GPT-4 with vision (GPT-4V) enables users to instruct GPT-4 to research image inputs provided by the user, and is the most recent capability we’re making broadly available. Incorporating additional modalities (corresponding to image inputs) into large language models (LLMs) is viewed by some as a key frontier in artificial intelligence research and development. Multimodal LLMs offer the potential of expanding the impact of language-only systems with novel interfaces and capabilities, enabling them to unravel recent tasks and supply novel experiences for his or her users. In this method card, we analyze the security properties of GPT-4V. Our work on safety for GPT-4V builds on the work done for GPT-4 and here we dive deeper into the evaluations, preparation, and mitigation work done specifically for image inputs.