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Jina Embeddings

Jina AI
restricted / Overall score: 4.0(strong)

Jina AI's text embedding line, from the v2 English and bilingual encoders through v3's task-LoRA multilingual model to the v5-text family released in early 2026. v5-text-small is a 677M Qwen3-0.6B-Base distillation of Qwen3-Embedding-4B scoring 67.7 on MMTEB across 119+ languages at 32K tokens, with retrieval, text-matching, clustering and classification adapters shipped separately for vLLM and ONNX. The weights are published on the Hub, but the current generation is non-commercial.

Added 2026-09-11 for the embeddings_retrieval roster, as the embedding sibling of jina-reranker. Scope is the TEXT line in the jina-embeddings namespace of the jinaai account: the v1 and v2 encoders, v3 and the v5-text tier. The v4 universal multimodal retriever and the v5-omni tier are excluded on every axis under the category's rule that a vision-language line is a separate product from the text line; that is why the Qwen Research License v4 inherits from Qwen2.5-VL-3B is not part of this record's licence compound. The vendor's own GGUF and vLLM re-publishes are the same weights in another container, so they belong to this line but are not added to the download sum, which would double-count them. jina-reranker covers the rerankers; jina-clip, jina-code-embeddings and jina-colbert-v2 are separate lines and are not counted here. The licence is the thing to read carefully, as with the reranker: v3 and v5-text are cc-by-nc-4.0 while the v1 and v2 checkpoints remain Apache-2.0, and the most restrictive distributed SKU governs. Verified 2026-09-11 via the model cards and the Hub API.

Openness

2 high confidence
2.0
weights
open(ungated safetensors on the Hub across the v2, v3 and v5-text lines)
data
closed(no training corpus or construction scripts released
code
partial(trust_remote_code inference modules and ONNX/GGUF conversions ship with the repositories
license
Apache-2.0(OSI, and only the older v1 and v2 encoders)+CC-BY-NC-4.0(non-commercial

The current text SKUs are non-commercial: v3 and the v5-text line read cc-by-nc-4.0, while Apache-2.0 covers only the superseded v1 and v2 encoders, so the compound resolves on the non-commercial half at commercial_forbidden - whose one question, does the license permit commercial use at all, the cards answer no, directing commercial use to a sales conversation. The compound covers the text line and nothing else: the v4 universal multimodal retriever, which inherits the Qwen Research License from Qwen2.5-VL-3B, is excluded from this record on every axis under the category's vision-language rule, so no unmapped licence is being passed over here.

Adoption

4 high confidence
4.0

4,687,946 downloads in the trailing 30 days across the jina-embeddings TEXT checkpoints. The v4 universal multimodal retriever and the v5-omni tier are excluded under the category's rule that a vision-language line is a separate product from the text line; counting them gives 5,402,605 and the same band. Vendor GGUF and vLLM re-publishes are excluded, as are the separate jina-clip, jina-code-embeddings and jina-colbert lines.

Capability

4 high confidence
4.0

Rung 4, competitive frontier. Current generation, multilingual and long-context, with published numbers on the same instrument as the anchor: 67.7 MMTEB against harrier-oss at 74.3, so one band below the leader rather than level with it. The card's own claim is narrower than the leaderboard - the highest MMTEB among multilingual embedding models under 1B parameters - which is a frontier position in its size class rather than the top of the table.

  • https://huggingface.co/jinaai/jina-embeddings-v5-text-small/raw/main/README.md recorded 2026-09-11

    Card states jina-embeddings-v5-text-small scores 71.7 average on MTEB English v2 and 67.7 on MMTEB with 677M parameters, the highest among multilingual embedding models under 1B, supporting 119+ languages at up to 32K tokens and built on Qwen3-0.6B-Base by distillation from Qwen3-Embedding-4B.

Verified 2026-09-11