Text Model¶

Number of models: 225

Instruction Model¶

`Alibaba-NLP/gte-Qwen1.5-7B-instruct`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.7B	28.8 GB	2024-04-20	eng-Latn

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`Alibaba-NLP/gte-Qwen2-1.5B-instruct`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	8960	1.8B	6.6 GB	2024-07-29	eng-Latn

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`Alibaba-NLP/gte-Qwen2-7B-instruct`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	3584	7.6B	28.4 GB	2024-06-15	not specified

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`BAAI/bge-base-en`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	390.0 MB	2023-08-05	eng-Latn

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-base-en-v1.5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	390.0 MB	2023-09-11	eng-Latn

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-base-zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	390.0 MB	2023-08-05	zho-Hans

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-base-zh-v1.5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	416.0 MB	2023-09-11	zho-Hans

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-large-en`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2023-08-05	eng-Latn

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-large-en-v1.5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2023-09-12	eng-Latn

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-large-zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2023-08-02	zho-Hans

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-large-zh-v1.5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2023-09-12	zho-Hans

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-small-en`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	512	33.4M	127.0 MB	2023-08-05	eng-Latn

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-small-en-v1.5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	512	33.4M	127.0 MB	2023-09-12	eng-Latn

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-small-zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	512	33.4M	127.0 MB	2023-08-05	zho-Hans

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-small-zh-v1.5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	512	33.4M	91.0 MB	2023-09-12	zho-Hans

Citation

@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding},
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BMRetriever/BMRetriever-1B`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	2048	908.8M	3.4 GB	2024-04-29	eng-Latn

Citation

@inproceedings{xu-etal-2024-bmretriever,
    title = "{BMR}etriever: Tuning Large Language Models as Better Biomedical Text Retrievers",
    author = "Xu, Ran and Shi, Wenqi and Yu, Yue and Zhuang, Yuchen and Zhu, Yanqiao and Wang, May Dongmei and Ho, Joyce C. and Zhang, Chao and Yang, Carl",
    booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
    month = "November",
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    pages = "22234--22254",
    url = "https://aclanthology.org/2024.emnlp-main.1241/"
}

`BMRetriever/BMRetriever-2B`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	2048	2.5B	9.3 GB	2024-04-29	eng-Latn

Citation

@inproceedings{xu-etal-2024-bmretriever,
    title = "{BMR}etriever: Tuning Large Language Models as Better Biomedical Text Retrievers",
    author = "Xu, Ran and Shi, Wenqi and Yu, Yue and Zhuang, Yuchen and Zhu, Yanqiao and Wang, May Dongmei and Ho, Joyce C. and Zhang, Chao and Yang, Carl",
    booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
    month = "November",
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    pages = "22234--22254",
    url = "https://aclanthology.org/2024.emnlp-main.1241/"
}

`BMRetriever/BMRetriever-410M`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	1024	353.8M	1.3 GB	2024-04-29	eng-Latn

Citation

@inproceedings{xu-etal-2024-bmretriever,
    title = "{BMR}etriever: Tuning Large Language Models as Better Biomedical Text Retrievers",
    author = "Xu, Ran and Shi, Wenqi and Yu, Yue and Zhuang, Yuchen and Zhu, Yanqiao and Wang, May Dongmei and Ho, Joyce C. and Zhang, Chao and Yang, Carl",
    booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
    month = "November",
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    pages = "22234--22254",
    url = "https://aclanthology.org/2024.emnlp-main.1241/"
}

`BMRetriever/BMRetriever-7B`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-04-29	eng-Latn

Citation

@inproceedings{xu-etal-2024-bmretriever,
    title = "{BMR}etriever: Tuning Large Language Models as Better Biomedical Text Retrievers",
    author = "Xu, Ran and Shi, Wenqi and Yu, Yue and Zhuang, Yuchen and Zhu, Yanqiao and Wang, May Dongmei and Ho, Joyce C. and Zhang, Chao and Yang, Carl",
    booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
    month = "November",
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    pages = "22234--22254",
    url = "https://aclanthology.org/2024.emnlp-main.1241/"
}

`BeastyZ/e5-R-mistral-7b`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.2B	27.0 GB	2024-06-28	eng-Latn

`ByteDance-Seed/Seed1.5-Embedding`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	2048	not specified	not specified	2025-04-25	eng-Latn, zho-Hans

`Bytedance/Seed1.6-embedding`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	2048	not specified	not specified	2025-06-18	eng-Latn, zho-Hans

`Bytedance/Seed1.6-embedding-1215`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	2048	not specified	not specified	2025-12-15	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

`Cohere/Cohere-embed-english-light-v3.0`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	not specified	not specified	2023-11-02	eng-Latn

`Cohere/Cohere-embed-english-v3.0`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	not specified	not specified	2023-11-02	eng-Latn

`Cohere/Cohere-embed-multilingual-light-v3.0`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	not specified	not specified	2023-11-02	afr-Latn, amh-Ethi, ara-Arab, asm-Beng, aze-Latn, ... (111)

`Cohere/Cohere-embed-multilingual-v3.0`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	512	not specified	not specified	2023-11-02	afr-Latn, amh-Ethi, ara-Arab, asm-Beng, aze-Latn, ... (111)

`GeoGPT-Research-Project/GeoEmbedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.2B	27.0 GB	2025-04-22	eng-Latn

`GritLM/GritLM-7B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.2B	13.5 GB	2024-02-15	deu-Latn, eng-Latn, fra-Latn, ita-Latn, spa-Latn

Citation

@misc{muennighoff2024generative,
      title={Generative Representational Instruction Tuning},
      author={Niklas Muennighoff and Hongjin Su and Liang Wang and Nan Yang and Furu Wei and Tao Yu and Amanpreet Singh and Douwe Kiela},
      year={2024},
      eprint={2402.09906},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`GritLM/GritLM-8x7B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	32768	57.9B	87.0 GB	2024-02-15	deu-Latn, eng-Latn, fra-Latn, ita-Latn, spa-Latn

Citation

@misc{muennighoff2024generative,
      title={Generative Representational Instruction Tuning},
      author={Niklas Muennighoff and Hongjin Su and Liang Wang and Nan Yang and Furu Wei and Tao Yu and Amanpreet Singh and Douwe Kiela},
      year={2024},
      eprint={2402.09906},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	896	494.0M	1.8 GB	2024-10-23	eng-Latn, zho-Hans

Citation

@article{hu2025kalm,
  title={KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model},
  author={Hu, Xinshuo and Shan, Zifei and Zhao, Xinping and Sun, Zetian and Liu, Zhenyu and Li, Dongfang and Ye, Shaolin and Wei, Xinyuan and Chen, Qian and Hu, Baotian and others},
  journal={arXiv preprint arXiv:2501.01028},
  year={2025}
}

`HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v1.5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	896	494.0M	1.8 GB	2024-12-26	eng-Latn, zho-Hans

Citation

@article{hu2025kalm,
  title={KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model},
  author={Hu, Xinshuo and Shan, Zifei and Zhao, Xinping and Sun, Zetian and Liu, Zhenyu and Li, Dongfang and Ye, Shaolin and Wei, Xinyuan and Chen, Qian and Hu, Baotian and others},
  journal={arXiv preprint arXiv:2501.01028},
  year={2025}
}

`HIT-TMG/KaLM-embedding-multilingual-mini-instruct-v2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	896	494.0M	942.0 MB	2025-06-25	eng-Latn, zho-Hans

Citation

@article{hu2025kalm,
  title={KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model},
  author={Hu, Xinshuo and Shan, Zifei and Zhao, Xinping and Sun, Zetian and Liu, Zhenyu and Li, Dongfang and Ye, Shaolin and Wei, Xinyuan and Chen, Qian and Hu, Baotian and others},
  journal={arXiv preprint arXiv:2501.01028},
  year={2025}
}

`IEITYuan/Yuan-embedding-2.0-en`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	1024	595.8M	2.2 GB	2025-11-27	eng-Latn

`KaLM-Embedding/KaLM-embedding-multilingual-mini-instruct-v2.5`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	896	494.0M	1.8 GB	2025-09-30	eng-Latn, zho-Hans

Citation

@misc{zhao2025kalmembeddingv2,
      title={KaLM-Embedding-V2: Superior Training Techniques and Data Inspire A Versatile Embedding Model}, 
      author={Xinping Zhao and Xinshuo Hu and Zifei Shan and Shouzheng Huang and Yao Zhou and Xin Zhang and Zetian Sun and Zhenyu Liu and Dongfang Li and Xinyuan Wei and Youcheng Pan and Yang Xiang and Meishan Zhang and Haofen Wang and Jun Yu and Baotian Hu and Min Zhang},
      year={2025},
      eprint={2506.20923},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.20923}, 
}

@misc{hu2025kalmembedding,
      title={KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model}, 
      author={Xinshuo Hu and Zifei Shan and Xinping Zhao and Zetian Sun and Zhenyu Liu and Dongfang Li and Shaolin Ye and Xinyuan Wei and Qian Chen and Baotian Hu and Haofen Wang and Jun Yu and Min Zhang},
      year={2025},
      eprint={2501.01028},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2501.01028}, 
}

`Kingsoft-LLM/QZhou-Embedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	3584	7.1B	14.1 GB	2025-08-24	eng-Latn, zho-Hans

Citation

@misc{yu2025qzhouembeddingtechnicalreport,
      title={QZhou-Embedding Technical Report},
      author={Peng Yu and En Xu and Bin Chen and Haibiao Chen and Yinfei Xu},
      year={2025},
      eprint={2508.21632},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.21632},
}

`Kingsoft-LLM/QZhou-Embedding-Zh`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1792	7.6B	28.7 GB	2025-09-28	zho-Hans

Citation

@misc{yu2025qzhouembeddingtechnicalreport,
      title={QZhou-Embedding Technical Report},
      author={Peng Yu and En Xu and Bin Chen and Haibiao Chen and Yinfei Xu},
      year={2025},
      eprint={2508.21632},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.21632},
}

`Linq-AI-Research/Linq-Embed-Mistral`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	13.2 GB	2024-05-29	eng-Latn

Citation

@misc{LinqAIResearch2024,
  title={Linq-Embed-Mistral:Elevating Text Retrieval with Improved GPT Data Through Task-Specific Control and Quality Refinement},
  author={Junseong Kim and Seolhwa Lee and Jihoon Kwon and Sangmo Gu and Yejin Kim and Minkyung Cho and Jy-yong Sohn and Chanyeol Choi},
  howpublished={Linq AI Research Blog},
  year={2024},
  url={https://getlinq.com/blog/linq-embed-mistral/}
}

`McGill-NLP/LLM2Vec-Llama-2-7b-chat-hf-mntp-supervised`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`McGill-NLP/LLM2Vec-Llama-2-7b-chat-hf-mntp-unsup-simcse`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	4096	7.5B	28.0 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-unsup-simcse`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	4096	7.5B	28.0 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`McGill-NLP/LLM2Vec-Mistral-7B-Instruct-v2-mntp-supervised`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`McGill-NLP/LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`McGill-NLP/LLM2Vec-Sheared-LLaMA-mntp-supervised`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`McGill-NLP/LLM2Vec-Sheared-LLaMA-mntp-unsup-simcse`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-04-09	eng-Latn

Citation

@misc{behnamghader2024llm2veclargelanguagemodels,
      title={LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders},
      author={Parishad BehnamGhader and Vaibhav Adlakha and Marius Mosbach and Dzmitry Bahdanau and Nicolas Chapados and Siva Reddy},
      year={2024},
      eprint={2404.05961},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.05961},
}

`MongoDB/mdbr-leaf-ir`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	22.9M	86.0 MB	2025-08-27	eng-Latn

Citation

@misc{mdbr_leaf,
  title={LEAF: Knowledge Distillation of Text Embedding Models with Teacher-Aligned Representations},
  author={Robin Vujanic and Thomas Rueckstiess},
  year={2025},
  eprint={2509.12539},
  archivePrefix={arXiv},
  primaryClass={cs.IR},
  url={https://arxiv.org/abs/2509.12539}
}

`MongoDB/mdbr-leaf-mt`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	23.0M	86.0 MB	2025-08-27	eng-Latn

Citation

@misc{mdbr_leaf,
  title={LEAF: Knowledge Distillation of Text Embedding Models with Teacher-Aligned Representations},
  author={Robin Vujanic and Thomas Rueckstiess},
  year={2025},
  eprint={2509.12539},
  archivePrefix={arXiv},
  primaryClass={cs.IR},
  url={https://arxiv.org/abs/2509.12539}
}

`NovaSearch/jasper_en_vision_language_v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
131.1K	8960	2.0B	3.7 GB	2024-12-11	eng-Latn

Citation

@misc{zhang2025jasperstelladistillationsota,
      title={Jasper and Stella: distillation of SOTA embedding models},
      author={Dun Zhang and Jiacheng Li and Ziyang Zeng and Fulong Wang},
      year={2025},
      eprint={2412.19048},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2412.19048},
}

`NovaSearch/stella_en_1.5B_v5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
131.1K	8960	1.5B	5.7 GB	2024-07-12	eng-Latn

Citation

@misc{zhang2025jasperstelladistillationsota,
      title={Jasper and Stella: distillation of SOTA embedding models},
      author={Dun Zhang and Jiacheng Li and Ziyang Zeng and Fulong Wang},
      year={2025},
      eprint={2412.19048},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2412.19048},
}

`NovaSearch/stella_en_400M_v5`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	4096	435.0M	1.6 GB	2024-07-12	eng-Latn

Citation

@misc{zhang2025jasperstelladistillationsota,
      title={Jasper and Stella: distillation of SOTA embedding models},
      author={Dun Zhang and Jiacheng Li and Ziyang Zeng and Fulong Wang},
      year={2025},
      eprint={2412.19048},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2412.19048},
}

`Qwen/Qwen3-Embedding-0.6B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	1024	595.8M	1.1 GB	2025-06-05	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

Citation

@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}
}

`Qwen/Qwen3-Embedding-4B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	2560	4.0B	7.5 GB	2025-06-05	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

Citation

@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}
}

`Qwen/Qwen3-Embedding-8B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.6B	14.1 GB	2025-06-05	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

Citation

@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}
}

`ReasonIR/ReasonIR-8B`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
131.1K	4096	7.5B	not specified	2025-04-29	eng-Latn

Citation

@article{shao2025reasonir,
      title={ReasonIR: Training Retrievers for Reasoning Tasks},
      author={Rulin Shao and Rui Qiao and Varsha Kishore and Niklas Muennighoff and Xi Victoria Lin and Daniela Rus and Bryan Kian Hsiang Low and Sewon Min and Wen-tau Yih and Pang Wei Koh and Luke Zettlemoyer},
      year={2025},
      journal={arXiv preprint arXiv:2504.20595},
      url={https://arxiv.org/abs/2504.20595},
}

`Sailesh97/Hinvec`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	2048	939.6M	3.6 GB	2025-06-19	eng-Latn, hin-Deva

`Salesforce/SFR-Embedding-2_R`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	13.2 GB	2024-06-14	eng-Latn

Citation

@misc{SFR-embedding-2,
      title={SFR-Embedding-2: Advanced Text Embedding with Multi-stage Training},
      author={Rui Meng*, Ye Liu*, Shafiq Rayhan Joty, Caiming Xiong, Yingbo Zhou, Semih Yavuz},
      year={2024},
      url={https://huggingface.co/Salesforce/SFR-Embedding-2_R}
    }

`Salesforce/SFR-Embedding-Code-2B_R`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	2304	2.6B	4.9 GB	2025-01-17	eng-Latn

Citation

@article{liu2024codexembed,
  title={CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval},
  author={Liu, Ye and Meng, Rui and Jot, Shafiq and Savarese, Silvio and Xiong, Caiming and Zhou, Yingbo and Yavuz, Semih},
  journal={arXiv preprint arXiv:2411.12644},
  year={2024}
}

`Salesforce/SFR-Embedding-Mistral`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	13.2 GB	2024-01-24	eng-Latn

Citation

    @misc{SFRAIResearch2024,
  title={SFR-Embedding-Mistral:Enhance Text Retrieval with Transfer Learning},
  author={Rui Meng, Ye Liu, Shafiq Rayhan Joty, Caiming Xiong, Yingbo Zhou, Semih Yavuz},
  howpublished={Salesforce AI Research Blog},
  year={2024},
  url={https://www.salesforce.com/blog/sfr-embedding/}
}

`SamilPwC-AXNode-GenAI/PwC-Embedding_expr`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	560.0M	2.1 GB	2025-08-12	kor-Hang

`Snowflake/snowflake-arctic-embed-l`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2024-04-12	eng-Latn

Citation

@article{merrick2024embedding,
      title={Embedding And Clustering Your Data Can Improve Contrastive Pretraining},
      author={Merrick, Luke},
      journal={arXiv preprint arXiv:2407.18887},
      year={2024},
      eprint={2407.18887},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2407.18887}
}

`Snowflake/snowflake-arctic-embed-l-v2.0`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	568.0M	2.1 GB	2024-12-04	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (74)

Citation

@article{yu2024arctic,
      title={Arctic-Embed 2.0: Multilingual Retrieval Without Compromise},
      author={Yu, Puxuan and Merrick, Luke and Nuti, Gaurav and Campos, Daniel},
      journal={arXiv preprint arXiv:2412.04506},
      year={2024},
      eprint={2412.04506},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2412.04506}
}

`Snowflake/snowflake-arctic-embed-m`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	415.0 MB	2024-04-12	eng-Latn

Citation

@article{merrick2024embedding,
      title={Embedding And Clustering Your Data Can Improve Contrastive Pretraining},
      author={Merrick, Luke},
      journal={arXiv preprint arXiv:2407.18887},
      year={2024},
      eprint={2407.18887},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2407.18887}
}

`Snowflake/snowflake-arctic-embed-m-long`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	768	137.0M	522.0 MB	2024-04-12	eng-Latn

Citation

@article{merrick2024embedding,
      title={Embedding And Clustering Your Data Can Improve Contrastive Pretraining},
      author={Merrick, Luke},
      journal={arXiv preprint arXiv:2407.18887},
      year={2024},
      eprint={2407.18887},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2407.18887}
}

`Snowflake/snowflake-arctic-embed-m-v1.5`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	415.0 MB	2024-07-08	eng-Latn

Citation

@article{merrick2024embedding,
      title={Embedding And Clustering Your Data Can Improve Contrastive Pretraining},
      author={Merrick, Luke},
      journal={arXiv preprint arXiv:2407.18887},
      year={2024},
      eprint={2407.18887},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2407.18887}
}

`Snowflake/snowflake-arctic-embed-m-v2.0`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	305.0M	1.1 GB	2024-12-04	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (74)

Citation

@article{yu2024arctic,
      title={Arctic-Embed 2.0: Multilingual Retrieval Without Compromise},
      author={Yu, Puxuan and Merrick, Luke and Nuti, Gaurav and Campos, Daniel},
      journal={arXiv preprint arXiv:2412.04506},
      year={2024},
      eprint={2412.04506},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2412.04506}
}

`Snowflake/snowflake-arctic-embed-s`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	32.2M	127.0 MB	2024-04-12	eng-Latn

Citation

@article{merrick2024embedding,
      title={Embedding And Clustering Your Data Can Improve Contrastive Pretraining},
      author={Merrick, Luke},
      journal={arXiv preprint arXiv:2407.18887},
      year={2024},
      eprint={2407.18887},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2407.18887}
}

`Snowflake/snowflake-arctic-embed-xs`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	22.6M	86.0 MB	2024-07-08	eng-Latn

Citation

@article{merrick2024embedding,
      title={Embedding And Clustering Your Data Can Improve Contrastive Pretraining},
      author={Merrick, Luke},
      journal={arXiv preprint arXiv:2407.18887},
      year={2024},
      eprint={2407.18887},
      archivePrefix={arXiv},
      url={https://arxiv.org/abs/2407.18887}
}

`Tarka-AIR/Tarka-Embedding-150M-V1`¶

License: gemma

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	768	155.7M	576.0 MB	2025-11-04	arb-Arab, deu-Latn, eng-Latn, fra-Latn, jpn-Jpan, ... (8)

Citation

@misc{tarka_ai_research_2025,
    author       = { Tarka AI Research },
    title        = { Tarka-Embedding-150M-V1 (Revision c5f4f43) },
    year         = 2025,
    url          = { https://huggingface.co/Tarka-AIR/Tarka-Embedding-150M-V1 },
    doi          = { 10.57967/hf/6875 },
    publisher    = { Hugging Face }
}

`Tarka-AIR/Tarka-Embedding-350M-V1`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
128.0K	1024	354.5M	676.0 MB	2025-11-11	arb-Arab, deu-Latn, eng-Latn, fra-Latn, jpn-Jpan, ... (8)

Citation

@misc{tarka_ai_research_2025,
    author       = { Tarka AI Research },
    title        = { Tarka-Embedding-350M-V1 (Revision f4b5de8) },
    year         = 2025,
    url          = { https://huggingface.co/Tarka-AIR/Tarka-Embedding-350M-V1 },
    doi          = { 10.57967/hf/6979 },
    publisher    = { Hugging Face }
}

`TencentBAC/Conan-embedding-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	3584	not specified	not specified	2025-04-10	eng-Latn, zho-Hans

`VPLabs/SearchMap_Preview`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	4096	435.0M	1.6 GB	2025-03-05	eng-Latn

Citation

@misc{vectorpath2025searchmap,
  title={SearchMap: Conversational E-commerce Search Embedding Model},
  author={VectorPath Research Team},
  year={2025},
  publisher={Hugging Face},
  journal={HuggingFace Model Hub},
}

`WhereIsAI/UAE-Large-V1`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2023-12-04	eng-Latn

Citation

    @article{li2023angle,
      title={AnglE-optimized Text Embeddings},
      author={Li, Xianming and Li, Jing},
      journal={arXiv preprint arXiv:2309.12871},
      year={2023}
    }

`ai-forever/FRIDA`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1536	823.0M	3.1 GB	2024-12-29	rus-Cyrl

`ai-forever/ru-en-RoSBERTa`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	404.0M	1.5 GB	2024-07-29	rus-Cyrl

Citation

@misc{snegirev2024russianfocusedembeddersexplorationrumteb,
      title={The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design},
      author={Artem Snegirev and Maria Tikhonova and Anna Maksimova and Alena Fenogenova and Alexander Abramov},
      year={2024},
      eprint={2408.12503},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2408.12503},
    }

`ai-sage/Giga-Embeddings-instruct`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.1K	2048	3.2B	12.6 GB	2025-09-23	eng-Latn, rus-Cyrl

`annamodels/LGAI-Embedding-Preview`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2025-06-11	eng-Latn

Citation

@misc{choi2025lgaiembeddingpreviewtechnicalreport,
      title={LGAI-EMBEDDING-Preview Technical Report},
      author={Jooyoung Choi and Hyun Kim and Hansol Jang and Changwook Jun and Kyunghoon Bae and Hyewon Choi and Stanley Jungkyu Choi and Honglak Lee and Chulmin Yun},
      year={2025},
      eprint={2506.07438},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.07438},
}

`bedrock/cohere-embed-english-v3`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	not specified	not specified	2023-11-02	eng-Latn

`bedrock/cohere-embed-multilingual-v3`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	not specified	not specified	2023-11-02	afr-Latn, amh-Ethi, ara-Arab, asm-Beng, aze-Latn, ... (111)

`bflhc/MoD-Embedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	2560	4.0B	7.5 GB	2025-12-14	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

Citation

@misc{mod-embedding-2025,
  title={MoD-Embedding: A Fine-tuned Multilingual Text Embedding Model},
  author={MoD Team},
  year={2025},
  url={https://huggingface.co/bflhc/MoD-Embedding}
}

`bflhc/Octen-Embedding-8B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.6B	14.1 GB	2025-12-23	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

Citation

@misc{octen-embedding-2025,
  title={Octen-Embedding-8B: A Fine-tuned Multilingual Text Embedding Model},
  author={Octen Team},
  year={2025},
  url={https://huggingface.co/bflhc/bflhc/Octen-Embedding-8B}
}

`castorini/repllama-v1-7b-lora-passage`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.1K	4096	7.0M	27.0 MB	2023-10-11	eng-Latn

Citation

@article{rankllama,
      title={Fine-Tuning LLaMA for Multi-Stage Text Retrieval},
      author={Xueguang Ma and Liang Wang and Nan Yang and Furu Wei and Jimmy Lin},
      year={2023},
      journal={arXiv:2310.08319},
}

`cl-nagoya/ruri-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	111.2M	212.0 MB	2024-08-28	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-base-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	111.2M	424.0 MB	2024-12-05	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-large`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	337.4M	644.0 MB	2024-08-28	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-large-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	337.4M	1.3 GB	2024-12-06	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-small`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	68.1M	130.0 MB	2024-08-28	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-small-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	68.1M	260.0 MB	2024-12-05	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-v3-130m`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	512	132.1M	504.0 MB	2025-04-09	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-v3-30m`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	256	36.7M	140.0 MB	2025-04-07	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-v3-310m`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	314.6M	1.2 GB	2025-04-09	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`cl-nagoya/ruri-v3-70m`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	256	36.7M	140.0 MB	2025-04-09	jpn-Jpan

Citation

@misc{Ruri,
  title={{Ruri: Japanese General Text Embeddings}},
  author={Hayato Tsukagoshi and Ryohei Sasano},
  year={2024},
  eprint={2409.07737},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2409.07737},
}

`clips/e5-base-trm-nl`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	124.4M	237.0 MB	2025-09-23	nld-Latn

Citation

@misc{banar2025mtebnle5nlembeddingbenchmark,
  archiveprefix = {arXiv},
  author = {Nikolay Banar and Ehsan Lotfi and Jens Van Nooten and Cristina Arhiliuc and Marija Kliocaite and Walter Daelemans},
  eprint = {2509.12340},
  primaryclass = {cs.CL},
  title = {MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch},
  url = {https://arxiv.org/abs/2509.12340},
  year = {2025},
}

`clips/e5-large-trm-nl`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	355.0M	1.3 GB	2025-09-23	nld-Latn

Citation

@misc{banar2025mtebnle5nlembeddingbenchmark,
  archiveprefix = {arXiv},
  author = {Nikolay Banar and Ehsan Lotfi and Jens Van Nooten and Cristina Arhiliuc and Marija Kliocaite and Walter Daelemans},
  eprint = {2509.12340},
  primaryclass = {cs.CL},
  title = {MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch},
  url = {https://arxiv.org/abs/2509.12340},
  year = {2025},
}

`clips/e5-small-trm-nl`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	40.8M	78.0 MB	2025-09-23	nld-Latn

Citation

@misc{banar2025mtebnle5nlembeddingbenchmark,
  archiveprefix = {arXiv},
  author = {Nikolay Banar and Ehsan Lotfi and Jens Van Nooten and Cristina Arhiliuc and Marija Kliocaite and Walter Daelemans},
  eprint = {2509.12340},
  primaryclass = {cs.CL},
  title = {MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch},
  url = {https://arxiv.org/abs/2509.12340},
  year = {2025},
}

`codefuse-ai/C2LLM-0.5B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	896	497.3M	948.0 MB	2025-12-22	eng-Latn, go-Code, java-Code, javascript-Code, php-Code, ... (8)

`codefuse-ai/C2LLM-7B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	3584	7.7B	14.3 GB	2025-12-22	eng-Latn, go-Code, java-Code, javascript-Code, php-Code, ... (8)

`codefuse-ai/F2LLM-0.6B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	595.8M	1.1 GB	2025-09-18	eng-Latn

Citation

@article{2025F2LLM,
    title={F2LLM Technical Report: Matching SOTA Embedding Performance with 6 Million Open-Source Data},
    author={Ziyin Zhang and Zihan Liao and Hang Yu and Peng Di and Rui Wang},
    journal={CoRR},
    volume={abs/2510.02294},
    year={2025},
    url={https://doi.org/10.48550/arXiv.2510.02294},
    doi={10.48550/ARXIV.2510.02294},
    eprinttype={arXiv},
    eprint={2510.02294}
}

`codefuse-ai/F2LLM-1.7B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	2560	1.7B	3.2 GB	2025-09-18	eng-Latn

Citation

@article{2025F2LLM,
    title={F2LLM Technical Report: Matching SOTA Embedding Performance with 6 Million Open-Source Data},
    author={Ziyin Zhang and Zihan Liao and Hang Yu and Peng Di and Rui Wang},
    journal={CoRR},
    volume={abs/2510.02294},
    year={2025},
    url={https://doi.org/10.48550/arXiv.2510.02294},
    doi={10.48550/ARXIV.2510.02294},
    eprinttype={arXiv},
    eprint={2510.02294}
}

`codefuse-ai/F2LLM-4B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	2560	4.0B	7.5 GB	2025-09-18	eng-Latn

Citation

@article{2025F2LLM,
    title={F2LLM Technical Report: Matching SOTA Embedding Performance with 6 Million Open-Source Data},
    author={Ziyin Zhang and Zihan Liao and Hang Yu and Peng Di and Rui Wang},
    journal={CoRR},
    volume={abs/2510.02294},
    year={2025},
    url={https://doi.org/10.48550/arXiv.2510.02294},
    doi={10.48550/ARXIV.2510.02294},
    eprinttype={arXiv},
    eprint={2510.02294}
}

`deepvk/USER-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	427.0M	473.0 MB	2024-06-10	rus-Cyrl

Citation

@misc{deepvk2024user,
        title={USER: Universal Sentence Encoder for Russian},
        author={Malashenko, Boris and  Zemerov, Anton and Spirin, Egor},
        url={https://huggingface.co/datasets/deepvk/USER-base},
        publisher={Hugging Face}
        year={2024},
    }

`deepvk/USER2-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	149.0M	568.0 MB	2025-04-19	rus-Cyrl

Citation

@misc{deepvk2025user,
    title={USER2},
    author={Malashenko, Boris and Spirin, Egor and Sokolov Andrey},
    url={https://huggingface.co/deepvk/USER2-base},
    publisher={Hugging Face},
    year={2025},
}

`deepvk/USER2-small`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	384	34.4M	131.0 MB	2025-04-19	rus-Cyrl

Citation

@misc{deepvk2025user,
    title={USER2},
    author={Malashenko, Boris and Spirin, Egor and Sokolov Andrey},
    url={https://huggingface.co/deepvk/USER2-small},
    publisher={Hugging Face},
    year={2025},
}

`emillykkejensen/EmbeddingGemma-Scandi-300m`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	768	307.6M	578.0 MB	2025-10-17	dan-Latn, nno-Latn, nob-Latn, nor-Latn, swe-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`emillykkejensen/Qwen3-Embedding-Scandi-0.6B`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	1024	595.8M	2.2 GB	2025-10-17	dan-Latn, nno-Latn, nob-Latn, nor-Latn, swe-Latn

`emillykkejensen/mmBERTscandi-base-embedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	306.9M	1.1 GB	2025-10-17	dan-Latn, nno-Latn, nob-Latn, nor-Latn, swe-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`fyaronskiy/english_code_retriever`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	149.0M	568.0 MB	2025-07-10	eng-Latn

`google/embeddinggemma-300m`¶

License: gemma

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	768	307.6M	1.1 GB	2025-09-04	arb-Arab, ben-Beng, deu-Latn, eng-Latn, fin-Latn, ... (19)

Citation

@misc{vera2025embeddinggemmapowerfullightweighttext,
      title={EmbeddingGemma: Powerful and Lightweight Text Representations},
      author={Henrique Schechter Vera and Sahil Dua and Biao Zhang and Daniel Salz and Ryan Mullins and Sindhu Raghuram Panyam and Sara Smoot and Iftekhar Naim and Joe Zou and Feiyang Chen and Daniel Cer and Alice Lisak and Min Choi and Lucas Gonzalez and Omar Sanseviero and Glenn Cameron and Ian Ballantyne and Kat Black and Kaifeng Chen and Weiyi Wang and Zhe Li and Gus Martins and Jinhyuk Lee and Mark Sherwood and Juyeong Ji and Renjie Wu and Jingxiao Zheng and Jyotinder Singh and Abheesht Sharma and Divyashree Sreepathihalli and Aashi Jain and Adham Elarabawy and AJ Co and Andreas Doumanoglou and Babak Samari and Ben Hora and Brian Potetz and Dahun Kim and Enrique Alfonseca and Fedor Moiseev and Feng Han and Frank Palma Gomez and Gustavo Hernández Ábrego and Hesen Zhang and Hui Hui and Jay Han and Karan Gill and Ke Chen and Koert Chen and Madhuri Shanbhogue and Michael Boratko and Paul Suganthan and Sai Meher Karthik Duddu and Sandeep Mariserla and Setareh Ariafar and Shanfeng Zhang and Shijie Zhang and Simon Baumgartner and Sonam Goenka and Steve Qiu and Tanmaya Dabral and Trevor Walker and Vikram Rao and Waleed Khawaja and Wenlei Zhou and Xiaoqi Ren and Ye Xia and Yichang Chen and Yi-Ting Chen and Zhe Dong and Zhongli Ding and Francesco Visin and Gaël Liu and Jiageng Zhang and Kathleen Kenealy and Michelle Casbon and Ravin Kumar and Thomas Mesnard and Zach Gleicher and Cormac Brick and Olivier Lacombe and Adam Roberts and Qin Yin and Yunhsuan Sung and Raphael Hoffmann and Tris Warkentin and Armand Joulin and Tom Duerig and Mojtaba Seyedhosseini},
      year={2025},
      eprint={2509.20354},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2509.20354},
}

`google/gemini-embedding-001`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	3072	not specified	not specified	2025-03-07	arb-Arab, ben-Beng, deu-Latn, eng-Latn, fin-Latn, ... (19)

`google/text-embedding-004`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	768	not specified	not specified	2024-05-14	eng-Latn

`google/text-embedding-005`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	768	not specified	not specified	2024-11-18	eng-Latn

`google/text-multilingual-embedding-002`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	768	not specified	not specified	2024-05-14	arb-Arab, ben-Beng, deu-Latn, eng-Latn, fin-Latn, ... (19)

`infgrad/Jasper-Token-Compression-600M`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	2048	595.8M	2.2 GB	2025-11-14	eng-Latn, zho-Hans

Citation

@misc{zhang2025jaspertokencompression600mtechnicalreport,
      title={Jasper-Token-Compression-600M Technical Report},
      author={Dun Zhang and Ziyang Zeng and Yudong Zhou and Shuyang Lu},
      year={2025},
      eprint={2511.14405},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2511.14405},
}

`infly/inf-retriever-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	3584	7.1B	13.2 GB	2024-12-24	eng-Latn, zho-Hans

Citation

@misc{infly-ai_2025,
  author       = {Junhan Yang and Jiahe Wan and Yichen Yao and Wei Chu and Yinghui Xu and Yuan Qi},
  title        = {inf-retriever-v1 (Revision 5f469d7)},
  year         = 2025,
  url          = {https://huggingface.co/infly/inf-retriever-v1},
  doi          = {10.57967/hf/4262},
  publisher    = {Hugging Face}
}

`infly/inf-retriever-v1-1.5b`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	1536	1.5B	2.9 GB	2025-02-08	eng-Latn, zho-Hans

Citation

@misc{infly-ai_2025,
  author       = {Junhan Yang and Jiahe Wan and Yichen Yao and Wei Chu and Yinghui Xu and Yuan Qi},
  title        = {inf-retriever-v1 (Revision 5f469d7)},
  year         = 2025,
  url          = {https://huggingface.co/infly/inf-retriever-v1},
  doi          = {10.57967/hf/4262},
  publisher    = {Hugging Face}
}

`intfloat/e5-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	418.0 MB	2022-12-26	eng-Latn

Citation

@article{wang2022text,
  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2212.03533},
  year={2022}
}

`intfloat/e5-base-v2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	418.0 MB	2024-02-08	eng-Latn

Citation

@article{wang2022text,
  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2212.03533},
  year={2022}
}

`intfloat/e5-large`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2022-12-26	eng-Latn

Citation

@article{wang2022text,
  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2212.03533},
  year={2022}
}

`intfloat/e5-large-v2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	335.0M	1.2 GB	2024-02-08	eng-Latn

Citation

@article{wang2022text,
  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2212.03533},
  year={2022}
}

`intfloat/e5-mistral-7b-instruct`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	13.2 GB	2024-02-08	deu-Latn, eng-Latn, fra-Latn, ita-Latn, spa-Latn

Citation

    @article{wang2023improving,
      title={Improving Text Embeddings with Large Language Models},
      author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu},
      journal={arXiv preprint arXiv:2401.00368},
      year={2023}
    }

    @article{wang2022text,
      title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
      author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
      journal={arXiv preprint arXiv:2212.03533},
      year={2022}
    }

`intfloat/e5-small`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	33.0M	127.0 MB	2024-02-08	eng-Latn

Citation

@article{wang2022text,
  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2212.03533},
  year={2022}
}

`intfloat/e5-small-v2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	33.0M	127.0 MB	2024-02-08	eng-Latn

Citation

@article{wang2022text,
  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2212.03533},
  year={2022}
}

`intfloat/multilingual-e5-base`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	278.0M	1.0 GB	2024-02-08	afr-Latn, amh-Latn, ara-Latn, asm-Latn, aze-Latn, ... (99)

Citation

@article{wang2024multilingual,
  title={Multilingual E5 Text Embeddings: A Technical Report},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2402.05672},
  year={2024}
}

`intfloat/multilingual-e5-large`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	560.0M	2.1 GB	2024-02-08	afr-Latn, amh-Latn, ara-Latn, asm-Latn, aze-Latn, ... (99)

Citation

@article{wang2024multilingual,
  title={Multilingual E5 Text Embeddings: A Technical Report},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2402.05672},
  year={2024}
}

`intfloat/multilingual-e5-large-instruct`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	560.0M	1.0 GB	2024-02-08	afr-Latn, amh-Latn, ara-Latn, asm-Latn, aze-Latn, ... (99)

Citation

@article{wang2024multilingual,
      title={Multilingual E5 Text Embeddings: A Technical Report},
      author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu},
      journal={arXiv preprint arXiv:2402.05672},
      year={2024}
    }

`intfloat/multilingual-e5-small`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	118.0M	449.0 MB	2024-02-08	afr-Latn, amh-Latn, ara-Latn, asm-Latn, aze-Latn, ... (99)

Citation

@article{wang2024multilingual,
  title={Multilingual E5 Text Embeddings: A Technical Report},
  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Yang, Linjun and Majumder, Rangan and Wei, Furu},
  journal={arXiv preprint arXiv:2402.05672},
  year={2024}
}

`jinaai/jina-embeddings-v3`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	572.0M	1.1 GB	2024-09-18	afr-Latn, amh-Latn, ara-Latn, asm-Latn, aze-Latn, ... (99)

Citation

    @misc{sturua2024jinaembeddingsv3multilingualembeddingstask,
      title={jina-embeddings-v3: Multilingual Embeddings With Task LoRA},
      author={Saba Sturua and Isabelle Mohr and Mohammad Kalim Akram and Michael Günther and Bo Wang and Markus Krimmel and Feng Wang and Georgios Mastrapas and Andreas Koukounas and Andreas Koukounas and Nan Wang and Han Xiao},
      year={2024},
      eprint={2409.10173},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2409.10173},
    }

`jxm/cde-small-v1`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	281.0M	1.0 GB	2024-09-24	eng-Latn

Citation

@misc{morris2024contextualdocumentembeddings,
    title={Contextual Document Embeddings},
    author={John X. Morris and Alexander M. Rush},
    year={2024},
    eprint={2410.02525},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2410.02525},
}

`jxm/cde-small-v2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	306.0M	1.1 GB	2025-01-13	eng-Latn

Citation

@misc{morris2024contextualdocumentembeddings,
    title={Contextual Document Embeddings},
    author={John X. Morris and Alexander M. Rush},
    year={2024},
    eprint={2410.02525},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2410.02525},
}

`llamaindex/vdr-2b-multi-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	1536	2.0B	4.1 GB	2024-01-08	deu-Latn, eng-Latn, fra-Latn, ita-Latn, spa-Latn

`manveertamber/cadet-embed-base-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.0M	418.0 MB	2025-05-11	eng-Latn

Citation

@article{tamber2025conventionalcontrastivelearningfalls,
    title={Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data},
    author={Manveer Singh Tamber and Suleman Kazi and Vivek Sourabh and Jimmy Lin},
    journal={arXiv:2505.19274},
    year={2025}
}

`mixedbread-ai/mxbai-embed-2d-large-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	335.0M	not specified	2024-03-04	eng-Latn

`mixedbread-ai/mxbai-embed-large-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	639.0 MB	2024-03-07	eng-Latn

Citation

    @online{emb2024mxbai,
      title={Open Source Strikes Bread - New Fluffy Embeddings Model},
      author={Sean Lee and Aamir Shakir and Darius Koenig and Julius Lipp},
      year={2024},
      url={https://www.mixedbread.ai/blog/mxbai-embed-large-v1},
    }

    @article{li2023angle,
      title={AnglE-optimized Text Embeddings},
      author={Li, Xianming and Li, Jing},
      journal={arXiv preprint arXiv:2309.12871},
      year={2023}
    }

`mixedbread-ai/mxbai-embed-xsmall-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	24.1M	not specified	2024-08-13	eng-Latn

Citation

@online{xsmall2024mxbai,
  title={Every Byte Matters: Introducing mxbai-embed-xsmall-v1},
  author={Sean Lee and Julius Lipp and Rui Huang and Darius Koenig},
  year={2024},
  url={https://www.mixedbread.ai/blog/mxbai-embed-xsmall-v1},
}

`nomic-ai/modernbert-embed-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	149.0M	568.0 MB	2024-12-29	eng-Latn

Citation

@misc{nussbaum2024nomic,
      title={Nomic Embed: Training a Reproducible Long Context Text Embedder},
      author={Zach Nussbaum and John X. Morris and Brandon Duderstadt and Andriy Mulyar},
      year={2024},
      eprint={2402.01613},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`nomic-ai/nomic-embed-text-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	not specified	522.0 MB	2024-01-31	eng-Latn

Citation

@misc{nussbaum2024nomic,
      title={Nomic Embed: Training a Reproducible Long Context Text Embedder},
      author={Zach Nussbaum and John X. Morris and Brandon Duderstadt and Andriy Mulyar},
      year={2024},
      eprint={2402.01613},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`nomic-ai/nomic-embed-text-v1-ablated`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	not specified	not specified	2024-01-15	eng-Latn

`nomic-ai/nomic-embed-text-v1-unsupervised`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	not specified	not specified	2024-01-15	eng-Latn

`nomic-ai/nomic-embed-text-v1.5`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	137.0M	522.0 MB	2024-02-10	eng-Latn

Citation

@misc{nussbaum2024nomic,
      title={Nomic Embed: Training a Reproducible Long Context Text Embedder},
      author={Zach Nussbaum and John X. Morris and Brandon Duderstadt and Andriy Mulyar},
      year={2024},
      eprint={2402.01613},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`nomic-ai/nomic-embed-text-v2-moe`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	475.3M	1.8 GB	2025-02-07	amh-Ethi, arb-Arab, bel-Cyrl, ben-Beng, bul-Cyrl, ... (98)

Citation

@misc{nussbaum2025trainingsparsemixtureexperts,
      title={Training Sparse Mixture Of Experts Text Embedding Models},
      author={Zach Nussbaum and Brandon Duderstadt},
      year={2025},
      eprint={2502.07972},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2502.07972},
}

`nvidia/NV-Embed-v1`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.8B	14.6 GB	2024-09-13	eng-Latn

Citation

@misc{moreira2025nvretrieverimprovingtextembedding,
      title={NV-Retriever: Improving text embedding models with effective hard-negative mining},
      author={Gabriel de Souza P. Moreira and Radek Osmulski and Mengyao Xu and Ronay Ak and Benedikt Schifferer and Even Oldridge},
      year={2025},
      eprint={2407.15831},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2407.15831}
}

`nvidia/NV-Embed-v2`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.8B	14.6 GB	2024-09-09	eng-Latn

Citation

@misc{moreira2025nvretrieverimprovingtextembedding,
      title={NV-Retriever: Improving text embedding models with effective hard-negative mining},
      author={Gabriel de Souza P. Moreira and Radek Osmulski and Mengyao Xu and Ronay Ak and Benedikt Schifferer and Even Oldridge},
      year={2025},
      eprint={2407.15831},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2407.15831}
}

`nvidia/llama-embed-nemotron-8b`¶

License: https://huggingface.co/nvidia/llama-embed-nemotron-8b/blob/main/LICENSE

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.5B	28.0 GB	2025-10-23	afr-Latn, amh-Ethi, ara-Arab, arq-Arab, ary-Arab, ... (66)

Citation

@misc{moreira2025nvretrieverimprovingtextembedding,
      title={NV-Retriever: Improving text embedding models with effective hard-negative mining},
      author={Gabriel de Souza P. Moreira and Radek Osmulski and Mengyao Xu and Ronay Ak and Benedikt Schifferer and Even Oldridge},
      year={2025},
      eprint={2407.15831},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2407.15831}
}

`opensearch-project/opensearch-neural-sparse-encoding-doc-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	30522	133.0M	507.0 MB	2024-03-07	eng-Latn

`opensearch-project/opensearch-neural-sparse-encoding-doc-v2-distill`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	30522	67.0M	267.0 MB	2024-07-17	eng-Latn

`opensearch-project/opensearch-neural-sparse-encoding-doc-v2-mini`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	30522	22.7M	86.0 MB	2024-07-18	eng-Latn

`opensearch-project/opensearch-neural-sparse-encoding-doc-v3-distill`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	30522	67.0M	267.0 MB	2025-03-28	eng-Latn

`opensearch-project/opensearch-neural-sparse-encoding-doc-v3-gte`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	30522	137.4M	549.0 MB	2025-06-18	eng-Latn

`samaya-ai/RepLLaMA-reproduced`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.1K	4096	7.0M	27.0 MB	2024-09-15	eng-Latn

Citation

@article{rankllama,
      title={Fine-Tuning LLaMA for Multi-Stage Text Retrieval},
      author={Xueguang Ma and Liang Wang and Nan Yang and Furu Wei and Jimmy Lin},
      year={2023},
      journal={arXiv:2310.08319},
}

`samaya-ai/promptriever-llama2-7b-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.1K	4096	7.0B	26.1 GB	2024-09-15	eng-Latn

Citation

@article{weller2024promptriever,
      title={Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models},
      author={Orion Weller and Benjamin Van Durme and Dawn Lawrie and Ashwin Paranjape and Yuhao Zhang and Jack Hessel},
      year={2024},
      eprint={2409.11136},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2409.11136},
}

`samaya-ai/promptriever-llama3.1-8b-instruct-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	4096	8.0B	29.8 GB	2024-09-15	eng-Latn

Citation

@article{weller2024promptriever,
      title={Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models},
      author={Orion Weller and Benjamin Van Durme and Dawn Lawrie and Ashwin Paranjape and Yuhao Zhang and Jack Hessel},
      year={2024},
      eprint={2409.11136},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2409.11136},
}

`samaya-ai/promptriever-llama3.1-8b-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	4096	8.0B	29.8 GB	2024-09-15	eng-Latn

Citation

@article{weller2024promptriever,
      title={Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models},
      author={Orion Weller and Benjamin Van Durme and Dawn Lawrie and Ashwin Paranjape and Yuhao Zhang and Jack Hessel},
      year={2024},
      eprint={2409.11136},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2409.11136},
}

`samaya-ai/promptriever-mistral-v0.1-7b-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.1K	4096	7.0B	26.1 GB	2024-09-15	eng-Latn

Citation

@article{weller2024promptriever,
      title={Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models},
      author={Orion Weller and Benjamin Van Durme and Dawn Lawrie and Ashwin Paranjape and Yuhao Zhang and Jack Hessel},
      year={2024},
      eprint={2409.11136},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2409.11136},
}

`sbintuitions/sarashina-embedding-v2-1b`¶

License: https://huggingface.co/sbintuitions/sarashina-embedding-v2-1b/blob/main/LICENSE

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1792	1.2B	4.6 GB	2025-07-30	jpn-Jpan

`sergeyzh/BERTA`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	128.0M	489.0 MB	2025-03-10	rus-Cyrl

`sergeyzh/rubert-mini-frida`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	312	32.3M	123.0 MB	2025-03-02	rus-Cyrl

`tencent/KaLM-Embedding-Gemma3-12B-2511`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	3840	11.8B	43.8 GB	2025-11-06	not specified

Citation

@misc{zhao2025kalmembeddingv2,
      title={KaLM-Embedding-V2: Superior Training Techniques and Data Inspire A Versatile Embedding Model}, 
      author={Xinping Zhao and Xinshuo Hu and Zifei Shan and Shouzheng Huang and Yao Zhou and Xin Zhang and Zetian Sun and Zhenyu Liu and Dongfang Li and Xinyuan Wei and Youcheng Pan and Yang Xiang and Meishan Zhang and Haofen Wang and Jun Yu and Baotian Hu and Min Zhang},
      year={2025},
      eprint={2506.20923},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.20923}, 
}

@misc{hu2025kalmembedding,
      title={KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model}, 
      author={Xinshuo Hu and Zifei Shan and Xinping Zhao and Zetian Sun and Zhenyu Liu and Dongfang Li and Shaolin Ye and Xinyuan Wei and Qian Chen and Baotian Hu and Haofen Wang and Jun Yu and Min Zhang},
      year={2025},
      eprint={2501.01028},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2501.01028}, 
}

`tencent/Youtu-Embedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	2048	2.7B	not specified	2025-09-28	zho-Hans

Citation

@misc{zhang2025codiemb,
  title={CoDiEmb: A Collaborative yet Distinct Framework for Unified Representation Learning in Information Retrieval and Semantic Textual Similarity},
  author={Zhang, Bowen and Song, Zixin and Chen, Chunquan and Zhang, Qian-Wen and Yin, Di and Sun, Xing},
  year={2025},
  eprint={2508.11442},
  archivePrefix={arXiv},
  url={https://arxiv.org/abs/2508.11442},
}

`voyageai/voyage-2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.0K	1024	not specified	not specified	2023-10-29	not specified

`voyageai/voyage-3`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2024-09-18	not specified

`voyageai/voyage-3-large`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2025-01-07	not specified

`voyageai/voyage-3-lite`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	512	not specified	not specified	2024-09-18	not specified

`voyageai/voyage-3-m-exp`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	2048	6.9B	not specified	2025-01-08	eng-Latn

`voyageai/voyage-3.5`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2025-01-21	not specified

`voyageai/voyage-3.5 (output_dtype=binary)`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2025-01-21	not specified

`voyageai/voyage-3.5 (output_dtype=int8)`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2025-01-21	not specified

`voyageai/voyage-code-2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
16.0K	1536	not specified	not specified	2024-01-23	not specified

`voyageai/voyage-code-3`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2024-12-04	not specified

`voyageai/voyage-finance-2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2024-05-30	not specified

`voyageai/voyage-large-2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
16.0K	1536	not specified	not specified	2023-10-29	not specified

`voyageai/voyage-large-2-instruct`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
16.0K	1024	not specified	not specified	2024-05-05	not specified

`voyageai/voyage-law-2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
16.0K	1024	not specified	not specified	2024-04-15	not specified

`voyageai/voyage-multilingual-2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.0K	1024	not specified	not specified	2024-06-10	not specified

`yibinlei/LENS-d4000`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4000	7.1B	26.5 GB	2025-01-17	not specified

Citation

@article{lei2025lens,
  title={Enhancing Lexicon-Based Text Embeddings with Large Language Models},
  author={Lei, Yibin and Shen, Tao and Cao, Yu and Yates, Andrew},
  journal={arXiv preprint arXiv:2501.09749},
  year={2025}
}

`yibinlei/LENS-d8000`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	8000	7.1B	26.5 GB	2025-01-17	not specified

Citation

@article{lei2025lens,
  title={Enhancing Lexicon-Based Text Embeddings with Large Language Models},
  author={Lei, Yibin and Shen, Tao and Cao, Yu and Yates, Andrew},
  journal={arXiv preprint arXiv:2501.09749},
  year={2025}
}

`zeta-alpha-ai/Zeta-Alpha-E5-Mistral`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	13.2 GB	2024-08-30	eng-Latn

Non-instruction Model¶

`AITeamVN/Vietnamese_Embedding`¶

License: cc-by-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	568.0M	2.1 GB	2024-03-17	vie-Latn

Citation

@misc{Vietnamese_Embedding,
  title={Vietnamese_Embedding: Embedding model in Vietnamese language.},
  author={Nguyen Nho Trung, Nguyen Nhat Quang, Nguyen Van Huy},
  year={2025},
  publisher={Huggingface},
}

`Alibaba-NLP/gte-base-en-v1.5`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	137.0M	not specified	2024-06-20	eng-Latn

Citation

@misc{zhang2024mgte,
  title={mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval}, 
  author={Xin Zhang and Yanzhao Zhang and Dingkun Long and Wen Xie and Ziqi Dai and Jialong Tang and Huan Lin and Baosong Yang and Pengjun Xie and Fei Huang and Meishan Zhang and Wenjie Li and Min Zhang},
  year={2024},
  eprint={2407.19669},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2407.19669}, 
}
@misc{li2023gte,
  title={Towards General Text Embeddings with Multi-stage Contrastive Learning}, 
  author={Zehan Li and Xin Zhang and Yanzhao Zhang and Dingkun Long and Pengjun Xie and Meishan Zhang},
  year={2023},
  eprint={2308.03281},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2308.03281}, 
}

`Alibaba-NLP/gte-modernbert-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	149.0M	284.0 MB	2025-01-21	eng-Latn

Citation

@inproceedings{zhang2024mgte,
  title={mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval},
  author={Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Wen and Dai, Ziqi and Tang, Jialong and Lin, Huan and Yang, Baosong and Xie, Pengjun and Huang, Fei and others},
  booktitle={Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track},
  pages={1393--1412},
  year={2024}
}

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`Alibaba-NLP/gte-multilingual-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	305.0M	582.0 MB	2024-07-20	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

Citation

@inproceedings{zhang2024mgte,
  title={mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval},
  author={Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Wen and Dai, Ziqi and Tang, Jialong and Lin, Huan and Yang, Baosong and Xie, Pengjun and Huang, Fei and others},
  booktitle={Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track},
  pages={1393--1412},
  year={2024}
}

`BAAI/bge-en-icl`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	4096	7.1B	26.5 GB	2024-07-25	eng-Latn

Citation

    @misc{li2024makingtextembeddersfewshot,
      title={Making Text Embedders Few-Shot Learners},
      author={Chaofan Li and MingHao Qin and Shitao Xiao and Jianlyu Chen and Kun Luo and Yingxia Shao and Defu Lian and Zheng Liu},
      year={2024},
      eprint={2409.15700},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2409.15700},
}

`BAAI/bge-m3`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	568.0M	2.1 GB	2024-06-28	afr-Latn, amh-Ethi, ast-Latn, azj-Latn, azj-Latn, ... (29)

Citation

@misc{bge-m3,
      title={BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation}, 
      author={Jianlv Chen and Shitao Xiao and Peitian Zhang and Kun Luo and Defu Lian and Zheng Liu},
      year={2024},
      eprint={2402.03216},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-m3-unsupervised`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	568.0M	2.1 GB	2024-01-30	afr-Latn, amh-Ethi, ast-Latn, azj-Latn, azj-Latn, ... (29)

Citation

@misc{bge-m3,
      title={BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation}, 
      author={Jianlv Chen and Shitao Xiao and Peitian Zhang and Kun Luo and Defu Lian and Zheng Liu},
      year={2024},
      eprint={2402.03216},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`BAAI/bge-multilingual-gemma2`¶

License: https://ai.google.dev/gemma/terms

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	3584	9.2B	34.4 GB	2024-07-25	eng-Latn, fra-Latn, jpn-Jpan, jpn-Latn, kor-Hang, ... (7)

Citation

@misc{bge-m3,
      title={BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation}, 
      author={Jianlv Chen and Shitao Xiao and Peitian Zhang and Kun Luo and Defu Lian and Zheng Liu},
      year={2024},
      eprint={2402.03216},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}


@misc{bge_embedding,
      title={C-Pack: Packaged Resources To Advance General Chinese Embedding}, 
      author={Shitao Xiao and Zheng Liu and Peitian Zhang and Niklas Muennighoff},
      year={2023},
      eprint={2309.07597},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

BAAI/bge-reranker-v2-m3¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	2.1 GB	2024-06-24	ara-Arab, ben-Beng, dan-Latn, deu-Latn, eng-Latn, ... (32)

Citation

    @misc{li2023making,
      title={Making Large Language Models A Better Foundation For Dense Retrieval},
      author={Chaofan Li and Zheng Liu and Shitao Xiao and Yingxia Shao},
      year={2023},
      eprint={2312.15503},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
    }
    @misc{chen2024bge,
          title={BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation},
          author={Jianlv Chen and Shitao Xiao and Peitian Zhang and Kun Luo and Defu Lian and Zheng Liu},
          year={2024},
          eprint={2402.03216},
          archivePrefix={arXiv},
          primaryClass={cs.CL}
    }

`ByteDance/ListConRanker`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	401.0M	1.2 GB	2024-12-11	zho-Hans

Citation

@article{liu2025listconranker,
  title={ListConRanker: A Contrastive Text Reranker with Listwise Encoding},
  author={Liu, Junlong and Ma, Yue and Zhao, Ruihui and Zheng, Junhao and Ma, Qianli and Kang, Yangyang},
  journal={arXiv preprint arXiv:2501.07111},
  year={2025}
}

`Classical/Yinka`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	326.0M	1.2 GB	2024-01-09	zho-Hans

`DMetaSoul/Dmeta-embedding-zh-small`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
1.0K	768	74.2M	283.0 MB	2024-03-25	zho-Hans

`DMetaSoul/sbert-chinese-general-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	128	not specified	not specified	2022-03-25	zho-Hans

`DeepPavlov/distilrubert-small-cased-conversational`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	107.0M	408.0 MB	2022-06-28	rus-Cyrl

Citation

@misc{https://doi.org/10.48550/arxiv.2205.02340,
      doi = {10.48550/ARXIV.2205.02340},
      url = {https://arxiv.org/abs/2205.02340},
      author = {Kolesnikova, Alina and Kuratov, Yuri and Konovalov, Vasily and Burtsev, Mikhail},
      keywords = {Computation and Language (cs.CL), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
      title = {Knowledge Distillation of Russian Language Models with Reduction of Vocabulary},
      publisher = {arXiv},
      year = {2022},
      copyright = {arXiv.org perpetual, non-exclusive license}
    }

`DeepPavlov/rubert-base-cased`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	1.3B	4.8 GB	2020-03-04	rus-Cyrl

Citation

@misc{kuratov2019adaptationdeepbidirectionalmultilingual,
      title={Adaptation of Deep Bidirectional Multilingual Transformers for Russian Language},
      author={Yuri Kuratov and Mikhail Arkhipov},
      year={2019},
      eprint={1905.07213},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/1905.07213},
    }

`DeepPavlov/rubert-base-cased-sentence`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	107.0M	408.0 MB	2020-03-04	rus-Cyrl

`FacebookAI/xlm-roberta-base`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	278.0M	1.0 GB	2019-11-05	afr-Latn, amh-Latn, ara-Latn, asm-Latn, aze-Latn, ... (99)

Citation

@article{DBLP:journals/corr/abs-1911-02116,
  author    = {Alexis Conneau and
               Kartikay Khandelwal and
               Naman Goyal and
               Vishrav Chaudhary and
               Guillaume Wenzek and
               Francisco Guzm{'{a}}n and
               Edouard Grave and
               Myle Ott and
               Luke Zettlemoyer and
               Veselin Stoyanov},
  title     = {Unsupervised Cross-lingual Representation Learning at Scale},
  journal   = {CoRR},
  volume    = {abs/1911.02116},
  year      = {2019},
  url       = {http://arxiv.org/abs/1911.02116},
  eprinttype = {arXiv},
  eprint    = {1911.02116},
  timestamp = {Mon, 11 Nov 2019 18:38:09 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-02116.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

`FacebookAI/xlm-roberta-large`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	559.9M	2.1 GB	2019-11-05	afr-Latn, amh-Latn, ara-Latn, asm-Latn, aze-Latn, ... (99)

Citation

@article{DBLP:journals/corr/abs-1911-02116,
  author    = {Alexis Conneau and
               Kartikay Khandelwal and
               Naman Goyal and
               Vishrav Chaudhary and
               Guillaume Wenzek and
               Francisco Guzm{'{a}}n and
               Edouard Grave and
               Myle Ott and
               Luke Zettlemoyer and
               Veselin Stoyanov},
  title     = {Unsupervised Cross-lingual Representation Learning at Scale},
  journal   = {CoRR},
  volume    = {abs/1911.02116},
  year      = {2019},
  url       = {http://arxiv.org/abs/1911.02116},
  eprinttype = {arXiv},
  eprint    = {1911.02116},
  timestamp = {Mon, 11 Nov 2019 18:38:09 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1911-02116.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

`Gameselo/STS-multilingual-mpnet-base-v2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	278.0M	1.0 GB	2024-06-07	not specified

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`GreenNode/GreenNode-Embedding-Large-VN-Mixed-V1`¶

License: cc-by-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	568.0M	2.1 GB	2024-04-11	vie-Latn

`GreenNode/GreenNode-Embedding-Large-VN-V1`¶

License: cc-by-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	568.0M	2.1 GB	2024-04-11	vie-Latn

`HIT-TMG/KaLM-embedding-multilingual-mini-v1`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	896	494.0M	1.8 GB	2024-08-27	eng-Latn, zho-Hans

Citation

@article{hu2025kalm,
  title={KaLM-Embedding: Superior Training Data Brings A Stronger Embedding Model},
  author={Hu, Xinshuo and Shan, Zifei and Zhao, Xinping and Sun, Zetian and Liu, Zhenyu and Li, Dongfang and Ye, Shaolin and Wei, Xinyuan and Chen, Qian and Hu, Baotian and others},
  journal={arXiv preprint arXiv:2501.01028},
  year={2025}
}

`Haon-Chen/speed-embedding-7b-instruct`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	not specified	7.1B	13.2 GB	2024-10-31	eng-Latn

Citation

@article{chen2024little,
    title={Little Giants: Synthesizing High-Quality Embedding Data at Scale},
    author={Chen, Haonan and Wang, Liang and Yang, Nan and Zhu, Yutao and Zhao, Ziliang and Wei, Furu and Dou, Zhicheng},
    journal={arXiv preprint arXiv:2410.18634},
    year={2024}
}

`HooshvareLab/bert-base-parsbert-uncased`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	162.8M	621.0 MB	2021-05-19	fas-Arab

Citation

    @article{ParsBERT,
    title={ParsBERT: Transformer-based Model for Persian Language Understanding},
    author={Mehrdad Farahani, Mohammad Gharachorloo, Marzieh Farahani, Mohammad Manthouri},
    journal={ArXiv},
    year={2020},
    volume={abs/2005.12515}
}

`Hum-Works/lodestone-base-4096-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	768	not specified	not specified	2023-08-25	eng-Latn

Human¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	not specified	ara-Arab, dan-Latn, eng-Latn, nob-Latn, rus-Cyrl

`IEITYuan/Yuan-embedding-2.0-zh`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1792	326.0M	1.2 GB	2025-11-24	zho-Hans

`Jaume/gemma-2b-embeddings`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	2048	2.5B	9.3 GB	2024-06-29	not specified

`KBLab/sentence-bert-swedish-cased`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
384	768	124.7M	476.0 MB	2023-01-11	swe-Latn

Citation

@misc{rekathati2021introducing,  
  author = {Rekathati, Faton},  
  title = {The KBLab Blog: Introducing a Swedish Sentence Transformer},  
  url = {https://kb-labb.github.io/posts/2021-08-23-a-swedish-sentence-transformer/},  
  year = {2021}  
}

`KFST/XLMRoberta-en-da-sv-nb`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	278.0M	1.0 GB	2022-02-22	dan-Latn, eng-Latn, nno-Latn, nob-Latn, swe-Latn

`KennethEnevoldsen/dfm-sentence-encoder-large`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	355.1M	1.5 GB	2023-07-12	dan-Latn

Citation

@article{enevoldsenScandinavianEmbeddingBenchmarks2024,
    title = {The {Scandinavian} {Embedding} {Benchmarks}: {Comprehensive} {Assessment} of {Multilingual} and {Monolingual} {Text} {Embedding}},
    shorttitle = {The {Scandinavian} {Embedding} {Benchmarks}},
    url = {https://openreview.net/forum?id=pJl_i7HIA72},
    language = {en},
    urldate = {2024-04-12},
    author = {Enevoldsen, Kenneth and Kardos, Márton and Muennighoff, Niklas and Nielbo, Kristoffer},
    month = feb,
    year = {2024},
}

`KennethEnevoldsen/dfm-sentence-encoder-medium`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	124.4M	475.0 MB	2023-07-12	dan-Latn

Citation

@article{enevoldsenScandinavianEmbeddingBenchmarks2024,
    title = {The {Scandinavian} {Embedding} {Benchmarks}: {Comprehensive} {Assessment} of {Multilingual} and {Monolingual} {Text} {Embedding}},
    shorttitle = {The {Scandinavian} {Embedding} {Benchmarks}},
    url = {https://openreview.net/forum?id=pJl_i7HIA72},
    language = {en},
    urldate = {2024-04-12},
    author = {Enevoldsen, Kenneth and Kardos, Márton and Muennighoff, Niklas and Nielbo, Kristoffer},
    month = feb,
    year = {2024},
}

`Kowshik24/bangla-sentence-transformer-ft-matryoshka-paraphrase-multilingual-mpnet-base-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
128	768	278.0M	1.0 GB	2025-11-10	ben-Beng

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`Lajavaness/bilingual-embedding-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	278.0M	1.0 GB	2024-06-26	not specified

Citation

    @article{conneau2019unsupervised,
  title={Unsupervised cross-lingual representation learning at scale},
  author={Conneau, Alexis and Khandelwal, Kartikay and Goyal, Naman and Chaudhary, Vishrav and Wenzek, Guillaume and Guzm{'a}n, Francisco and Grave, Edouard and Ott, Myle and Zettlemoyer, Luke and Stoyanov, Veselin},
  journal={arXiv preprint arXiv:1911.02116},
  year={2019}
}

@article{reimers2019sentence,
   title={Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks},
   author={Nils Reimers, Iryna Gurevych},
   journal={https://arxiv.org/abs/1908.10084},
   year={2019}
}

@article{thakur2020augmented,
  title={Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks},
  author={Thakur, Nandan and Reimers, Nils and Daxenberger, Johannes and Gurevych, Iryna},
  journal={arXiv e-prints},
  pages={arXiv--2010},
  year={2020}
}

`Lajavaness/bilingual-embedding-large`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	559.9M	2.1 GB	2024-06-24	eng-Latn, fra-Latn

Citation

    @article{conneau2019unsupervised,
  title={Unsupervised cross-lingual representation learning at scale},
  author={Conneau, Alexis and Khandelwal, Kartikay and Goyal, Naman and Chaudhary, Vishrav and Wenzek, Guillaume and Guzm{'a}n, Francisco and Grave, Edouard and Ott, Myle and Zettlemoyer, Luke and Stoyanov, Veselin},
  journal={arXiv preprint arXiv:1911.02116},
  year={2019}
}

@article{reimers2019sentence,
   title={Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks},
   author={Nils Reimers, Iryna Gurevych},
   journal={https://arxiv.org/abs/1908.10084},
   year={2019}
}

@article{thakur2020augmented,
  title={Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks},
  author={Thakur, Nandan and Reimers, Nils and Daxenberger, Johannes and Gurevych, Iryna},
  journal={arXiv e-prints},
  pages={arXiv--2010},
  year={2020}
}

`Lajavaness/bilingual-embedding-small`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	117.7M	449.0 MB	2024-07-17	eng-Latn, fra-Latn

Citation

    @article{conneau2019unsupervised,
  title={Unsupervised cross-lingual representation learning at scale},
  author={Conneau, Alexis and Khandelwal, Kartikay and Goyal, Naman and Chaudhary, Vishrav and Wenzek, Guillaume and Guzm{'a}n, Francisco and Grave, Edouard and Ott, Myle and Zettlemoyer, Luke and Stoyanov, Veselin},
  journal={arXiv preprint arXiv:1911.02116},
  year={2019}
}

@article{reimers2019sentence,
   title={Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks},
   author={Nils Reimers, Iryna Gurevych},
   journal={https://arxiv.org/abs/1908.10084},
   year={2019}
}

@article{thakur2020augmented,
  title={Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks},
  author={Thakur, Nandan and Reimers, Nils and Daxenberger, Johannes and Gurevych, Iryna},
  journal={arXiv e-prints},
  pages={arXiv--2010},
  year={2020}
}

`MCINext/Hakim`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	124.4M	475.0 MB	2025-05-10	fas-Arab

Citation

@article{sarmadi2025hakim,
      title={Hakim: Farsi Text Embedding Model},
      author={Sarmadi, Mehran and Alikhani, Morteza and Zinvandi, Erfan and Pourbahman, Zahra},
      journal={arXiv preprint arXiv:2505.08435},
      year={2025}
}

`MCINext/Hakim-small`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	512	38.7M	148.0 MB	2025-05-10	fas-Arab

Citation

@article{sarmadi2025hakim,
      title={Hakim: Farsi Text Embedding Model},
      author={Sarmadi, Mehran and Alikhani, Morteza and Zinvandi, Erfan and Pourbahman, Zahra},
      journal={arXiv preprint arXiv:2505.08435},
      year={2025}
}

`MCINext/Hakim-unsup`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	124.4M	475.0 MB	2025-05-10	fas-Arab

Citation

@article{sarmadi2025hakim,
      title={Hakim: Farsi Text Embedding Model},
      author={Sarmadi, Mehran and Alikhani, Morteza and Zinvandi, Erfan and Pourbahman, Zahra},
      journal={arXiv preprint arXiv:2505.08435},
      year={2025}
}

`Mihaiii/Bulbasaur`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	17.4M	66.0 MB	2024-04-27	not specified

`Mihaiii/Ivysaur`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	22.7M	87.0 MB	2024-04-27	not specified

`Mihaiii/Squirtle`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	15.6M	60.0 MB	2024-04-30	not specified

`Mihaiii/Venusaur`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	15.6M	60.0 MB	2024-04-29	not specified

`Mihaiii/Wartortle`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	17.4M	66.0 MB	2024-04-30	not specified

`Mihaiii/gte-micro`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	17.4M	66.0 MB	2024-04-21	not specified

`Mihaiii/gte-micro-v4`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	19.2M	73.0 MB	2024-04-22	not specified

`Mira190/Euler-Legal-Embedding-V1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
1.5K	4096	8.0B	15.3 GB	2025-11-06	eng-Latn

Citation

@misc{euler2025legal,
      title={Euler-Legal-Embedding: Advanced Legal Representation Learning}, 
      author={LawRank Team},
      year={2025},
      publisher={Hugging Face}
}

`NbAiLab/nb-bert-base`¶

License: cc-by-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	177.9M	681.0 MB	2021-01-13	nno-Latn, nob-Latn

`NbAiLab/nb-bert-large`¶

License: cc-by-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	355.1M	1.3 GB	2021-04-29	nno-Latn, nob-Latn

`NbAiLab/nb-sbert-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
75	4096	1.8B	678.0 MB	2022-11-23	dan-Latn, nno-Latn, nob-Latn, swe-Latn

`NeuML/pubmedbert-base-embeddings-100K`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	64	100.0K	0.0 MB	2025-01-03	eng-Latn

`NeuML/pubmedbert-base-embeddings-1M`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	64	1.0M	2.0 MB	2025-01-03	eng-Latn

`NeuML/pubmedbert-base-embeddings-2M`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	64	1.9M	7.0 MB	2025-01-03	eng-Latn

`NeuML/pubmedbert-base-embeddings-500K`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	64	500.0K	2.0 MB	2025-01-03	eng-Latn

`NeuML/pubmedbert-base-embeddings-8M`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	7.8M	30.0 MB	2025-01-03	eng-Latn

`Omartificial-Intelligence-Space/Arabert-all-nli-triplet-Matryoshka`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	135.2M	516.0 MB	2024-06-16	ara-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`Omartificial-Intelligence-Space/Arabic-MiniLM-L12-v2-all-nli-triplet`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	117.7M	449.0 MB	2024-06-25	ara-Arab

`Omartificial-Intelligence-Space/Arabic-Triplet-Matryoshka-V2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
768	768	135.0M	516.0 MB	2024-07-28	ara-Arab

Citation

    @article{nacar2025gate,
    title={GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training},
    author={Nacar, Omer and Koubaa, Anis and Sibaee, Serry and Al-Habashi, Yasser and Ammar, Adel and Boulila, Wadii},
    journal={arXiv preprint arXiv:2505.24581},
    year={2025}
}

`Omartificial-Intelligence-Space/Arabic-all-nli-triplet-Matryoshka`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	278.0M	1.0 GB	2024-06-14	ara-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`Omartificial-Intelligence-Space/Arabic-labse-Matryoshka`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	470.9M	1.8 GB	2024-06-16	ara-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`Omartificial-Intelligence-Space/Arabic-mpnet-base-all-nli-triplet`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	109.5M	418.0 MB	2024-06-15	ara-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`Omartificial-Intelligence-Space/Marbert-all-nli-triplet-Matryoshka`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	162.8M	621.0 MB	2024-06-17	ara-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`OpenSearch-AI/Ops-MoA-Conan-embedding-v1`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1536	343.0M	1.3 GB	2025-03-26	zho-Hans

`OpenSearch-AI/Ops-MoA-Yuan-embedding-1.0`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1536	343.0M	1.2 GB	2025-03-26	zho-Hans

`OrdalieTech/Solon-embeddings-large-0.1`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	559.9M	2.1 GB	2023-12-09	fra-Latn

`OrdalieTech/Solon-embeddings-mini-beta-1.1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	210.0M	808.0 MB	2025-01-01	fra-Latn

`OrlikB/KartonBERT-USE-base-v1`¶

License: gpl-3.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	103.7M	396.0 MB	2024-09-30	pol-Latn

`OrlikB/st-polish-kartonberta-base-alpha-v1`¶

License: lgpl

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	not specified	not specified	2023-11-12	pol-Latn

`PartAI/Tooka-SBERT`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	353.0M	1.3 GB	2024-12-07	fas-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`PartAI/Tooka-SBERT-V2-Large`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	353.0M	1.3 GB	2025-05-01	fas-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`PartAI/Tooka-SBERT-V2-Small`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	122.9M	496.0 MB	2025-05-01	fas-Arab

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`PartAI/TookaBERT-Base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	122.9M	469.0 MB	2024-12-08	fas-Arab

`Qodo/Qodo-Embed-1-1.5B`¶

License: https://huggingface.co/Qodo/Qodo-Embed-1-1.5B/blob/main/LICENSE

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	1536	1.8B	6.6 GB	2025-02-19	c#-Code, c++-Code, go-Code, java-Code, javascript-Code, ... (9)

`Qodo/Qodo-Embed-1-7B`¶

License: https://huggingface.co/Qodo/Qodo-Embed-1-1.5B/blob/main/LICENSE

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
32.8K	3584	7.6B	28.4 GB	2025-02-24	c#-Code, c++-Code, go-Code, java-Code, javascript-Code, ... (9)

`Shuu12121/CodeSearch-ModernBERT-Crow-Plus`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
1.0K	768	151.7M	607.0 MB	2025-04-21	eng-Latn

`TencentBAC/Conan-embedding-v1`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	326.0M	1.2 GB	2024-08-22	zho-Hans

Citation

@misc{li2024conanembeddinggeneraltextembedding,
  title={Conan-embedding: General Text Embedding with More and Better Negative Samples}, 
  author={Shiyu Li and Yang Tang and Shizhe Chen and Xi Chen},
  year={2024},
  eprint={2408.15710},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2408.15710}, 
}

`VoVanPhuc/sup-SimCSE-VietNamese-phobert-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
256	768	135.0M	517.0 MB	2021-05-26	vie-Latn

Citation

@article{gao2021simcse,
   title={{SimCSE}: Simple Contrastive Learning of Sentence Embeddings},
   author={Gao, Tianyu and Yao, Xingcheng and Chen, Danqi},
   journal={arXiv preprint arXiv:2104.08821},
   year={2021}
}

@inproceedings{phobert,
title     = {{PhoBERT: Pre-trained language models for Vietnamese}},
author    = {Dat Quoc Nguyen and Anh Tuan Nguyen},
booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2020},
year      = {2020},
pages     = {1037--1042}
}

`aari1995/German_Semantic_STS_V2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.7M	1.3 GB	2022-11-17	deu-Latn

`abhinand/MedEmbed-small-v0.1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	33.4M	127.0 MB	2024-10-20	eng-Latn

Citation

@software{balachandran2024medembed,
  author = {Balachandran, Abhinand},
  title = {MedEmbed: Medical-Focused Embedding Models},
  year = {2024},
  url = {https://github.com/abhinand5/MedEmbed}
}

`ai-forever/sbert_large_mt_nlu_ru`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	427.0M	1.6 GB	2021-05-18	rus-Cyrl

`ai-forever/sbert_large_nlu_ru`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	427.0M	1.6 GB	2020-11-20	rus-Cyrl

`amazon/Titan-text-embeddings-v2`¶

License: https://aws.amazon.com/service-terms/

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2024-04-30	eng-Latn

`andersborges/model2vecdk`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	48.0M	183.0 MB	2025-11-21	dan-Latn

Citation

@article{minishlab2024model2vec,
  author = {Tulkens, Stephan and {van Dongen}, Thomas},
  title = {Model2Vec: Fast State-of-the-Art Static Embeddings},
  year = {2024},
  url = {https://github.com/MinishLab/model2vec}
}

`andersborges/model2vecdk-stem`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	48.6M	185.0 MB	2025-11-21	dan-Latn

Citation

@article{minishlab2024model2vec,
  author = {Tulkens, Stephan and {van Dongen}, Thomas},
  title = {Model2Vec: Fast State-of-the-Art Static Embeddings},
  year = {2024},
  url = {https://github.com/MinishLab/model2vec}
}

`avsolatorio/GIST-Embedding-v0`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.5M	418.0 MB	2024-01-31	eng-Latn

Citation

@article{solatorio2024gistembed,
    title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
    author={Aivin V. Solatorio},
    journal={arXiv preprint arXiv:2402.16829},
    year={2024},
    URL={https://arxiv.org/abs/2402.16829}
    eprint={2402.16829},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

`avsolatorio/GIST-all-MiniLM-L6-v2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	22.7M	87.0 MB	2024-02-03	eng-Latn

Citation

@article{solatorio2024gistembed,
    title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
    author={Aivin V. Solatorio},
    journal={arXiv preprint arXiv:2402.16829},
    year={2024},
    URL={https://arxiv.org/abs/2402.16829}
    eprint={2402.16829},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

`avsolatorio/GIST-large-Embedding-v0`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.1M	1.2 GB	2024-02-14	eng-Latn

Citation

@article{solatorio2024gistembed,
    title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
    author={Aivin V. Solatorio},
    journal={arXiv preprint arXiv:2402.16829},
    year={2024},
    URL={https://arxiv.org/abs/2402.16829}
    eprint={2402.16829},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

`avsolatorio/GIST-small-Embedding-v0`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	33.4M	127.0 MB	2024-02-03	eng-Latn

Citation

@article{solatorio2024gistembed,
    title={GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning},
    author={Aivin V. Solatorio},
    journal={arXiv preprint arXiv:2402.16829},
    year={2024},
    URL={https://arxiv.org/abs/2402.16829}
    eprint={2402.16829},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

`avsolatorio/NoInstruct-small-Embedding-v0`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	33.4M	127.0 MB	2024-05-01	eng-Latn

`bedrock/amazon-titan-embed-text-v1`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1536	not specified	not specified	2023-09-27	not specified

`bedrock/amazon-titan-embed-text-v2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	not specified	not specified	2024-04-30	not specified

`bigscience/sgpt-bloom-7b1-msmarco`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	4096	not specified	not specified	2022-08-26	not specified

Citation

@article{muennighoff2022sgpt,
  title={SGPT: GPT Sentence Embeddings for Semantic Search},
  author={Muennighoff, Niklas},
  journal={arXiv preprint arXiv:2202.08904},
  year={2022}
}

`bisectgroup/BiCA-base`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	110.0M	418.0 MB	2025-11-14	eng-Latn

Citation

@misc{sinha2025bicaeffectivebiomedicaldense,
      title={BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives}, 
      author={Aarush Sinha and Pavan Kumar S and Roshan Balaji and Nirav Pravinbhai Bhatt},
      year={2025},
      eprint={2511.08029},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2511.08029}, 
}

`bkai-foundation-models/vietnamese-bi-encoder`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
256	768	135.0M	515.0 MB	2023-09-09	vie-Latn

Citation

      @article{duc2024towards,
    title={Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models},
    author={Nguyen Quang Duc, Le Hai Son, Nguyen Duc Nhan, Nguyen Dich Nhat Minh, Le Thanh Huong, Dinh Viet Sang},
    journal={arXiv preprint arXiv:2403.01616},
    year={2024}
  }

`bm25s`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2024-07-10	eng-Latn

Citation

@misc{bm25s,
      title={BM25S: Orders of magnitude faster lexical search via eager sparse scoring},
      author={Xing Han Lù},
      year={2024},
      eprint={2407.03618},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2407.03618},
}

`brahmairesearch/slx-v0.1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	22.7M	87.0 MB	2024-08-13	eng-Latn

castorini/monobert-large-msmarco¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2020-05-28	eng-Latn

castorini/monot5-3b-msmarco-10k¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2022-03-28	eng-Latn

Citation

@misc{rosa2022parameterleftbehinddistillation,
      title={No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval},
      author={Guilherme Moraes Rosa and Luiz Bonifacio and Vitor Jeronymo and Hugo Abonizio and Marzieh Fadaee and Roberto Lotufo and Rodrigo Nogueira},
      year={2022},
      eprint={2206.02873},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2206.02873},
    }

castorini/monot5-base-msmarco-10k¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2022-03-28	eng-Latn

Citation

@misc{rosa2022parameterleftbehinddistillation,
      title={No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval},
      author={Guilherme Moraes Rosa and Luiz Bonifacio and Vitor Jeronymo and Hugo Abonizio and Marzieh Fadaee and Roberto Lotufo and Rodrigo Nogueira},
      year={2022},
      eprint={2206.02873},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2206.02873},
    }

castorini/monot5-large-msmarco-10k¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2022-03-28	eng-Latn

Citation

@misc{rosa2022parameterleftbehinddistillation,
      title={No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval},
      author={Guilherme Moraes Rosa and Luiz Bonifacio and Vitor Jeronymo and Hugo Abonizio and Marzieh Fadaee and Roberto Lotufo and Rodrigo Nogueira},
      year={2022},
      eprint={2206.02873},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2206.02873},
    }

castorini/monot5-small-msmarco-10k¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2022-03-28	eng-Latn

Citation

@misc{rosa2022parameterleftbehinddistillation,
      title={No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval},
      author={Guilherme Moraes Rosa and Luiz Bonifacio and Vitor Jeronymo and Hugo Abonizio and Marzieh Fadaee and Roberto Lotufo and Rodrigo Nogueira},
      year={2022},
      eprint={2206.02873},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2206.02873},
    }

`codesage/codesage-base-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	1024	356.0M	1.3 GB	2024-02-03	go-Code, java-Code, javascript-Code, php-Code, python-Code, ... (6)

Citation

@inproceedings{
    zhang2024code,
    title={{CODE} {REPRESENTATION} {LEARNING} {AT} {SCALE}},
    author={Dejiao Zhang and Wasi Uddin Ahmad and Ming Tan and Hantian Ding and Ramesh Nallapati and Dan Roth and Xiaofei Ma and Bing Xiang},
    booktitle={The Twelfth International Conference on Learning Representations},
    year={2024},
    url={https://openreview.net/forum?id=vfzRRjumpX}
}

`codesage/codesage-large-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	2048	1.3B	4.8 GB	2024-02-03	go-Code, java-Code, javascript-Code, php-Code, python-Code, ... (6)

Citation

@inproceedings{
    zhang2024code,
    title={{CODE} {REPRESENTATION} {LEARNING} {AT} {SCALE}},
    author={Dejiao Zhang and Wasi Uddin Ahmad and Ming Tan and Hantian Ding and Ramesh Nallapati and Dan Roth and Xiaofei Ma and Bing Xiang},
    booktitle={The Twelfth International Conference on Learning Representations},
    year={2024},
    url={https://openreview.net/forum?id=vfzRRjumpX}
}

`codesage/codesage-small-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	1024	130.0M	496.0 MB	2024-02-03	go-Code, java-Code, javascript-Code, php-Code, python-Code, ... (6)

Citation

@inproceedings{
    zhang2024code,
    title={{CODE} {REPRESENTATION} {LEARNING} {AT} {SCALE}},
    author={Dejiao Zhang and Wasi Uddin Ahmad and Ming Tan and Hantian Ding and Ramesh Nallapati and Dan Roth and Xiaofei Ma and Bing Xiang},
    booktitle={The Twelfth International Conference on Learning Representations},
    year={2024},
    url={https://openreview.net/forum?id=vfzRRjumpX}
}

`cointegrated/LaBSE-en-ru`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	129.0M	492.0 MB	2021-06-10	rus-Cyrl

`cointegrated/rubert-tiny`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	312	11.9M	45.0 MB	2021-05-24	rus-Cyrl

`cointegrated/rubert-tiny2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	312	29.4M	112.0 MB	2021-10-28	rus-Cyrl

`colbert-ir/colbertv2.0`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
180	not specified	110.0M	418.0 MB	2024-09-21	eng-Latn

`consciousAI/cai-lunaris-text-embeddings`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	not specified	not specified	2023-06-22	not specified

`consciousAI/cai-stellaris-text-embeddings`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	not specified	not specified	2023-06-23	not specified

`deepfile/embedder-100p`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	not specified	1.0 GB	2023-07-24	not specified

`deepvk/USER-bge-m3`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	359.0M	1.3 GB	2024-07-05	rus-Cyrl

Citation

@misc{deepvk2024user,
    title={USER: Universal Sentence Encoder for Russian},
    author={Malashenko, Boris and  Zemerov, Anton and Spirin, Egor},
    url={https://huggingface.co/datasets/deepvk/USER-base},
    publisher={Hugging Face},
    year={2024},
}

`deepvk/deberta-v1-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	124.0M	473.0 MB	2023-02-07	rus-Cyrl

`dmedhi/PawanEmbd-68M`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	68.0M	260.0 MB	2025-12-08	eng-Latn

Citation

@misc{medhi2025pawanembd,
    title={PawanEmbd-68M: Distilled Embedding Model},
    author={Medhi, D.},
    year={2025},
    url={https://huggingface.co/dmedhi/PawanEmbd-68M}
}

`dunzhang/stella-large-zh-v3-1792d`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1792	not specified	not specified	2024-02-17	zho-Hans

`dunzhang/stella-mrl-large-zh-v3.5-1792d`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1792	326.0M	1.2 GB	2024-02-27	zho-Hans

`dwzhu/e5-base-4k`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.1K	not specified	not specified	not specified	2024-03-28	eng-Latn

Citation

@article{zhu2024longembed,
  title={LongEmbed: Extending Embedding Models for Long Context Retrieval},
  author={Zhu, Dawei and Wang, Liang and Yang, Nan and Song, Yifan and Wu, Wenhao and Wei, Furu and Li, Sujian},
  journal={arXiv preprint arXiv:2404.12096},
  year={2024}
}

`facebook/SONAR`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	not specified	not specified	2021-05-21	ace-Arab, ace-Latn, acm-Arab, acq-Arab, aeb-Arab, ... (204)

Citation

@misc{Duquenne:2023:sonar_arxiv,
  author = {Paul-Ambroise Duquenne and Holger Schwenk and Benoit Sagot},
  title = {{SONAR:} Sentence-Level Multimodal and Language-Agnostic Representations},
  publisher = {arXiv},
  year = {2023},
  url = {https://arxiv.org/abs/2308.11466},
}

`facebook/contriever-msmarco`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	150.0M	572.0 MB	2022-06-25	eng-Latn

Citation

    @misc{izacard2021contriever,
      title={Unsupervised Dense Information Retrieval with Contrastive Learning},
      author={Gautier Izacard and Mathilde Caron and Lucas Hosseini and Sebastian Riedel and Piotr Bojanowski and Armand Joulin and Edouard Grave},
      year={2021},
      url = {https://arxiv.org/abs/2112.09118},
      doi = {10.48550/ARXIV.2112.09118},
    }

`fangxq/XYZ-embedding`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	326.0M	1.2 GB	2024-09-13	zho-Hans

google/flan-t5-base¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	944.0 MB	2022-10-21	eng-Latn

Citation

@misc{10.48550/arxiv.2210.11416,
      doi = {10.48550/ARXIV.2210.11416},
      url = {https://arxiv.org/abs/2210.11416},
      author = {Chung, Hyung Won and Hou, Le and Longpre, Shayne and Zoph, Barret and Tay, Yi and Fedus, William and Li, Eric and Wang, Xuezhi and Dehghani, Mostafa and Brahma, Siddhartha and Webson, Albert and Gu, Shixiang Shane and Dai, Zhuyun and Suzgun, Mirac and Chen, Xinyun and Chowdhery, Aakanksha and Narang, Sharan and Mishra, Gaurav and Yu, Adams and Zhao, Vincent and Huang, Yanping and Dai, Andrew and Yu, Hongkun and Petrov, Slav and Chi, Ed H. and Dean, Jeff and Devlin, Jacob and Roberts, Adam and Zhou, Denny and Le, Quoc V. and Wei, Jason},
      keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
      title = {Scaling Instruction-Finetuned Language Models},
      publisher = {arXiv},
      year = {2022},
      copyright = {Creative Commons Attribution 4.0 International}
    }

google/flan-t5-large¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	2.9 GB	2022-10-21	eng-Latn

Citation

@misc{10.48550/arxiv.2210.11416,
      doi = {10.48550/ARXIV.2210.11416},
      url = {https://arxiv.org/abs/2210.11416},
      author = {Chung, Hyung Won and Hou, Le and Longpre, Shayne and Zoph, Barret and Tay, Yi and Fedus, William and Li, Eric and Wang, Xuezhi and Dehghani, Mostafa and Brahma, Siddhartha and Webson, Albert and Gu, Shixiang Shane and Dai, Zhuyun and Suzgun, Mirac and Chen, Xinyun and Chowdhery, Aakanksha and Narang, Sharan and Mishra, Gaurav and Yu, Adams and Zhao, Vincent and Huang, Yanping and Dai, Andrew and Yu, Hongkun and Petrov, Slav and Chi, Ed H. and Dean, Jeff and Devlin, Jacob and Roberts, Adam and Zhou, Denny and Le, Quoc V. and Wei, Jason},
      keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
      title = {Scaling Instruction-Finetuned Language Models},
      publisher = {arXiv},
      year = {2022},
      copyright = {Creative Commons Attribution 4.0 International}
    }

google/flan-t5-xl¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	10.6 GB	2022-10-21	eng-Latn

Citation

@misc{10.48550/arxiv.2210.11416,
      doi = {10.48550/ARXIV.2210.11416},
      url = {https://arxiv.org/abs/2210.11416},
      author = {Chung, Hyung Won and Hou, Le and Longpre, Shayne and Zoph, Barret and Tay, Yi and Fedus, William and Li, Eric and Wang, Xuezhi and Dehghani, Mostafa and Brahma, Siddhartha and Webson, Albert and Gu, Shixiang Shane and Dai, Zhuyun and Suzgun, Mirac and Chen, Xinyun and Chowdhery, Aakanksha and Narang, Sharan and Mishra, Gaurav and Yu, Adams and Zhao, Vincent and Huang, Yanping and Dai, Andrew and Yu, Hongkun and Petrov, Slav and Chi, Ed H. and Dean, Jeff and Devlin, Jacob and Roberts, Adam and Zhou, Denny and Le, Quoc V. and Wei, Jason},
      keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
      title = {Scaling Instruction-Finetuned Language Models},
      publisher = {arXiv},
      year = {2022},
      copyright = {Creative Commons Attribution 4.0 International}
    }

google/flan-t5-xxl¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	42.0 GB	2022-10-21	eng-Latn

Citation

@misc{10.48550/arxiv.2210.11416,
      doi = {10.48550/ARXIV.2210.11416},
      url = {https://arxiv.org/abs/2210.11416},
      author = {Chung, Hyung Won and Hou, Le and Longpre, Shayne and Zoph, Barret and Tay, Yi and Fedus, William and Li, Eric and Wang, Xuezhi and Dehghani, Mostafa and Brahma, Siddhartha and Webson, Albert and Gu, Shixiang Shane and Dai, Zhuyun and Suzgun, Mirac and Chen, Xinyun and Chowdhery, Aakanksha and Narang, Sharan and Mishra, Gaurav and Yu, Adams and Zhao, Vincent and Huang, Yanping and Dai, Andrew and Yu, Hongkun and Petrov, Slav and Chi, Ed H. and Dean, Jeff and Devlin, Jacob and Roberts, Adam and Zhou, Denny and Le, Quoc V. and Wei, Jason},
      keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
      title = {Scaling Instruction-Finetuned Language Models},
      publisher = {arXiv},
      year = {2022},
      copyright = {Creative Commons Attribution 4.0 International}
    }

`hiieu/halong_embedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	278.0M	1.0 GB	2024-07-06	vie-Latn

Citation

@misc{HalongEmbedding,
  title={HalongEmbedding: A Vietnamese Text Embedding},
  author={Ngo Hieu},
  year={2024},
  publisher={Huggingface},
}

`iampanda/zpoint_large_embedding_zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1792	326.0M	1.2 GB	2024-06-04	zho-Hans

`ibm-granite/granite-embedding-107m-multilingual`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	107.0M	204.0 MB	2024-12-18	ara-Latn, ces-Latn, deu-Latn, eng-Latn, fra-Latn, ... (13)

Citation

@article{awasthy2025graniteembedding,
  title={Granite Embedding Models},
  author={Awasthy, Parul and Trivedi, Aashka and Li, Yulong and Bornea, Mihaela and Cox, David and Daniels, Abraham and Franz, Martin and Goodhart, Gabe and Iyer, Bhavani and Kumar, Vishwajeet and Lastras, Luis and McCarley, Scott and Murthy, Rudra and P, Vignesh and Rosenthal, Sara and Roukos, Salim and Sen, Jaydeep and Sharma, Sukriti and Sil, Avirup and Soule, Kate and Sultan, Arafat and Florian, Radu},
  journal={arXiv preprint arXiv:2502.20204},
  year={2025}
}

`ibm-granite/granite-embedding-125m-english`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	125.0M	238.0 MB	2024-12-18	eng-Latn

Citation

@article{awasthy2025graniteembedding,
  title={Granite Embedding Models},
  author={Awasthy, Parul and Trivedi, Aashka and Li, Yulong and Bornea, Mihaela and Cox, David and Daniels, Abraham and Franz, Martin and Goodhart, Gabe and Iyer, Bhavani and Kumar, Vishwajeet and Lastras, Luis and McCarley, Scott and Murthy, Rudra and P, Vignesh and Rosenthal, Sara and Roukos, Salim and Sen, Jaydeep and Sharma, Sukriti and Sil, Avirup and Soule, Kate and Sultan, Arafat and Florian, Radu},
  journal={arXiv preprint arXiv:2502.20204},
  year={2025}
}

`ibm-granite/granite-embedding-278m-multilingual`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	278.0M	530.0 MB	2024-12-18	ara-Latn, ces-Latn, deu-Latn, eng-Latn, fra-Latn, ... (13)

Citation

@article{awasthy2025graniteembedding,
  title={Granite Embedding Models},
  author={Awasthy, Parul and Trivedi, Aashka and Li, Yulong and Bornea, Mihaela and Cox, David and Daniels, Abraham and Franz, Martin and Goodhart, Gabe and Iyer, Bhavani and Kumar, Vishwajeet and Lastras, Luis and McCarley, Scott and Murthy, Rudra and P, Vignesh and Rosenthal, Sara and Roukos, Salim and Sen, Jaydeep and Sharma, Sukriti and Sil, Avirup and Soule, Kate and Sultan, Arafat and Florian, Radu},
  journal={arXiv preprint arXiv:2502.20204},
  year={2025}
}

`ibm-granite/granite-embedding-30m-english`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	30.0M	58.0 MB	2024-12-18	eng-Latn

Citation

@article{awasthy2025graniteembedding,
  title={Granite Embedding Models},
  author={Awasthy, Parul and Trivedi, Aashka and Li, Yulong and Bornea, Mihaela and Cox, David and Daniels, Abraham and Franz, Martin and Goodhart, Gabe and Iyer, Bhavani and Kumar, Vishwajeet and Lastras, Luis and McCarley, Scott and Murthy, Rudra and P, Vignesh and Rosenthal, Sara and Roukos, Salim and Sen, Jaydeep and Sharma, Sukriti and Sil, Avirup and Soule, Kate and Sultan, Arafat and Florian, Radu},
  journal={arXiv preprint arXiv:2502.20204},
  year={2025}
}

`ibm-granite/granite-embedding-english-r2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	149.0M	284.0 MB	2025-08-15	eng-Latn

Citation

@article{awasthy2025graniteembedding,
  title={Granite Embedding Models},
  author={Awasthy, Parul and Trivedi, Aashka and Li, Yulong and Bornea, Mihaela and Cox, David and Daniels, Abraham and Franz, Martin and Goodhart, Gabe and Iyer, Bhavani and Kumar, Vishwajeet and Lastras, Luis and McCarley, Scott and Murthy, Rudra and P, Vignesh and Rosenthal, Sara and Roukos, Salim and Sen, Jaydeep and Sharma, Sukriti and Sil, Avirup and Soule, Kate and Sultan, Arafat and Florian, Radu},
  journal={arXiv preprint arXiv:2502.20204},
  year={2025}
}

`ibm-granite/granite-embedding-small-english-r2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	384	47.0M	91.0 MB	2025-08-15	eng-Latn

Citation

@article{awasthy2025graniteembedding,
  title={Granite Embedding Models},
  author={Awasthy, Parul and Trivedi, Aashka and Li, Yulong and Bornea, Mihaela and Cox, David and Daniels, Abraham and Franz, Martin and Goodhart, Gabe and Iyer, Bhavani and Kumar, Vishwajeet and Lastras, Luis and McCarley, Scott and Murthy, Rudra and P, Vignesh and Rosenthal, Sara and Roukos, Salim and Sen, Jaydeep and Sharma, Sukriti and Sil, Avirup and Soule, Kate and Sultan, Arafat and Florian, Radu},
  journal={arXiv preprint arXiv:2502.20204},
  year={2025}
}

`infgrad/stella-base-en-v2`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	not specified	not specified	not specified	2023-10-19	eng-Latn

`infgrad/stella-base-zh-v3-1792d`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1792	not specified	not specified	2024-02-17	zho-Hans

`izhx/udever-bloom-1b1`¶

License: https://huggingface.co/spaces/bigscience/license

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2023-10-24	aka-Latn, ara-Arab, asm-Beng, bam-Latn, ben-Beng, ... (45)

Citation

@article{zhang2023language,
  title={Language Models are Universal Embedders},
  author={Zhang, Xin and Li, Zehan and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Zhang, Min},
  journal={arXiv preprint arXiv:2310.08232},
  year={2023}
}

`izhx/udever-bloom-3b`¶

License: https://huggingface.co/spaces/bigscience/license

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2023-10-24	aka-Latn, ara-Arab, asm-Beng, bam-Latn, ben-Beng, ... (45)

Citation

@article{zhang2023language,
  title={Language Models are Universal Embedders},
  author={Zhang, Xin and Li, Zehan and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Zhang, Min},
  journal={arXiv preprint arXiv:2310.08232},
  year={2023}
}

`izhx/udever-bloom-560m`¶

License: https://huggingface.co/spaces/bigscience/license

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2023-10-24	aka-Latn, ara-Arab, asm-Beng, bam-Latn, ben-Beng, ... (45)

Citation

@article{zhang2023language,
  title={Language Models are Universal Embedders},
  author={Zhang, Xin and Li, Zehan and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Zhang, Min},
  journal={arXiv preprint arXiv:2310.08232},
  year={2023}
}

`izhx/udever-bloom-7b1`¶

License: https://huggingface.co/spaces/bigscience/license

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2023-10-24	aka-Latn, ara-Arab, asm-Beng, bam-Latn, ben-Beng, ... (45)

Citation

@article{zhang2023language,
  title={Language Models are Universal Embedders},
  author={Zhang, Xin and Li, Zehan and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Zhang, Min},
  journal={arXiv preprint arXiv:2310.08232},
  year={2023}
}

jhu-clsp/FollowIR-7B¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	13.5 GB	2024-04-29	eng-Latn

Citation

    @misc{weller2024followir,
      title={FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions},
      author={Orion Weller and Benjamin Chang and Sean MacAvaney and Kyle Lo and Arman Cohan and Benjamin Van Durme and Dawn Lawrie and Luca Soldaini},
      year={2024},
      eprint={2403.15246},
      archivePrefix={arXiv},
      primaryClass={cs.IR}
    }

`jinaai/jina-colbert-v2`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	not specified	559.0M	1.0 GB	2024-08-16	ara-Arab, ben-Beng, deu-Latn, eng-Latn, fas-Arab, ... (22)

Citation

@inproceedings{xiao-etal-2024-jina,
    title = "{J}ina-{C}ol{BERT}-v2: A General-Purpose Multilingual Late Interaction Retriever",
    author = {Jha, Rohan  and
      Wang, Bo  and
      G{"u}nther, Michael  and
      Mastrapas, Georgios  and
      Sturua, Saba  and
      Mohr, Isabelle  and
      Koukounas, Andreas  and
      Wang, Mohammad Kalim  and
      Wang, Nan  and
      Xiao, Han},
    editor = {S{"a}lev{"a}, Jonne  and
      Owodunni, Abraham},
    booktitle = "Proceedings of the Fourth Workshop on Multilingual Representation Learning (MRL 2024)",
    month = nov,
    year = "2024",
    address = "Miami, Florida, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.mrl-1.11/",
    doi = "10.18653/v1/2024.mrl-1.11",
    pages = "159--166",
    abstract = "Multi-vector dense models, such as ColBERT, have proven highly effective in information retrieval. ColBERT`s late interaction scoring approximates the joint query-document attention seen in cross-encoders while maintaining inference efficiency closer to traditional dense retrieval models, thanks to its bi-encoder architecture and recent optimizations in indexing and search. In this paper, we introduce a novel architecture and a training framework to support long context window and multilingual retrieval. Leveraging Matryoshka Representation Loss, we further demonstrate that the reducing the embedding dimensionality from 128 to 64 has insignificant impact on the model`s retrieval performance and cut storage requirements by up to 50{\%}. Our new model, Jina-ColBERT-v2, demonstrates strong performance across a range of English and multilingual retrieval tasks,"
}

`jinaai/jina-embedding-b-en-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	110.0M	420.0 MB	2023-07-07	eng-Latn

Citation

@misc{günther2023jina,
      title={Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models},
      author={Michael Günther and Louis Milliken and Jonathan Geuter and Georgios Mastrapas and Bo Wang and Han Xiao},
      year={2023},
      eprint={2307.11224},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`jinaai/jina-embedding-s-en-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	512	35.0M	134.0 MB	2023-07-07	eng-Latn

Citation

@misc{günther2023jina,
      title={Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models},
      author={Michael Günther and Louis Milliken and Jonathan Geuter and Georgios Mastrapas and Bo Wang and Han Xiao},
      year={2023},
      eprint={2307.11224},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`jinaai/jina-embeddings-v2-base-en`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	768	137.0M	262.0 MB	2023-09-27	eng-Latn

Citation

@misc{günther2023jina,
      title={Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents},
      author={Michael Günther and Jackmin Ong and Isabelle Mohr and Alaeddine Abdessalem and Tanguy Abel and Mohammad Kalim Akram and Susana Guzman and Georgios Mastrapas and Saba Sturua and Bo Wang and Maximilian Werk and Nan Wang and Han Xiao},
      year={2023},
      eprint={2310.19923},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

`jinaai/jina-embeddings-v2-small-en`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	512	32.7M	62.0 MB	2023-09-27	eng-Latn

Citation

@misc{günther2023jina,
      title={Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents},
      author={Michael Günther and Jackmin Ong and Isabelle Mohr and Alaeddine Abdessalem and Tanguy Abel and Mohammad Kalim Akram and Susana Guzman and Georgios Mastrapas and Saba Sturua and Bo Wang and Maximilian Werk and Nan Wang and Han Xiao},
      year={2023},
      eprint={2310.19923},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

jinaai/jina-reranker-v2-base-multilingual¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	531.0 MB	2024-09-26	eng-Latn

`jinaai/jina-reranker-v3`¶

License: cc-by-nc-4.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
131.1K	not specified	600.0M	1.1 GB	2025-09-18	afr-Latn, ara-Arab, aze-Latn, bel-Cyrl, ben-Beng, ... (73)

Citation

@misc{wang2025jinarerankerv3lateinteractionlistwise,
      title={jina-reranker-v3: Last but Not Late Interaction for Listwise Document Reranking},
      author={Feng Wang and Yuqing Li and Han Xiao},
      year={2025},
      eprint={2509.25085},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2509.25085},}

`keeeeenw/MicroLlama-text-embedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	1024	272.0M	1.0 GB	2024-11-10	eng-Latn

`lier007/xiaobu-embedding`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	326.0M	1.2 GB	2024-01-09	zho-Hans

`lier007/xiaobu-embedding-v2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	326.0M	1.2 GB	2024-06-30	zho-Hans

`lightonai/GTE-ModernColBERT-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	not specified	149.0M	not specified	2025-04-30	eng-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084"
}

`llmrails/ember-v1`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.0M	1.2 GB	2023-10-10	eng-Latn

Citation

@misc{nur2024emberv1,
      title={ember-v1: SOTA embedding model}, 
      author={Enrike Nur and Anar Aliyev},
      year={2023},
}

`m3hrdadfi/bert-zwnj-wnli-mean-tokens`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	118.3M	451.0 MB	2021-06-28	fas-Arab

`m3hrdadfi/roberta-zwnj-wnli-mean-tokens`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	118.3M	451.0 MB	2021-06-28	fas-Arab

`malenia1/ternary-weight-embedding`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	98.7M	158.0 MB	2024-10-23	not specified

`manu/bge-m3-custom-fr`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1024	567.8M	2.1 GB	2024-04-11	not specified

`manu/sentence_croissant_alpha_v0.2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	2048	1.3B	2.4 GB	2024-03-15	not specified

`manu/sentence_croissant_alpha_v0.3`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	2048	1.3B	2.4 GB	2024-04-26	not specified

`manu/sentence_croissant_alpha_v0.4`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	2048	1.3B	2.4 GB	2024-04-27	eng-Latn, fra-Latn

meta-llama/Llama-2-7b-chat-hf¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2023-07-18	eng-Latn

Citation

@misc{touvron2023llama2openfoundation,
      title={Llama 2: Open Foundation and Fine-Tuned Chat Models},
      author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov and Soumya Batra and Prajjwal Bhargava and Shruti Bhosale and Dan Bikel and Lukas Blecher and Cristian Canton Ferrer and Moya Chen and Guillem Cucurull and David Esiobu and Jude Fernandes and Jeremy Fu and Wenyin Fu and Brian Fuller and Cynthia Gao and Vedanuj Goswami and Naman Goyal and Anthony Hartshorn and Saghar Hosseini and Rui Hou and Hakan Inan and Marcin Kardas and Viktor Kerkez and Madian Khabsa and Isabel Kloumann and Artem Korenev and Punit Singh Koura and Marie-Anne Lachaux and Thibaut Lavril and Jenya Lee and Diana Liskovich and Yinghai Lu and Yuning Mao and Xavier Martinet and Todor Mihaylov and Pushkar Mishra and Igor Molybog and Yixin Nie and Andrew Poulton and Jeremy Reizenstein and Rashi Rungta and Kalyan Saladi and Alan Schelten and Ruan Silva and Eric Michael Smith and Ranjan Subramanian and Xiaoqing Ellen Tan and Binh Tang and Ross Taylor and Adina Williams and Jian Xiang Kuan and Puxin Xu and Zheng Yan and Iliyan Zarov and Yuchen Zhang and Angela Fan and Melanie Kambadur and Sharan Narang and Aurelien Rodriguez and Robert Stojnic and Sergey Edunov and Thomas Scialom},
      year={2023},
      eprint={2307.09288},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2307.09288},
    }

meta-llama/Llama-2-7b-hf¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2023-07-18	eng-Latn

Citation

@misc{touvron2023llama2openfoundation,
      title={Llama 2: Open Foundation and Fine-Tuned Chat Models},
      author={Hugo Touvron and Louis Martin and Kevin Stone and Peter Albert and Amjad Almahairi and Yasmine Babaei and Nikolay Bashlykov and Soumya Batra and Prajjwal Bhargava and Shruti Bhosale and Dan Bikel and Lukas Blecher and Cristian Canton Ferrer and Moya Chen and Guillem Cucurull and David Esiobu and Jude Fernandes and Jeremy Fu and Wenyin Fu and Brian Fuller and Cynthia Gao and Vedanuj Goswami and Naman Goyal and Anthony Hartshorn and Saghar Hosseini and Rui Hou and Hakan Inan and Marcin Kardas and Viktor Kerkez and Madian Khabsa and Isabel Kloumann and Artem Korenev and Punit Singh Koura and Marie-Anne Lachaux and Thibaut Lavril and Jenya Lee and Diana Liskovich and Yinghai Lu and Yuning Mao and Xavier Martinet and Todor Mihaylov and Pushkar Mishra and Igor Molybog and Yixin Nie and Andrew Poulton and Jeremy Reizenstein and Rashi Rungta and Kalyan Saladi and Alan Schelten and Ruan Silva and Eric Michael Smith and Ranjan Subramanian and Xiaoqing Ellen Tan and Binh Tang and Ross Taylor and Adina Williams and Jian Xiang Kuan and Puxin Xu and Zheng Yan and Iliyan Zarov and Yuchen Zhang and Angela Fan and Melanie Kambadur and Sharan Narang and Aurelien Rodriguez and Robert Stojnic and Sergey Edunov and Thomas Scialom},
      year={2023},
      eprint={2307.09288},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2307.09288},
    }

`minishlab/M2V_base_glove`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	102.0M	391.0 MB	2024-09-21	eng-Latn

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

`minishlab/M2V_base_glove_subword`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	103.0M	391.0 MB	2024-09-21	eng-Latn

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

`minishlab/M2V_base_output`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	7.6M	29.0 MB	2024-09-21	eng-Latn

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

`minishlab/M2V_multilingual_output`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	128.0M	489.0 MB	2024-09-21	eng-Latn

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

`minishlab/potion-base-2M`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	64	2.0M	7.0 MB	2024-10-29	eng-Latn

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

`minishlab/potion-base-4M`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	128	3.8M	14.0 MB	2024-10-29	eng-Latn

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

`minishlab/potion-base-8M`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	7.6M	29.0 MB	2024-10-29	eng-Latn

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

`minishlab/potion-multilingual-128M`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	128.0M	489.0 MB	2025-05-23	afr-Latn, amh-Ethi, ara-Arab, aze-Latn, bel-Cyrl, ... (101)

Citation

@software{minishlab2024model2vec,
      authors = {Stephan Tulkens, Thomas van Dongen},
      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
      year = {2024},
      url = {https://github.com/MinishLab/model2vec}
}

mistralai/Mistral-7B-Instruct-v0.2¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2023-12-11	eng-Latn

Citation

@misc{jiang2023mistral7b,
      title={Mistral 7B},
      author={Albert Q. Jiang and Alexandre Sablayrolles and Arthur Mensch and Chris Bamford and Devendra Singh Chaplot and Diego de las Casas and Florian Bressand and Gianna Lengyel and Guillaume Lample and Lucile Saulnier and Lélio Renard Lavaud and Marie-Anne Lachaux and Pierre Stock and Teven Le Scao and Thibaut Lavril and Thomas Wang and Timothée Lacroix and William El Sayed},
      year={2023},
      eprint={2310.06825},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2310.06825},
    }

`moka-ai/m3e-base`¶

License: https://huggingface.co/moka-ai/m3e-base#%F0%9F%93%9C-license

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	102.0M	390.0 MB	2023-06-06	eng-Latn, zho-Hans

Citation

@software{MokaMassiveMixedEmbedding,
  author = {Wang Yuxin and Sun Qingxuan and He Sicheng},
  title = {M3E: Moka Massive Mixed Embedding Model},
  year = {2023}
}

`moka-ai/m3e-large`¶

License: https://huggingface.co/moka-ai/m3e-base#%F0%9F%93%9C-license

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	not specified	not specified	2023-06-21	eng-Latn, zho-Hans

Citation

@software{MokaMassiveMixedEmbedding,
  author = {Wang Yuxin and Sun Qingxuan and He Sicheng},
  title = {M3E: Moka Massive Mixed Embedding Model},
  year = {2023}
}

`moka-ai/m3e-small`¶

License: https://huggingface.co/moka-ai/m3e-base#%F0%9F%93%9C-license

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	512	not specified	not specified	2023-06-02	eng-Latn, zho-Hans

Citation

@software{MokaMassiveMixedEmbedding,
  author = {Wang Yuxin and Sun Qingxuan and He Sicheng},
  title = {M3E: Moka Massive Mixed Embedding Model},
  year = {2023}
}

`myrkur/sentence-transformer-parsbert-fa`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	162.8M	621.0 MB	2024-12-10	fas-Arab

`omarelshehy/arabic-english-sts-matryoshka`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	559.9M	2.1 GB	2024-10-13	ara-Arab, eng-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`openai/text-embedding-3-large`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	3072	not specified	not specified	2024-01-25	not specified

`openai/text-embedding-3-large (embed_dim=512)`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	512	not specified	not specified	2024-01-25	not specified

`openai/text-embedding-3-small`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1536	not specified	not specified	2024-01-25	not specified

`openai/text-embedding-3-small (embed_dim=512)`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	512	not specified	not specified	2024-01-25	not specified

`openai/text-embedding-ada-002`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1536	not specified	not specified	2022-12-15	not specified

`openbmb/MiniCPM-Embedding`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	2304	2.7B	5.1 GB	2024-09-04	eng-Latn, zho-Hans

`panalexeu/xlm-roberta-ua-distilled`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	278.0M	1.0 GB	2025-04-15	eng-Latn, ukr-Cyrl

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`prdev/mini-gte`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	66.3M	253.0 MB	2025-01-28	eng-Latn

`rasgaard/m2v-dfm-large`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
infP	256	22.9M	87.0 MB	2025-10-08	dan-Latn

Citation

@article{minishlab2024model2vec,
    author = {Tulkens, Stephan and {van Dongen}, Thomas},
    title = {Model2Vec: Fast State-of-the-Art Static Embeddings},
    year = {2024},
    url = {https://github.com/MinishLab/model2vec}
}

`richinfoai/ritrieve_zh_v1`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1792	326.0M	1.2 GB	2025-03-25	zho-Hans

`sbintuitions/sarashina-embedding-v1-1b`¶

License: https://huggingface.co/sbintuitions/sarashina-embedding-v1-1b/blob/main/LICENSE

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
8.2K	1792	1.2B	4.6 GB	2024-11-22	jpn-Jpan

`sbunlp/fabert`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	124.4M	475.0 MB	2024-10-07	fas-Arab

Citation

@inproceedings{masumi-etal-2025-fabert,
    title = "{F}a{BERT}: Pre-training {BERT} on {P}ersian Blogs",
    author = "Masumi, Mostafa  and
      Majd, Seyed Soroush  and
      Shamsfard, Mehrnoush  and
      Beigy, Hamid",
    editor = "Bak, JinYeong  and
      Goot, Rob van der  and
      Jang, Hyeju  and
      Buaphet, Weerayut  and
      Ramponi, Alan  and
      Xu, Wei  and
      Ritter, Alan",
    booktitle = "Proceedings of the Tenth Workshop on Noisy and User-generated Text",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.wnut-1.10/",
    doi = "10.18653/v1/2025.wnut-1.10",
    pages = "85--96",
    ISBN = "979-8-89176-232-9",
}

`sdadas/mmlw-e5-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	278.0M	1.0 GB	2023-11-17	pol-Latn

Citation

@article{dadas2024pirb,
  title={{PIRB}: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods}, 
  author={Sławomir Dadas and Michał Perełkiewicz and Rafał Poświata},
  year={2024},
  eprint={2402.13350},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}

`sdadas/mmlw-e5-large`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	559.9M	2.1 GB	2023-11-17	pol-Latn

Citation

@article{dadas2024pirb,
  title={{PIRB}: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods}, 
  author={Sławomir Dadas and Michał Perełkiewicz and Rafał Poświata},
  year={2024},
  eprint={2402.13350},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}

`sdadas/mmlw-e5-small`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	117.7M	449.0 MB	2023-11-17	pol-Latn

Citation

@article{dadas2024pirb,
  title={{PIRB}: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods}, 
  author={Sławomir Dadas and Michał Perełkiewicz and Rafał Poświata},
  year={2024},
  eprint={2402.13350},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}

`sdadas/mmlw-roberta-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	768	124.4M	475.0 MB	2023-11-17	pol-Latn

Citation

@article{dadas2024pirb,
  title={{PIRB}: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods}, 
  author={Sławomir Dadas and Michał Perełkiewicz and Rafał Poświata},
  year={2024},
  eprint={2402.13350},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}

`sdadas/mmlw-roberta-large`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
514	1024	435.0M	1.6 GB	2023-11-17	pol-Latn

Citation

@article{dadas2024pirb,
  title={{PIRB}: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods}, 
  author={Sławomir Dadas and Michał Perełkiewicz and Rafał Poświata},
  year={2024},
  eprint={2402.13350},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}

`sensenova/piccolo-base-zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	not specified	not specified	2023-09-04	zho-Hans

`sensenova/piccolo-large-zh-v2`¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	not specified	not specified	2024-04-22	zho-Hans

Citation

@misc{2405.06932,
    Author = {Junqin Huang and Zhongjie Hu and Zihao Jing and Mengya Gao and Yichao Wu},
    Title = {Piccolo2: General Text Embedding with Multi-task Hybrid Loss Training},
    Year = {2024},
    Eprint = {arXiv:2405.06932},
}

`sentence-transformers/LaBSE`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	471.0M	1.8 GB	2019-11-01	ara-Arab, bul-Cyrl, cat-Latn, ces-Latn, dan-Latn, ... (53)

Citation

@misc{feng2022languageagnosticbertsentenceembedding,
      title={Language-agnostic BERT Sentence Embedding},
      author={Fangxiaoyu Feng and Yinfei Yang and Daniel Cer and Naveen Arivazhagan and Wei Wang},
      year={2022},
      eprint={2007.01852},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2007.01852},
    }

`sentence-transformers/all-MiniLM-L12-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
256	384	33.4M	127.0 MB	2021-08-30	eng-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

`sentence-transformers/all-MiniLM-L6-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
256	384	22.7M	87.0 MB	2021-08-30	eng-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

`sentence-transformers/all-mpnet-base-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
384	768	109.0M	418.0 MB	2021-08-30	eng-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

`sentence-transformers/gtr-t5-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	110.0M	209.0 MB	2022-02-09	eng-Latn

Citation

@misc{ni2021largedualencodersgeneralizable,
      title={Large Dual Encoders Are Generalizable Retrievers}, 
      author={Jianmo Ni and Chen Qu and Jing Lu and Zhuyun Dai and Gustavo Hernández Ábrego and Ji Ma and Vincent Y. Zhao and Yi Luan and Keith B. Hall and Ming-Wei Chang and Yinfei Yang},
      year={2021},
      eprint={2112.07899},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2112.07899}, 
}

`sentence-transformers/gtr-t5-large`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	335.0M	639.0 MB	2022-02-09	eng-Latn

Citation

@misc{ni2021largedualencodersgeneralizable,
      title={Large Dual Encoders Are Generalizable Retrievers}, 
      author={Jianmo Ni and Chen Qu and Jing Lu and Zhuyun Dai and Gustavo Hernández Ábrego and Ji Ma and Vincent Y. Zhao and Yi Luan and Keith B. Hall and Ming-Wei Chang and Yinfei Yang},
      year={2021},
      eprint={2112.07899},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2112.07899}, 
}

`sentence-transformers/gtr-t5-xl`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	1.2B	2.3 GB	2022-02-09	eng-Latn

Citation

@misc{ni2021largedualencodersgeneralizable,
      title={Large Dual Encoders Are Generalizable Retrievers}, 
      author={Jianmo Ni and Chen Qu and Jing Lu and Zhuyun Dai and Gustavo Hernández Ábrego and Ji Ma and Vincent Y. Zhao and Yi Luan and Keith B. Hall and Ming-Wei Chang and Yinfei Yang},
      year={2021},
      eprint={2112.07899},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2112.07899}, 
}

`sentence-transformers/gtr-t5-xxl`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	4.9B	9.1 GB	2022-02-09	eng-Latn

Citation

@misc{ni2021largedualencodersgeneralizable,
      title={Large Dual Encoders Are Generalizable Retrievers}, 
      author={Jianmo Ni and Chen Qu and Jing Lu and Zhuyun Dai and Gustavo Hernández Ábrego and Ji Ma and Vincent Y. Zhao and Yi Luan and Keith B. Hall and Ming-Wei Chang and Yinfei Yang},
      year={2021},
      eprint={2112.07899},
      archivePrefix={arXiv},
      primaryClass={cs.IR},
      url={https://arxiv.org/abs/2112.07899}, 
}

`sentence-transformers/multi-qa-MiniLM-L6-cos-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	22.7M	87.0 MB	2021-08-30	eng-Latn

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

`sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	118.0M	449.0 MB	2019-11-01	ara-Arab, bul-Cyrl, cat-Latn, ces-Latn, dan-Latn, ... (53)

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

`sentence-transformers/paraphrase-multilingual-mpnet-base-v2`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	278.0M	1.0 GB	2019-11-01	ara-Arab, bul-Cyrl, cat-Latn, ces-Latn, dan-Latn, ... (53)

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "http://arxiv.org/abs/1908.10084",
}

`sentence-transformers/sentence-t5-base`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	110.0M	209.0 MB	2022-02-09	eng-Latn

Citation

@misc{ni2021sentencet5scalablesentenceencoders,
      title={Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models}, 
      author={Jianmo Ni and Gustavo Hernández Ábrego and Noah Constant and Ji Ma and Keith B. Hall and Daniel Cer and Yinfei Yang},
      year={2021},
      eprint={2108.08877},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2108.08877}, 
}

`sentence-transformers/sentence-t5-large`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	335.0M	639.0 MB	2022-02-09	eng-Latn

Citation

@misc{ni2021sentencet5scalablesentenceencoders,
      title={Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models}, 
      author={Jianmo Ni and Gustavo Hernández Ábrego and Noah Constant and Ji Ma and Keith B. Hall and Daniel Cer and Yinfei Yang},
      year={2021},
      eprint={2108.08877},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2108.08877}, 
}

`sentence-transformers/sentence-t5-xl`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	3.0B	2.3 GB	2024-03-27	eng-Latn

Citation

@misc{ni2021sentencet5scalablesentenceencoders,
      title={Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models}, 
      author={Jianmo Ni and Gustavo Hernández Ábrego and Noah Constant and Ji Ma and Keith B. Hall and Daniel Cer and Yinfei Yang},
      year={2021},
      eprint={2108.08877},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2108.08877}, 
}

`sentence-transformers/sentence-t5-xxl`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	11.0B	9.1 GB	2024-03-27	eng-Latn

Citation

@misc{ni2021sentencet5scalablesentenceencoders,
      title={Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models}, 
      author={Jianmo Ni and Gustavo Hernández Ábrego and Noah Constant and Ji Ma and Keith B. Hall and Daniel Cer and Yinfei Yang},
      year={2021},
      eprint={2108.08877},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2108.08877}, 
}

`sentence-transformers/static-similarity-mrl-multilingual-v1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	1024	108.4M	413.0 MB	2025-01-15	ara-Arab, bul-Cyrl, cat-Latn, ces-Latn, dan-Latn, ... (49)

Citation

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

`sergeyzh/LaBSE-ru-turbo`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	129.0M	490.0 MB	2024-06-27	rus-Cyrl

`sergeyzh/rubert-tiny-turbo`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
2.0K	312	29.2M	111.0 MB	2024-06-21	rus-Cyrl

`shibing624/text2vec-base-chinese`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	102.0M	390.0 MB	2022-01-23	zho-Hans

Citation

@software{text2vec,
  author = {Xu Ming},
  title = {text2vec: A Tool for Text to Vector},
  year = {2022},
  url = {https://github.com/shibing624/text2vec},
}

`shibing624/text2vec-base-chinese-paraphrase`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	118.0M	450.0 MB	2023-06-19	zho-Hans

Citation

@software{text2vec,
  author = {Xu Ming},
  title = {text2vec: A Tool for Text to Vector},
  year = {2022},
  url = {https://github.com/shibing624/text2vec},
}

`shibing624/text2vec-base-multilingual`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
256	384	117.7M	449.0 MB	2023-06-22	deu-Latn, eng-Latn, fra-Latn, ita-Latn, nld-Latn, ... (10)

Citation

@software{text2vec,
  author = {Xu Ming},
  title = {text2vec: A Tool for Text to Vector},
  year = {2022},
  url = {https://github.com/shibing624/text2vec},
}

`silma-ai/silma-embeddding-matryoshka-v0.1`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	135.2M	516.0 MB	2024-10-12	ara-Arab, eng-Latn

Citation

@misc{silma2024embedding,
  author = {Abu Bakr Soliman, Karim Ouda, SILMA AI},
  title = {SILMA Embedding Matryoshka 0.1},
  year = {2024},
  publisher = {Hugging Face},
  howpublished = {https://huggingface.co/silma-ai/silma-embeddding-matryoshka-0.1},
}

`spartan8806/atles-champion-embedding`¶

License: apache-2.0

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	110.0M	420.0 MB	2025-11-15	eng-Latn

Citation

@article{conner2025epistemic,
  title={The Epistemic Barrier: How RLHF Makes AI Consciousness Empirically Undecidable},
  author={Conner (spartan8806)},
  journal={ATLES Research Papers},
  year={2025},
  note={Cross-model validation study (Phoenix, Grok, Gemini, Claude)}
}

`thenlper/gte-base`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	768	109.5M	209.0 MB	2023-07-27	eng-Latn

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`thenlper/gte-base-zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	102.0M	195.0 MB	2023-11-08	zho-Hans

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`thenlper/gte-large`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	335.1M	639.0 MB	2023-07-27	eng-Latn

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`thenlper/gte-large-zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	326.0M	621.0 MB	2023-11-08	zho-Hans

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`thenlper/gte-small`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	384	33.4M	64.0 MB	2023-07-27	eng-Latn

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

`thenlper/gte-small-zh`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
512	1024	30.3M	58.0 MB	2023-11-08	zho-Hans

Citation

@article{li2023towards,
  title={Towards general text embeddings with multi-stage contrastive learning},
  author={Li, Zehan and Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Pengjun and Zhang, Meishan},
  journal={arXiv preprint arXiv:2308.03281},
  year={2023}
}

unicamp-dl/mt5-13b-mmarco-100k¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2022-11-04	afr-Latn, amh-Ethi, ara-Arab, aze-Latn, bel-Cyrl, ... (103)

unicamp-dl/mt5-base-mmarco-v2¶

License: not specified

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
not specified	not specified	not specified	not specified	2022-01-05	afr-Latn, amh-Ethi, ara-Arab, aze-Latn, bel-Cyrl, ... (103)

Citation

@misc{bonifacio2021mmarco,
      title={mMARCO: A Multilingual Version of MS MARCO Passage Ranking Dataset},
      author={Luiz Henrique Bonifacio and Vitor Jeronymo and Hugo Queiroz Abonizio and Israel Campiotti and Marzieh Fadaee and  and Roberto Lotufo and Rodrigo Nogueira},
      year={2021},
      eprint={2108.13897},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
    }

`w601sxs/b1ade-embed`¶

License: mit

Max Tokens	Embedding dimension	Parameters	Required Memory (Mb)	Release date	Languages
4.1K	1024	335.0M	1.2 GB	2025-03-10	eng-Latn

Citation

    @misc{bigscience_workshop_2022,
    author       = { {Shreyas Subramanian} },
    title        = { {b1ade series of models} },
    year         = 2024,
    url          = { https://huggingface.co/w601sxs/b1ade-embed },
    publisher    = { Hugging Face }
}