Voyage Multimodal 3.5
Next-generation multimodal embedding model built for retrieval over text, images, and videos, supporting Matryoshka embeddings with 4.56% higher accuracy than Cohere Embed v4 on visual document retrieval.
About this tool
Overview
voyage-multimodal-3.5 extends Voyage's industry-leading multimodal capabilities to video retrieval. This represents a significant advancement in their multimodal embedding offerings, announced in January 2026.
Key Features
Video Support
voyage-multimodal-3.5 is a next-generation multimodal embedding model built for retrieval over text, images, and videos, with explicit support for video frames. It's the first production-grade video embedding model to support Matryoshka embeddings for flexible dimensionality.
Multimodal Capabilities
Embeds interleaved text and images including:
- Screenshots
- PDFs
- Tables
- Figures
- Slides
- Video frames
API Access
Voyage multimodal embeddings are accessible in:
- Python: Through the voyageai package using voyageai.Client.multimodal_embed()
- TypeScript: Through the Voyage TypeScript Library
Performance
voyage-multimodal-3.5 attains:
- 4.56% higher retrieval accuracy than Cohere Embed v4 across 15 visual document retrieval datasets
- 4.65% higher than Google Multimodal Embedding 001 across 3 video retrieval datasets
Availability
The models are newly available on:
- MongoDB Atlas
- Google Cloud Platform (GCP)
- Amazon Web Services (AWS)
- Microsoft Azure
Pricing
API-based pricing available through Voyage AI.
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