https://store-images.s-microsoft.com/image/apps.19458.ee3cbb00-a358-411a-a42f-a5a8604c5921.f1ee0fb0-5aec-459f-be90-a18407b78a5e.94c96e06-d2f3-45ad-baa4-15a44b014d5d

voyage-3.5 Embedding model

by MongoDB, Inc.

Voyage model Virtual Machine

Overview

  • Text embedding model optimized for general-purpose (including multilingual) retrieval/search and AI applications. 32K context length.
voyage-3.5:

  • Outperforms OpenAI-v3-large, voyage-3, and Cohere-v4 by an average of 8.26%, 2.66%, and 1.63% respectively across domains

  • Supports embeddings of 2048, 1024, 512, and 256 dimensions

  • Offers multiple quantization formats including float, int8, uint8, and binary variants

  • Maintains a 32K-token context length at the same price point as voyage-3

  • Reduces vector database costs by up to 83% (int8, 2048) or 99% (binary, 1024) compared to OpenAI-v3-large