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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.

The v4 multimodal retriever carries a separate Qwen Research License inherited from Qwen2.5-VL-3B, which is why it and the v5-omni tier are treated as a distinct vision-language product rather than folded into this record. The vendor's GGUF and vLLM re-publishes are the same weights in another container and are excluded from the download count to avoid double-counting.

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

Jina's current text models are non-commercial: v3 and the v5-text line ship under CC-BY-NC-4.0, with commercial use routed to a sales conversation rather than granted. Only the older v1 and v2 encoders carry Apache-2.0, and because CC-BY-NC-4.0 governs what ships today, that is the license the score reflects.

Adoption

4 high confidence
4.0

Adoption is measured as Hugging Face downloads across the jina-embeddings text checkpoints — v2, v3 and the v5-text line — excluding the multimodal v4 and v5-omni tier and the separate jina-clip, code-embeddings and colbert lines.

Capability

4 high confidence
4.0

Jina-embeddings-v5-text-small is current-generation, multilingual and long-context, scoring 67.7 on MMTEB against Harrier-OSS's 74.3 on the same benchmark — a step behind the category leader rather than level with it.

  • 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