Jina Embeddings v5 Omni Nano by Jina AI — 768D
1.04B-parameter compact multimodal omni embedding model accepting text, images, video, and audio. Shared vector space with text-only v5-text-nano. 768-dim embeddings with Matryoshka truncation. Supports retrieval, classification, clustering, and text-matching tasks. Optimized for efficiency.
At a glance
Modalities
Dimensions
768
Max tokens
8K
Parameters
1.04B
Price / 1M tokens
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Type
Matryoshka dimensions
Output types
Language support
Details
| Release date | 2026-05-01 |
| License | CC BY-NC 4.0 |
| Model ID | jina-embeddings-v5-omni-nano |
| Provider | Jina AI |
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What You Need to Know About Jina Embeddings v5 Omni Nano
Complete Specifications for Jina Embeddings v5 Omni Nano by Jina AI
Get detailed specifications for Jina Embeddings v5 Omni Nano, including output dimensionality of 768 dimensions, maximum input token length, supported input modalities, and pricing per million tokens. This embedding model is designed for semantic search, text classification, clustering, and retrieval-augmented generation applications where understanding the relationship between texts is essential.
Pricing and Cost Efficiency for Jina Embeddings v5 Omni Nano
Review the pricing structure for Jina Embeddings v5 Omni Nano and compare it against other embedding models from Jina AI and competitors. Understanding embedding model costs is essential when scaling vector search and RAG applications to millions of documents. We provide transparent pricing to help you budget effectively.
Use Cases and Applications for Jina Embeddings v5 Omni Nano
Explore the ideal use cases for Jina Embeddings v5 Omni Nano. Whether you are building a semantic search engine, recommendation system, document classification pipeline, or multilingual retrieval system, understanding this model's capabilities and dimensionality will help you choose the right embedding strategy for your project.