Jina Embeddings v5 Omni Nano

embedjina-ai

Jina Embeddings v5 Omni Nano is a lightweight multilingual multimodal embedding model with 1.004B parameters built on the jina-embeddings-v5-text-nano text backbone, extended with a fine-tuned SigLIP2 Base vision encoder (from Qwen3.5-0.8B) for image and video and a Whisper-large-v3 audio encoder (from Qwen2.5-Omni-7B), connected via trained cross-modal projectors. It supports 8K context length and produces 768-dimensional embeddings with Matryoshka representation learning (down to 32 dimensions). It uses last-token pooling and supports retrieval, text-matching, clustering, and classification tasks across text, image, video, audio, and PDF inputs.

Context
8K
Input price
$0.02/1M tokens
Output price
—

Capabilities

No supported capabilities recorded.

Details

Model IDjina-embeddings-v5-omni-nano
Provider Jina AI
Creator jina
Licensejina-ai
Statusactive
Typeembed
Input modalitiestext, image, video, audio
Output modalitiesembedding
Open weightYes
Parameters—
Architecture—
Context window8K tokens
Max input—
Max output—
Reasoning tokens—
Knowledge cutoff—
Release date
Sourceofficial

Endpoints

EmbeddingsPOST
Generate vector embeddings for texthttps://api.jina.ai/v1/embeddings

Pricing

Input
$0.02
Output
—
Cache write
—
Cache read
—
Batch in
—
Batch out
—

Family Comparison: jina-embeddings

ModelContextMax outPricing
Jina Embeddings v5 Omni Nano8K—$0.02—
Jina Embeddings v5 Text Nano8K—$0.02—
Jina Embeddings v2 Base Code8K—$0.05—
Jina Embeddings v2 Base DE8K—$0.05—
Jina Embeddings v2 Base EN8K—$0.05—
Jina Embeddings v2 Base ES8K—$0.05—
Jina Embeddings v2 Base ZH8K—$0.05—
Jina Embeddings v38K—$0.05—
Jina Embeddings v433K—$0.05—
Jina Embeddings v5 Omni Small33K—$0.05—
Jina Embeddings v5 Text Small33K—$0.05—

API

GET/v1/models/jina/jina-embeddings-v5-omni-nano

Jina Embeddings v5 Omni Nano

jina-embeddings-v5-omni-nano

Jina Embeddings v5 Omni Nano is a lightweight multilingual multimodal embedding model with 1.004B parameters built on the jina-embeddings-v5-text-nano text backbone, extended with a fine-tuned SigLIP2 Base vision encoder (from Qwen3.5-0.8B) for image and video and a Whisper-large-v3 audio encoder (from Qwen2.5-Omni-7B), connected via trained cross-modal projectors. It supports 8K context length and produces 768-dimensional embeddings with Matryoshka representation learning (down to 32 dimensions). It uses last-token pooling and supports retrieval, text-matching, clustering, and classification tasks across text, image, video, audio, and PDF inputs.

Changes · 2 entries
jina-embeddings-v5-omni-nanocreateca7a400Nov 2, 2026, 03:02 AM
jina-embeddings-v5-omni-nanocreate80c574aJun 3, 2026, 07:05 AM