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jina embeddings v5 omni small

jina-embeddings-v5-omni-small is a multimodal feature-extraction embedding model from Jina AI. It accepts text, images, video, and audio and produces embeddings in a shared vector space aligned with the text-only jina-embeddings-v5-text-small. It is a base repository holding adapters for retrieval, classification, clustering, and text-matching, with separate pre-merged task-specific variants available. The model is tagged multilingual and uses a last-token pooling strategy. Its license is cc-by-nc-4.0.

EstimatedRepository opened Apr 1, 2026Source checked 9/25/2026Version: 5c54692f
LOCALRENTED GPUOPEN WEIGHTS
Freshness 47 out of 100. Repository age: 197 days old, Apr 1, 2026. Measures age, not quality.
Popularity 78 out of 100. 1,000,355 downloads in 30 days; 170 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.
What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

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Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source
Scores as of Oct 15, 2026. Statistics checked Oct 15, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

At a glance

Parameters
1.63B
Architecture
jina_embeddings_v5_omni
License
cc-by-nc-4.0
Disk space
3 GB
Software
vLLM
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Best for

  • Cross-modal semantic search where text queries retrieve items indexed from text, images, video, or audio.
  • Zero-shot or few-shot classification across modalities using embedding similarity.
  • Clustering semantically similar multimodal items for topic discovery, deduplication, or exploratory analysis.
  • Symmetric pairwise similarity scoring for STS, paraphrase detection, or near-duplicate detection.
  • RAG retrieval over heterogeneous media including documents, images, video, and audio.

Tradeoffs

  • Released under cc-by-nc-4.0, which restricts commercial use.
  • It is a base repository with task adapters; using a single task may require a separate pre-merged variant.
  • No explicit supported hardware, memory, or performance requirements are provided in the source facts.
  • No information is provided about training data, languages beyond the 'multilingual' tag, or modality coverage details.
  • The model card states inference: false.

Ways to run it

vLLM · Linux

Repository-specific command in publisher documentation; confirm dependencies and hardware in the source.

vllm serve jinaai/jina-embeddings-v5-omni-small --trust-remote-code --hf-overrides '{"task": "retrieval"}'
Official instructions

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Popularity 90 out of 100. 4,849,199 downloads in 30 days; 2,697 lifetime likes. Checked Oct 15, 2026. Measures adoption, not quality.
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