SigLIP2 is a multilingual vision-language encoder developed by Google, featuring improved semantic understanding, localization, and dense features. It supports zero-shot image classification, enabling direct image classification via text descriptions without requiring additional training. The model excels in multilingual scenarios and is suitable for various vision-language tasks. Key advantages include efficient image-text alignment, support for multiple resolutions and dynamic resolution adjustment, and robust cross-lingual generalization capabilities. SigLIP2 offers a novel solution for multilingual visual tasks, particularly beneficial for scenarios requiring rapid deployment and multilingual support.