Wan 3.0 FAQ

Wan 3.0 is a new-generation AI video model designed for high-quality, longer-form video creation with multimodal control. It accepts text, images, video, and audio, helping creators produce AI videos with consistent characters, natural motion, and cinematic visuals.

Wan 3.0 Standard and Prime support the same core creative inputs and output controls. Prime is optimized for faster end-to-end generation, while Standard is the regular creation option. Choose Prime for rapid iteration and frequent production, or Standard for everyday video generation.

Wan 3.0 Standard and Prime support 480P, 720P, and 1080P output. Videos can run from 2 to 30 seconds, and smart duration can choose a suitable length automatically. When a reference video is used, the input and output duration together cannot exceed 30 seconds.

Wan 3.0 supports multimodal input, including text prompts, image references, video references, and audio references. Combining these materials gives you more precise control over characters, products, motion, style, and scene composition.

Yes. Wan 3.0 can create videos with realistic human performances while maintaining character appearance, motion, and scene style. It is suitable for digital presenters, advertising, social content, and narrative video projects.

Wan 3.0 combines information from reference images, video, and text to control character features, motion relationships, and visual style. Across continuous shots, this helps reduce identity changes, appearance drift, and scene instability so the result feels more coherent.

The WAN30 workspace offers text-to-video, first-frame video, first-and-last-frame video, and multimodal reference generation with images, video, and audio. Choose the simplest workflow that matches the materials you already have, then refine the prompt, references, duration, and resolution before generating.

Many AI video tools rely mainly on text prompts. Wan 3.0 adds richer reference controls through images, video, and audio. That makes it easier to direct character identity, product appearance, motion, visual style, and camera language, especially for stable output and commercial workflows.

A typical workflow is to describe the idea, upload image, video, or audio references, adjust the generation settings, wait for the AI to create the video, and then download the result. Refining the prompt and reference materials over several iterations helps you reach a result that better matches your goal.