enabled by Matryoshka learning and quantization-aware training, voyage-4-large supports embeddings in 2048, 1024, 512, and 256 dimensions, with multiple quantization options. Learn more about voyage-4-large here.