Stable Video

Stable Video is a generative AI video model currently available in a research preview, designed to convert static images or textual descriptions into short, dynamic video clips. The core technology relies on a latent video diffusion architecture, which processes an input image or text prompt and generates a coherent sequence of frames that form a short video. Users can upload an initial image—such as a photograph, illustration, or graphic—and the model animates it with motion, adding temporal consistency and scene transitions. Alternatively, users can provide a text description, and the system synthesizes a video from scratch, interpreting the prompt to create relevant visual content. The platform supports multiple output dimensions, allowing creators to produce videos in various aspect ratios and resolutions, including HD quality. This flexibility makes it suitable for diverse use cases: media professionals can quickly generate b-roll, transitions, or concept visualizations; educators can create animated explanations from diagrams or textual outlines; marketers can produce short promotional clips from product images or campaign slogans; and entertainment creators can prototype storyboards or dynamic scenes for further refinement. The model is designed to handle both simple motions (e.g., panning, zooming, object movement) and more complex cinematic effects, such as lighting changes and camera shifts, by leveraging its training on large-scale video datasets. Users can adjust parameters like motion strength, number of frames, and style consistency to fine-tune the output. The platform also offers a free tier for initial experimentation, with paid plans for higher usage limits and additional features such as batch processing and priority rendering. In the research preview