Wan 2.5 Image to Video Prompt Guide

What you’ll see: a boy made of spray paint steps out of a concrete wall under a railway bridge at night. He raps fast, hits classic hip-hop poses, and a single street lamp shapes the scene—cinematic and high energy.

How does WAN 2.5 Image to Video work?

1. Understand your image — Wan 2.5 can detect the subject, materials (in this case the paint), layout, lighting and depth of the image to preserve style and identity.
2. Plans motion — uses your cue to decide what moves (subject and/or camera) and how much.
3. Generates coherent frames — video diffusion builds frames while avoiding jitter and keeping structure (paint texture, wall, lamp shadows).
4. (Optional) Syncs audio & lips — if audio is supplied, aligns mouth shapes and micro-gestures.
5. Refines — stabilizes motion and keeps color/contrast close to the original image.

Why this Wan 2.5 Image to Video prompt example works?

• Clear subject: “boy made of spray paint.”
• Single location: under a railway bridge at night → readable scene.
• Lighting anchor: one street lamp → cinematic contrast.
• Specific action: fast rap + classic poses → rhythmic body/face motion.
• Audio constraint: only the rap → no crowd/traffic noise.

How to set up Image to Video in Wan 2.5 for strong results?

• Use a clean still: high-res, centered subject, minimal text.
• Split motion on purpose: e.g., subject performs; camera gentle push-in.
• Lock vibe: state lighting & atmosphere (e.g., single lamp; cinematic contrast).
• Preserve cues: keep composition, palette, and character design.
• Constrain extras: negatives like no extra characters; no text overlay; no watermark.

Useful settings (if available): Duration & FPS (shorter is cleaner), Motion strength, Camera movement (static / push-in / orbit / handheld), Stylization strength, Seed (repeatability).

Quick troubleshooting of Wan 2.5 image-to-video

• Identity drift: shorten duration; increase “preserve” strength; reduce motion scale.
• Jittery edges: favor gentle camera moves; avoid tiny flickering details.
• Lip/mouth off: clearer audio, slower motion, more frontal angle.
• Overbusy frame: one location + single light source; prune style terms.

Learn how to use Wan 2.5 in Promptus with this step-by-step tutorial.

Here's another example of a Wan 2.5 video and prompt

Wan 2.5 has the ability to take multiple images and combine them. In this video, the prompt used was: 

‍a girl gracefully emerges from the depths of an ancient, misty forest. Her steps are light, and the camera captures her every fluid moment. When the girl stands still and looks around at the lush trees, her face lights up with a smile that blends surprise and joy. This moment, frozen in the interplay of light and shadow, captures the girl's wonderful encounter with nature.

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Follow this formula to generate the your multi-image Wan 2.5 video.

• ‍Entity: a teenage/young woman, calm and curious; light steps; graceful posture
• ‍Environment: ancient misty forest; tall, lush trees; soft ground fog
• Shot size: start wide/medium full as she enters → medium close-up when she stops and smiles
• Perspective: eye-level (natural, intimate)
• Camera: slow, smooth tracking/push-in while she walks; static/hold on her smile; no handheld shake
• Motion: walks lightly from deeper forest into frame; pauses; looks around; subtle smile that mixes surprise + joy; gentle breathing and head turns
• Lighting: dappled forest light; god rays through mist; soft contrast; interplay of light and shadow on face and trees
• Style: realistic cinematic, dreamy/natural color; rich greens; soft bloom; 24 fps
• Audio: optional forest ambience only (wind/leaves/birds), no dialogue
• Duration: ~8–10 s (short and focused)
• Negatives: no extra people/animals; no extra people/animals; no text overlay; no watermark; no fast cuts; no lens breathing; no hard spotlight