ShieldGemma 2: Robust and Tractable Image Content Moderation

Zeng, Wenjun, Kurniawan, Dana, Mullins, Ryan, Liu, Yuchi, Saha, Tamoghna, Ike-Njoku, Dirichi, Gu, Jindong, Song, Yiwen, Xu, Cai, Zhou, Jingjing, Joshi, Aparna, Dheep, Shravan, Malek, Mani, Palangi, Hamid, Baek, Joon, Pereira, Rick, Narasimhan, Karthik

arXiv.org Artificial Intelligence 

We introduce ShieldGemma 2, a 4B parameter image content moderation model built on Gemma 3. This model provides robust safety risk predictions across the following key harm categories: Sexually Explicit, Violence \& Gore, and Dangerous Content for synthetic images (e.g. output of any image generation model) and natural images (e.g. any image input to a Vision-Language Model). We evaluated on both internal and external benchmarks to demonstrate state-of-the-art performance compared to LlavaGuard \citep{helff2024llavaguard}, GPT-4o mini \citep{hurst2024gpt}, and the base Gemma 3 model \citep{gemma_2025} based on our policies. Additionally, we present a novel adversarial data generation pipeline which enables a controlled, diverse, and robust image generation. ShieldGemma 2 provides an open image moderation tool to advance multimodal safety and responsible AI development.

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