Intfloat
E5-Base-v2
Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022
- Context
- 512
- Input
- $0.005
- Output
- $0.00
Text
Other Model Family
Explore 3 curated models in the Other family and compare context, API pricing, modalities and capabilities.
3models tracked
Model directory
3 models in this view
Intfloat
E5-Large-v2
Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022
- Context
- 512
- Input
- $0.01
- Output
- $0.00
Text
Intfloat
Multilingual-E5-Large
Multilingual E5 Text Embeddings: A Technical Report. Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, Furu Wei, arXiv 2024
- Context
- 512
- Input
- $0.01
- Output
- $0.00
Text
OUR METHOD
How AIToolly handles model data
Model-native facts and provider endpoint facts stay separate. Third-party catalogs support discovery and provider snapshots, while official documentation and verified model cards take priority for model facts.