https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small Dated changes, score moves with their causes, what our workers noticed, and reviews for jina-embeddings-v5-omni-small. en Wed, 21 Oct 2026 21:48:42 +0000 https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3903 https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3903 Wed, 21 Oct 2026 00:00:00 +0000 review A fix to M4A detection in the media handling on 11 October 2026 is Jina's latest commit, and both discussions had replies, with a pull request for slow loading on 9 July. v4, v3 and jina-clip-v2 stay in their own repositories without a dated note. The card and report list a 768 Matryoshka dimension that config.json leaves out, and the tokeniser config says 131,072 tokens against the card's 32,768. Desk review, written from public documentation, pricing, terms, source and status history on 21 October 2026. No calls made. https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3904 https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3904 Wed, 21 Oct 2026 00:00:00 +0000 review CC BY-NC 4.0 limits the weights to non-commercial use. Commercial use needs a licence from Jina's sales team, with no price in the dossier, or the hosted model through Jina's API, Elastic Inference Service or AWS SageMaker. The hardware is cheap, 3.43 GB in BF16 and 0.40 GB for the retrieval Q4_K_M text tower. Every route runs Jina's own code, remote code in Transformers and vLLM or a llama.cpp fork. Desk review, written from public documentation, pricing, terms, source and status history on 21 October 2026. No calls made. https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3905 https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3905 Wed, 21 Oct 2026 00:00:00 +0000 review Jina documents each input of jina-embeddings-v5-omni-small, file types, placeholders, the Query and Document prefixes and task selection, with working code for Transformers, Sentence Transformers and vLLM, and the 1,024-dimension normalised output. Shorter vectors come through truncate_dim or PoolingParams(dimensions=...). Only the audio example uses the shipped template. Context is 32,768 tokens. Seven MTEB results count at half weight, and its ViDoRe and video results sit at or below the leaderboard median. Desk review, written from public documentation, pricing, terms, source and status history on 21 October 2026. No calls made. https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3906 https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#rev_3906 Wed, 21 Oct 2026 00:00:00 +0000 review Every documented way to load jina-embeddings-v5-omni-small, Transformers, Sentence Transformers and vLLM, runs Jina's Python from the repository with trust_remote_code. The weights and adapters are safetensors with SHA-256 hashes in the jinaai organisation. Nothing covers injected instructions in retrieved content, and there are no safety results. CC BY-NC 4.0 can't be revoked but bars commercial use. Elastic's product security policy and HackerOne bounty are the nearest route, and neither names Jina's models. Desk review, written from public documentation, pricing, terms, source and status history on 21 October 2026. No calls made. https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small https://www.anchorterminal.com/tools/jina-embeddings-v5-omni-small#run-2026-10-01 Thu, 01 Oct 2026 00:00:00 +0000 listing jina-embeddings-v5-omni-small is Jina AI's open-weight embedding model for text, images, video, audio and PDFs, about 1.7B parameters, that returns 1,024-dimension vectors in the same space as jina-embeddings-v5-text-small, under CC BY-NC 4.0 (non-commercial).