Clip Vit Base Patch 16
OpenAI's Clip Vit Base Patch 16 model is a research-oriented AI model that utilizes a ViT-B/16 Transformer architecture as an image encoder and a masked self-attention Transformer as a text encoder, trained with a contrastive loss to maximize the similarity of image-text pairs. It is genuinely best at enabling researchers to explore zero-shot, arbitrary image classification and understand robustness, generalization, and other capabilities of computer vision models.
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0K
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150M
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Estimated GPU Requirements for Clip Vit Base Patch 16
Estimates based on INT8 quantization. Actual requirements vary by framework and configuration.
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Data sourced from official provider APIs and documentation
Last updated: Jun 24, 2026
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