Siglip 2 Base Patch 16 512
Google's Siglip 2 Base Patch 16 512 is a vision model designed for tasks such as zero-shot image classification and image-text retrieval, leveraging a unified pretraining objective that combines prior techniques for improved semantic understanding. It is genuinely best at handling vision tasks that require dense features and localization.
Input
Output
Context
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Max Output
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Parameters
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Technical Specifications
Model TypeVision
Context WindowNot available
Max Output TokensNot available
ParametersNot available
Release DateFeb 17, 2025
Training CutoffFeb 20, 2025
Licenseapache-2.0
Open SourceYes
Input Modalities
Image
Output Modalities
Text
Capabilities
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Data sourced from official provider APIs and documentation
Last updated: Aug 8, 2026
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