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Embeddings
copyright CC BY-NC 4.0
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jina-embeddings-v5-omni-nano

Compact multimodal embeddings for edge deployment
License
copyright CC-BY-NC-4.0
Release Date
calendar_month
2026-05-07
Input
abc
Text
image
Image
audiotrack
Audio
videocam
Video
picture_as_pdf
PDF
arrow_forward
Output
more_horiz
Vector
Matryoshka Dimensions help_outline
32
64
128
256
512
768
Late Chunking help_outline
cancel
No
Model Details
Parameters: 1.0B
Input Token Length: 8K
Output Dimension: 768
Base Model help_outline
open_in_new
jina-embeddings-v5-text-nano
Trained Languages help_outline
32 languages
Supported Languages help_outline
108 languages
Quantizations help_outline
GGUF
Apple Silicon Support help_outline
MLX
Related Models
link
jina-embeddings-v5-omni-small
link
jina-embeddings-v5-text-nano
link
jina-embeddings-v3
link
jina-clip-v2
Supported Tasks
search Retrieval
compare_arrows Text Matching
bubble_chart Clustering
label Classification
Tags
multimodal-embedding
embeddings
multilingual
long-context
production
matryoshka
last-token-pooling
visual-document-retrieval
Available via
Elastic Inference ServiceJina APIAWS SageMakerHugging Face
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Publications (1)
arXiv
May 11, 2026
jina-embeddings-v5-omni: Text-Geometry-Preserving Multimodal Embeddings via Frozen-Tower Composition

Overview

jina-embeddings-v5-omni-nano (~1.04B parameters) is the compact variant of the v5-omni family, designed for edge and commodity hardware. It extends jina-embeddings-v5-text-nano with the same multimodal capabilities: text, images, video, and audio inputs in a shared vector space. Text-only outputs are bit-identical to jina-embeddings-v5-text-nano. The model produces 768-dimensional embeddings with Matryoshka truncation down to 32 dimensions and supports 8K token context length.

Methods

Follows the same third-stage training as omni-small, extending jina-embeddings-v5-text-nano. The EuroBERT-210M text backbone and LoRA adapters are frozen. Cross-modal projectors connect a SigLIP2 Base vision encoder and Whisper-large-v3 audio encoder to the text backbone. Training data and objectives mirror omni-small.

Performance

Text-only performance is bit-identical to jina-embeddings-v5-text-nano. Multimodal performance is slightly below omni-small due to the narrower embedding space (768 vs 1024 dimensions) and smaller text backbone, but maintains strong cross-modal alignment. Optimized for CPU and edge hardware where the larger omni-small model cannot run.

Best Practice

Same usage pattern as omni-small with identical LoRA adapter selection and multimodal input handling. Key differences: 768-dimensional output space (Matryoshka truncation down to 32) and 8K context window. The nano variant runs on commodity hardware without GPU acceleration. Text-only embeddings are drop-in compatible with jina-embeddings-v5-text-nano.
Blogs that mention this model
May 12, 2026 • 7 minutes read
jina-embeddings-v5-omni: Embeddings for Text, Image, Audio and Video
One model, four modalities: text, image, audio, video. Best-in-class omni embeddings in 1.6B and 0.9B.
Han Xiao
Search Foundation
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