voyage context-4 AI Foundry
MongoDB, Inc. · Software Development
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 9 captures on record
What the publisher says
As described on Microsoft Marketplace.
Contextualized chunk embedding models are novel neural networks that encode not only the chunk’s own content, but also capture the contextual information from the full document 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-context-4 is a next-generation contextualized chunk embedding model that delivers higher retrieval accuracy, more effective long-document support, and built-in auto-chunking, with full support for both overlapping and non-overlapping chunks. Users can submit a full document as a single string and let the backend chunk it automatically, with chunk text returned in the response for inspection and storage. voyage-context-4 delivers approximately 1.4 NDCG@10 points higher chunk-retrieval quality than voyage-context-3 and approximately 8.4 NDCG@10 points higher than cohere-embed-v4.0 across chunk retrieval benchmarks, while removing the 32K-token ceiling through extended context handling via backend partitioning. Enabled by Matryoshka learning and quantization-aware training, voyage-context-4 supports embeddings in 2048, 1024, 512, and 256 dimensions, with multiple quantization options. Learn more about voyage-context-4 here: https://blog.voyageai.com/2026/06/29/voyage-context-4/
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- FedRAMP AuthorizedConfirmed95%, domain-verifiedMongoDB Atlas for Government is FedRAMP Authorized at Moderate impact (domain match)FedRAMP Marketplaceregistry recordas observed 2026-08-27
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External enrichment · as of 2026-08-29
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