dense Open weights Instruction-tuned ST compatible text
Qwen/Qwen3-Embedding-4B
- Languages
AfrikaansArabicArmenianAzerbaijaniBasqueBelarusianBengaliBulgarianBurmeseCatalanCebuanoChinese +61 more
CroatianCzechDanishDutchEnglishEstonianFinnishFrenchGalicianGeorgianGermanGujaratiHaitianHebrewHindiHungarianIcelandicIndonesianItalianJapaneseJavaneseKannadaKazakhKhmerKirghizKoreanLaoLatvianLithuanianMacedonianMalay (macrolanguage)MalayalamMarathiModern Greek (1453-)MongolianNepali (macrolanguage)NorwegianNorwegian BokmålNorwegian NynorskPanjabiPersianPolishPortugueseQuechua (Latin)RomanianRussianSinhalaSlovakSlovenianSpanishSwahili (macrolanguage)TagalogTamilTeluguThaiTurkishUkrainianUrduVietnameseWelshYoruba- License
- apache-2.0
- Trained on
CMedQAv2-rerankingCodeSearchNetDuRetrievalFEVERHotpotQAMIRACLRetrievalMMarcoRerankingMSMARCO +3 more
MrTidyRetrievalNQT2Retrieval
Cite this model
Citation (BibTeX)
@article{qwen3embedding,
title={Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models},
author={Zhang, Yanzhao and Li, Mingxin and Long, Dingkun and Zhang, Xin and Lin, Huan and Yang, Baosong and Xie, Pengjun and Yang, An and Liu, Dayiheng and Lin, Junyang and Huang, Fei and Zhou, Jingren},
journal={arXiv preprint arXiv:2506.05176},
year={2025}
}Parameters 4.0B
Active parameters 3.6B
Embedding dim 2,560
Max tokens 32,768
Memory 7.5 GB
Released 2025-06-05
Openness
4/6
- Open weights
- Open license
- Training code
- Training data
- Paper
- Model card