Voyage multimodal 3.5
Multimodal embedding model that vectorizes interleaved text, images, and videos into a shared vector space for retrieval tasks. Uses a single transformer encoder for all modalities, eliminating the modality gap. Supports document screenshots, PDFs, slides, figures, tables, and video frames. Context window of 32,000 tokens with Matryoshka embeddings at 256, 512, 1024, and 2048 dimensions.
- Type
- Multimodal
- Weights
- Closed
Model hub
voyageai/voyage-multimodal-3.5
- Repo
- voyageai/voyage-multimodal-3.5
- Access
- Public
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About Voyage AI
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Voyage AI provides best-in-class embedding models and rerankers for search and retrieval over unstructured data, used to power retrieval-augmented generation (RAG) and AI applications. It offers general-purpose, domain-specific (finance, legal, code) and company-specific fine-tuned models. Founded in 2023 and based in Palo Alto, the company was acquired by MongoDB, Inc. in February 2025 and now operates as a MongoDB subsidiary.