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Wan 3.0 Audio Reference Prompts

Sixty-four Wan 3.0 prompts from the official Wan 3.0 creator handbook, each shown next to the clip it produced: 30-second text-to-video, image, video and audio references, document-to-video, editing, extension and first-frame jobs. Hover to play, one click to copy.

← All 64 Wan 3.0 prompts

Last updated: · Wan 3.0 API — pricing & playground · API docs

TL;DR

Wan 3.0 is Alibaba's all-in-one video model: one model name covers text-to-video, first-frame and first+last-frame image-to-video, and omni-reference generation from up to 10 reference images, 5 reference videos and 5 audio clips, or straight from a document or a public web page. It outputs a native single shot of up to 30 seconds at 30fps with a synced audio track, in 480P, 720P or 1080P. On apimodels.app it is model wan-3.0-video at $0.045, $0.09 and $0.18 per second by resolution, with a prime mode that is about 6x faster for roughly 50% more. This page collects the 64 prompts and sample clips published in the official Wan 3.0 creator handbook, grouped by job type and free to copy.

Source: Wan 3.0 视频创作者手册(通义万相) (the model vendor’s official site)

Hover to preview · click for sound

Two portraits, two voices: a gym conversation

将图片1中的女人定义为主体1，将图片2中的女人定义为主体2，主体1台词音色参考音频1，主体2台词音色参考音频2，在健身房内，主体1和主体2并排站在跑步机旁，主体1转头微笑对主体2说{今天练哪个部位}，主体2一边用毛巾擦汗一边回应{练背吧，昨天腿还酸着呢}，主体1笑着点头说{行，我陪你，先热身十分钟}，主体2拿起水杯喝一口回应{走吧}，背景是器械区和落地镜，写实拍摄，画面明亮通透，冷白色自然饱和度色调

Reference prompts (2)

This clip was made by generating reference images with the prompts below, then driving the video with the prompt above.

参考音频1(reference_audio_urls)

https://r2.apimodels.app/assets/wan3-cases/wan3-case-15-audio-1.mp3

参考音频2(reference_audio_urls)

https://r2.apimodels.app/assets/wan3-cases/wan3-case-15-audio-2.mp3

by Wan 3.0 视频创作者手册 · 通义万相
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Idol dance locked to a reference audio beat

竖屏9:16，全身镜头，固定稳定机位。一位长黑发的年轻女性，身穿白色花朵刺绣长袖上衣、白色百褶短裙配黑色腰带、白色厚底运动鞋，在现代简约风厨房中，跟随固定音频的节拍跳偶像风舞蹈。背景为浅灰色橱柜、白色岛台、深色夜景窗户，人物身后有一块方形补光灯形成轮廓光，室内冷白色灯光。 根据固定音频的节奏、速度和情绪起伏进行舞蹈编排：鼓点重拍对应干脆利落的大幅度动作与定格姿势，舒缓段落对应柔和的身体波浪与手部姿态，副歌高潮段落动作更密集更有爆发力。整体为偶像风舞蹈，动作连贯流畅，富有节奏感和表现力，与音频节拍完全同步。 运动流畅，肢体比例自然。

Reference prompts (1)

This clip was made by generating reference images with the prompts below, then driving the video with the prompt above.

参考音频1(reference_audio_urls)

https://r2.apimodels.app/assets/wan3-cases/wan3-case-43-audio-1.m4a

by Wan 3.0 视频创作者手册 · 通义万相
Hover to preview · click for sound

Character swap with a cloned voice reading new lines

将图片 @Image1 的男性角色无缝替换至视频 @Video1 的女生。角色坐在窗边，手持手机贴耳说话。 【音色与台词】提取音频 @Audio1 中的音色特征，并让角色说出以下台词：“真的吗？听起来很棒！你什么时候回来啊。我好想你啊.” 【口型与神态】生成的语音需精准驱动角色的口型自然开合。说话时伴随自然的眨眼、轻微的头部点动和呼吸感，面部微表情需与台词中的关怀、回忆情绪完美契合。 【光影与场景】人物面部需自然接收室内暖光与窗外霓虹冷光的混合照明。背景窗外雨滴持续缓慢滑落，桌上咖啡有轻微热气升腾，人物与场景边缘融合自然，无抠图痕迹。 【镜头与画质】15秒长镜头，镜头极缓慢向前推进，画面极度稳定，电影级光影，8K分辨率，照片级真实感。

Reference prompts (2)

This clip was made by generating reference images with the prompts below, then driving the video with the prompt above.

参考视频1(reference_video_urls)

https://r2.apimodels.app/assets/wan3-cases/wan3-case-44-in-1.mp4

参考音频1(reference_audio_urls)

https://r2.apimodels.app/assets/wan3-cases/wan3-case-44-audio-1.mp3

by Wan 3.0 视频创作者手册 · 通义万相

How to write great Wan 3.0 prompts

  1. 1Number your materials and address them by slot. Wan 3.0 reads references positionally: "figure 1", "video 1", "audio 1", with images, videos and audio counted separately. The handbook prompts do exactly this, for example "the girl in figure 1 wears the blouse from figure 2". Name the slot, never the file.
  2. 2Write a timeline for anything over 10 seconds. Nearly every 30-second case is written as segments: "0-4 s wide shot", "shot 2 (4-9 s) close-up". The model follows a timeline far better than a paragraph of adjectives, and saying "one continuous take" keeps it from cutting.
  3. 3Write the sound, Wan 3.0 generates it. Every clip carries a synced audio track. The handbook marks effects inline as <cloth rubbing the bar> and dialogue in {braces} or quotes; ambience, a BGM cue and a spoken line each land as written. A prompt with no sound gets generic audio.
  4. 4For edits, say what changes and what must not. Editing prompts open with "edit the video", name the element, and always close with a lock: "the woman's action and the rest of the frame stay unchanged". Without that lock the model re-imagines the whole frame.
  5. 5References carry identity, words carry the action. With a character card or portrait attached, the prompt repeats the traits that must not drift (hair, wardrobe, accessories) and spends the rest on blocking and camera. Two people need two references; two voices need two audio clips.
  6. 6Give an extension a script, not just a length. Extension prompts state the direction ("extend forward 15 s") and then write the new beats with the characters named from the existing footage, dialogue included. A bare "continue" produces filler.
  7. 7Frame mode and reference mode do not mix. On the API first_frame_url / last_frame_url and reference_* / file_url / link_url are mutually exclusive. A first-frame prompt describes motion out of that frame; a reference prompt talks to figure 1 and friends.
  8. 8State duration and aspect ratio up front. The handbook prompts open with "10 s, 16:9, 1920x1080" or "vertical 9:16, 15 s". Wan 3.0 takes 2-30 seconds and 480P / 720P / 1080P; put the numbers in the prompt and match them with the duration parameter.

Prompt formula

Duration + aspect ratio + reference slots (figure 1 / video 1 / audio 1) + timeline segments + subject with locked traits + camera move + light and palette + sound tags + what must stay unchanged

Example: 15 s, 16:9. Figure 1 is the only reference for the woman; keep her short black hair and beige trench. 0-5 s: wide shot, she pushes open a glass café door onto a cobbled street, <heels on stone>. 5-10 s: slow dolly in to a mid shot as she unfolds a paper map. 10-15 s: close-up, she looks up and says "It should be this way." Warm afternoon backlight, film grain, street ambience throughout.

Frequently asked questions

Where do these Wan 3.0 prompts come from?

All 64 prompts and clips come from the Wan 3.0 creator handbook that the Tongyi Wanxiang team published for the model launch, linked above. Every prompt is kept verbatim in its original Chinese, and the sample clips are re-hosted so they keep playing; nothing was regenerated. The reference images and documents some cases used were not published with the handbook, so those cards carry the prompt and the result only.

Where can I run Wan 3.0?

On apimodels.app as model wan-3.0-video, on the same unified video endpoint as VEO, Kling and Seedance: $0.045 per second at 480P, $0.09 at 720P, $0.18 at 1080P, billed only on success, with mode "prime" for the faster tier at roughly 50% more. Reference images, audio, documents and web pages cost nothing extra; a reference video adds its own duration to the billed seconds. No Alibaba Cloud account or mainland real-name verification is needed. The model is also available on Alibaba Cloud Model Studio and the Wan web app.

Do the prompts work in English?

Yes. Wan 3.0 accepts English and Chinese; what matters is the structure the handbook uses: numbered material slots, time segments, sound tags and an explicit "everything else stays unchanged" on edits. Translate the words and keep the skeleton. We leave the originals in Chinese because a translated prompt is not the prompt that produced the clip.

How do the editing and extension cases pass the input video?

Through reference_video_urls, with the prompt addressing it as "video 1". Edits keep the input length; extension prompts state the direction and the added seconds. Upstream caps input plus output at 30 seconds, and billing counts both.

Can I use these clips commercially?

The clips belong to their publisher and are shown here as examples of what each prompt produced. Anything you generate yourself is governed by Alibaba's terms for Wan. The prompt text you can copy, edit and reuse freely.

Run these prompts on apimodels.app

Wan 3.0 is live here alongside 160+ other image, video, audio and language models — one API, one key, pay as you go, with $0.10 of trial credit on sign-up.

Try Wan 3.0 →API docs

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