Text to Image
Create AI images from text prompts
Alibaba/wan-3.0-video-edit
wan-3.0-video-edit
Free to try Alibaba Wan 3.0 API for Video Editing and reshape existing footage through natural-language direction for creative revisions on Flaq AI.
Video Edit
Related Wan 3.0 Models
API Examples
Submit Example
const response = await fetch('https://api.flaq.ai/api/v1/video/task', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
model_name: 'wan-3.0-video-edit',
prompt: 'Turn the daytime scene into a rainy evening while preserving the subject and camera movement',
video_url: 'https://example.com/source-video.mp4',
duration: 10,
resolution: '1080p',
aspect_ratio: '16:9',
sound: true,
seed: 42
})
});
const { data } = await response.json();
const taskId = data.task_id;
Polling Example
// Step 2: Poll for results
const taskId = data.task_id;
const pollResult = async (taskId) => {
const res = await fetch(`https://api.flaq.ai/api/v1/video/${taskId}`, {
headers: { 'Authorization': 'Bearer YOUR_API_KEY' }
});
return res.json();
};
while (true) {
const pollResultData = await pollResult(taskId);
const status = pollResultData.data.task_status;
if (status === 'succeed') {
console.log(pollResultData.data.task_result.videos[0].url);
break;
}
if (status === 'failed') {
console.error(pollResultData.data.task_status_msg);
break;
}
await new Promise(resolve => setTimeout(resolve, 10000));
}
Submit Example
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/video/task',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': 'wan-3.0-video-edit',
'prompt': 'Turn the daytime scene into a rainy evening while preserving the subject and camera movement',
'video_url': 'https://example.com/source-video.mp4',
'duration': 10,
'resolution': '1080p',
'aspect_ratio': '16:9',
'sound': True,
'seed': 42
}
)
result = response.json()
task_id = result['data']['task_id']
Polling Example
# Step 2: Poll for results
task_id = response.json()['data']['task_id']
poll_url = f"https://api.flaq.ai/api/v1/video/{task_id}"
while True:
poll_result = requests.get(poll_url, headers={'Authorization': 'Bearer YOUR_API_KEY'}).json()
status = poll_result['data']['task_status']
if status == 'succeed':
print(poll_result['data']['task_result']['videos'][0]['url'])
break
if status == 'failed':
print(poll_result['data']['task_status_msg'])
break
time.sleep(10)
Submit Example
curl -X POST https://api.flaq.ai/api/v1/video/task \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model_name": "wan-3.0-video-edit",
"prompt": "Turn the daytime scene into a rainy evening while preserving the subject and camera movement",
"video_url": "https://example.com/source-video.mp4",
"duration": 10,
"resolution": "1080p",
"aspect_ratio": "16:9",
"sound": true,
"seed": 42
}'
Polling Example
# Step 2: Poll for results
# Replace {task_id} with the task_id returned from the submit response
curl -X GET "https://api.flaq.ai/api/v1/video/{task_id}" \
-H "Authorization: Bearer YOUR_API_KEY"
Try the AI Video Generator now
Wan 3.0 Video Edit Pricing
| Parameters | Price | Original Price | Discount |
|---|
Related Models
qwen-image-2.0text-to-imageqwen-image-2.0-editimage-to-imageqwen-image-2.0-protext-to-imageqwen-image-2.0-pro-editimage-to-imageqwen-image-lora-editimage-to-imagez-imagetext-to-image
happyhorse-1.0-text-to-videotext-to-videohappyhorse-1.0-image-to-videoimage-to-videohappyhorse-1.1-text-to-videotext-to-videohappyhorse-1.1-image-to-videoimage-to-videohappyhorse-1.1-reference-to-videoreference-to-videowan-2.7-text-to-videotext-to-videowan-2.7-image-to-videoimage-to-videowan-2.7-lora-image-to-videoimage-to-videowan-2.7-video-editvideo-editwan-2.7-reference-to-videoreference-to-videowan-v2.7-imagetext-to-imagewan-v2.7-image-editimage-to-imagewan-v2.7-image-protext-to-imagewan-v2.7-image-pro-editimage-to-imagewan-2.6-text-to-videotext-to-videowan-2.6-image-to-videoimage-to-videoqwen-image-3.0text-to-imageqwen-image-3.0-editimage-to-imageqwen-image-3.0-protext-to-imageqwen-image-3.0-pro-editimage-to-imagewan-3.0-text-to-videotext-to-videowan-3.0-image-to-videoimage-to-videowan-3.0-video-editvideo-editwan-3.0-reference-to-videoreference-to-videoqwen-3.7-max-text-to-texttext-to-textqwen-3.7-plus-text-to-texttext-to-textqwen-3.7-max-web-searchweb-searchqwen-3.7-plus-web-searchweb-searchqwen-plus-charactertext-to-textqwen-flash-charactertext-to-textqwen-3.8-max-text-to-texttext-to-textqwen-3.8-max-web-searchweb-searchREADME
Wan 3.0 API for Video Editing (Prompt-Guided Video Transformation)
Wan 3.0 API for Video Editing applies natural-language instructions to an existing video. Developers can describe scene, style, atmosphere, subject, or environmental changes while controlling the requested output duration, resolution, aspect ratio, sound, and seed. Flaq AI provides a task-based API workflow for submitting source footage, tracking the edit, and retrieving the transformed video.
Key Features of Wan 3.0 API for Video Editing
- Prompt-Guided Video Editing: Describe what should change and what should remain stable using direct natural-language instructions.
- Existing Footage as the Foundation: Start from an MP4 or MOV source video and transform it without rebuilding the entire sequence from scratch.
- Flexible Output Controls: Configure duration, resolution, and aspect ratio for different production and delivery requirements.
- Optional Sound Generation: Choose whether the edited result should include generated sound as part of the requested output.
- Seed-Based Iteration: Use an optional seed when comparing prompt revisions or testing alternative settings against the same source.
- Task-Based API Integration: Submit edits, store the returned task identifier, monitor processing, and retrieve completed results programmatically.
How to Use Wan 3.0 API for Video Editing on Flaq AI
- Input: A supported source video URL and a prompt explaining the intended changes and preservation requirements.
- Output: A transformed video returned through the Flaq AI task workflow for review, storage, further editing, or publishing.
- Source Preparation: Use compatible MP4 or MOV footage within the supported duration and dimension limits.
- Timing Control: Choose an output duration that keeps the source duration and requested duration within the combined limit.
- Delivery Settings: Select the resolution, aspect ratio, sound preference, and optional seed for the edited result.
Best Use Cases for Wan 3.0 Video Edit API Integration
- Campaign Asset Revision: Adapt existing footage for new scenes, visual treatments, audiences, and distribution channels.
- Product and Brand Updates: Change backgrounds, atmosphere, presentation, or supporting elements while retaining important source content.
- Creative Post-Production: Explore alternate looks, lighting conditions, environments, and shot treatments from existing footage.
- Social Video Adaptation: Rework a source clip for landscape, portrait, square, and other platform-oriented output formats.
- Automated Editing Pipelines: Add prompt-driven video transformation to media tools, content systems, and production queues.
Note The source video must meet the supported format, duration, and dimension limits. Its duration plus the requested output duration cannot exceed the combined limit, so validate timing before submission.
Wan 3.0 Video Edit vs Competitors: Comparative Analysis
-
Wan 3.0 vs. Wan 2.7 Video Edit
Wan 2.7 provides prompt-guided source video editing with its own reference controls. Wan 3.0 uses a focused source-video workflow with explicit duration, resolution, ratio, sound, and seed settings. -
Wan 3.0 vs. Kling Video O3 Video Edit
Kling Video O3 spans editing and additional video generation modes. Wan 3.0 is suited to teams that need a direct Wan-family route for transforming uploaded footage. -
Wan 3.0 vs. Runway Aleph
Runway Aleph is part of a broader creative editing environment. Wan 3.0 supports developers who want to orchestrate source-video transformations through their own application and task flow. -
Wan 3.0 vs. Adobe Firefly Video
Adobe Firefly Video connects video generation and editing with Adobe's creative ecosystem. Wan 3.0 provides an Alibaba-oriented API option for prompt-guided editing inside custom products. -
Wan 3.0 vs. Pika
Pika emphasizes accessible creative effects and transformations. Wan 3.0 is designed for structured requests, configurable output settings, and programmatic task handling.
Use the Wan 3.0 Video Edit Model Directly in Powerful AI Tools
Explore several AI creation tools for quick image and video workflows in your browser, then scale successful ideas with Flaq AI's production-ready model APIs. Flaq AI provides a unified API layer for all models, making it easy to use and scale your workflows.
Image to Image
Create AI images from images and text prompts
Text to Video
Create AI videos from text prompts
Image to Video
Animate images into AI videos
AI Media Creator
Create AI images and videos in one unified workspace
Reference to Video
Create consistent videos from reference media
AI Canvas
Build visual AI image and video workflows on an infinite canvas