WAN PROMPT GUIDE

The Complete Wan AI Prompt Guide: From Basic to Cinematic

Great Wan videos start with structured prompts. This guide distills the official Alibaba formula plus community best practices into copy-paste templates you can use in the generator right now.

The Core Formula: Six Building Blocks

Wan responds best to prompts assembled in a consistent order. The structure recommended by Alibaba's own documentation — and validated across thousands of community generations — is:

  • Subject — who or what the video is about ('a young chef', 'a matte black sports car')
  • Scene — where it happens ('in a neon-lit ramen shop', 'on a windswept cliff at dawn')
  • Motion — what physically happens ('kneads dough rhythmically', 'drifts around a corner, tires smoking')
  • Camera language — how the camera behaves ('slow dolly in', 'orbiting crane shot')
  • Atmosphere — light, weather, mood ('golden hour haze', 'moody overcast with drifting fog')
  • Style — the visual register ('cinematic photorealistic', '90s cel anime', 'documentary handheld')

Ideal Prompt Length: 80–120 Words

Short prompts ('a cat playing piano') leave every creative decision to the model — results are generic and inconsistent. The sweet spot is roughly 80–120 words: enough to lock subject, motion and mood, but not so dense that instructions conflict.

If you must write short prompts, prioritize motion and camera language over adjectives — those two blocks have the largest impact on output quality.

Image-to-Video Prompts: Describe Motion Only

When animating a photo, your image already defines the subject, scene and style. Adding them again confuses the model. The I2V formula is simply: Motion + Camera movement.

Two rules matter more than anything else in I2V: only describe elements actually visible in the image (the model will not invent new objects), and keep camera moves minimal — a slight zoom or gentle pan outperforms dramatic tracking shots.

One Action per Clip

Wan renders 5–15 second clips. Cramming three actions into one prompt produces morphing transitions between them. Choose the single most important action and let the atmosphere carry the rest.

Need a sequence? Generate multiple clips and cut them together — you'll get cleaner results and full editorial control.

Negative Prompts: Your Quality Insurance

A short negative prompt list dramatically reduces artifacts. Our standard baseline: 'morphing, warping, distorted face, extra fingers, blurry, flickering, low quality'. For the full vocabulary see our Negative Prompts dictionary.

Prompt Building Blocks Cheat Sheet

BlockWeakStrong
Subjecta doga wet golden retriever shaking off water
Motionmoving fastsprints toward camera, ears flapping, splashing through puddles
Cameracool cameralow-angle tracking shot pushing backward
Atmospherenice lightingbacklit by low orange sunset, dust motes floating
Stylegood qualityshot on 35mm film, cinematic photorealistic

Copy-Paste Prompt Templates

Copy any template below and paste it straight into the generator.

Cinematic Product Shot

A matte black perfume bottle on wet slate stone, slow orbital rotation, soft key light sweeping across the glass surface, fine mist drifting through a single spotlight beam, dark elegant backdrop, cinematic product photography style, shallow depth of field.

Works best in image-to-video mode with a clean product photo.

Nature Documentary

A golden eagle glides over snow-covered mountain ridges at sunrise, wings catching thermal updrafts, slow aerial tracking shot following behind, crisp morning light casting long shadows, documentary nature film style, photorealistic.

Urban Night Walk

A woman in a long coat walks through a rain-soaked Tokyo alley at night, neon signs reflecting in puddles, steady gimbal shot retreating ahead of her, steam rising from vents, moody cyberpunk color grade, anamorphic lens flares, cinematic photorealistic style.

Cozy Food Close-Up (I2V)

Steam rises gently from the bowl as the camera pushes in very slightly, warm kitchen light flickering softly in the background bokeh.

Image-to-video template — keep motion subtle and physical.

Anime Rooftop Scene

Anime style: a schoolgirl stands on a rooftop as wind lifts her hair and skirt hem, cherry blossom petals drift past, slow tilt up from shoes to face, late afternoon sun flare, Ghibli-inspired painterly background, 90s cel animation style.

Vertical Social Loop

Vertical 9:16 composition: latte art poured in extreme close-up, crema swirling into a rosetta pattern, warm cafe bokeh background, static macro shot, satisfying seamless loop, soft natural window light.

Frequently Asked Questions

What is the best prompt formula for Wan AI?

Subject + Scene + Motion + Camera language + Atmosphere + Style, in that order, at roughly 80–120 words. For image-to-video, drop everything except motion and camera movement.

How long should a Wan prompt be?

80–120 words is the sweet spot. Below ~40 words results become generic; beyond ~200 words instructions start conflicting and quality drops.

Should I write prompts in English?

English prompts are most reliable since training data is English-heavy. The model also handles Chinese well; other languages work but with reduced prompt adherence.

Why do my videos look different each time?

Generation is stochastic. Lock in consistency by reusing full structured prompts (not fragments), and iterate on one block at a time instead of rewriting the whole prompt.

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