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*Average score vs. parameter count across image (MIEB-Lite), video (MMEB-V), and audio (MAEB) benchmarks — `jina-v5-omni-nano` and `jina-v5-omni-small` define the open-weight frontier (Table 1 in the ArXiv report).* `jina-embeddings-v5-omni-nano-retrieval` is a multimodal embedding model that accepts **text, images, video, and audio** and produces embeddings in a shared vector space aligned with the text-only `jinaai/jina-embeddings-v5-text-nano-retrieval` — so you can index with text and query with any modality, no reindexing. For higher performance at a larger size, see `jinaai/jina-embeddings-v5-omni-small-retrieval`. This is the **retrieval-targeted** variant of the `jina-embeddings-v5-omni-nano` family. The combined repo containing all task adapters is `jinaai/jina-embeddings-v5-omni-nano`.

Embeddings & similarity
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*Average score vs. parameter count across image (MIEB-Lite), video (MMEB-V), and audio (MAEB) benchmarks — `jina-v5-omni-nano` and `jina-v5-omni-small` define the open-weight frontier (Table 1 in the ArXiv report).* `jina-embeddings-v5-omni-small` is a multimodal embedding model that accepts **text, images, video, and audio** and produces embeddings in a shared vector space aligned with the text-only `jinaai/jina-embeddings-v5-text-small` — so you can index with text and query with any modality, no reindexing. For a more compact alternative, see `jinaai/jina-embeddings-v5-omni-nano`. This is the **base** repository — it holds all task adapters (retrieval, classification, clustering, text-matching). For a single task, pre-merged task-specific variants are also available: - `jinaai/jina-embeddings-v5-omni-small-retrieval` — query–document semantic search and RAG (raw-transformers users prepend `Query: ` / `Document: ` to text; sentence-transformers users call `encode_query()` / `encode_document()`). - `jinaai/jina-embeddings-v5-omni-small-classification` — assigning labels via embedding similarity — zero-shot and few-shot classification across modalities. - `jinaai/jina-embeddings-v5-omni-small-clustering` — grouping semantically similar items — topic discovery, deduplication, exploratory analysis. - `jinaai/jina-embeddings-v5-omni-small-text-matching` — symmetric pairwise similarity scoring — STS, paraphrase and near-duplicate detection.

Text analysisOpen weights
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基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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*Average score vs. parameter count across image (MIEB-Lite), video (MMEB-V), and audio (MAEB) benchmarks — `jina-v5-omni-nano` and `jina-v5-omni-small` define the open-weight frontier (Table 1 in the ArXiv report).* `jina-embeddings-v5-omni-small-retrieval` is a multimodal embedding model that accepts **text, images, video, and audio** and produces embeddings in a shared vector space aligned with the text-only `jinaai/jina-embeddings-v5-text-small-retrieval` — so you can index with text and query with any modality, no reindexing. For a more compact alternative, see `jinaai/jina-embeddings-v5-omni-nano-retrieval`. This is the **retrieval-targeted** variant of the `jina-embeddings-v5-omni-small` family. The combined repo containing all task adapters is `jinaai/jina-embeddings-v5-omni-small`.

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