Text to Image
Create AI images from text prompts
Alibaba/wan-3.0-image-to-video
wan-3.0-image-to-video
Free to try Alibaba Wan 3.0 API for Image-to-Video and animate a first frame toward a chosen end frame for controlled visual storytelling on Flaq AI.
Image to Video
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-image-to-video',
prompt: 'The camera glides forward as daylight gradually shifts into a warm evening glow',
image_url: 'https://example.com/start-frame.jpg',
image_end_url: 'https://example.com/end-frame.jpg',
duration: 8,
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-image-to-video',
'prompt': 'The camera glides forward as daylight gradually shifts into a warm evening glow',
'image_url': 'https://example.com/start-frame.jpg',
'image_end_url': 'https://example.com/end-frame.jpg',
'duration': 8,
'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-image-to-video",
"prompt": "The camera glides forward as daylight gradually shifts into a warm evening glow",
"image_url": "https://example.com/start-frame.jpg",
"image_end_url": "https://example.com/end-frame.jpg",
"duration": 8,
"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 Image to Video Pricing
| Parameters | Price | Original Price | Discount |
|---|
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Wan 3.0 API for Image-to-Video (Start and End Frame Animation)
Wan 3.0 API for Image-to-Video generates a video transition between required start and end frames. Developers can combine both images with a natural-language motion prompt, flexible duration, multiple resolutions and aspect ratios, optional sound, and seed control. Flaq AI provides a task-based integration for creating, monitoring, and retrieving image-guided video results.
Key Features of Wan 3.0 API for Image-to-Video
- Required Start and End Frames: Define both endpoints of the generated sequence to guide its visual direction and final composition.
- Prompt-Guided Motion: Describe subject movement, camera behavior, pacing, environmental changes, and the intended transition in natural language.
- Broad Image Format Support: Use common web and production image formats, including JPEG, PNG without transparency, BMP, and WEBP.
- Flexible Video Controls: Configure duration, resolution, and aspect ratio for landscape, portrait, square, and classic frame outputs.
- Optional Sound Generation: Generate sound with the video when the workflow needs an audio-visual result, or disable it for silent output.
- Seed-Based Iteration: Supply an optional seed when testing prompt changes or comparing different generation settings.
How to Use Wan 3.0 API for Image-to-Video on Flaq AI
- Input: A required start-frame image, a required end-frame image, and a prompt describing the desired motion and transition.
- Output: An image-guided video returned through the Flaq AI task workflow for review, storage, editing, or publishing.
- Frame Preparation: Use compatible images with dimensions inside the supported range. PNG images must not contain an alpha channel.
- Generation Controls: Select duration, resolution, aspect ratio, sound preference, and an optional seed for the request.
- Task Handling: Submit the request, keep the returned task identifier, and poll for the completed video.
Best Use Cases for Wan 3.0 Image-to-Video API Integration
- Controlled Visual Transitions: Animate a planned movement between two keyframes for reveals, transformations, and scene changes.
- Product Motion Design: Turn product stills into launch sequences, camera moves, and promotional video assets.
- Character and Illustration Animation: Guide a subject from one pose or composition to another while providing motion direction in the prompt.
- Storyboard Prototyping: Connect selected frames to test shot timing, transition logic, and visual continuity before production.
- Social and Campaign Creative: Adapt existing brand images into landscape, portrait, square, and feed-ready motion assets.
Note Both frame images are required. PNG images must not contain an alpha channel. Align both frame compositions with the requested aspect ratio, and review transition continuity and artifacts before publishing.
Wan 3.0 Image-to-Video vs Competitors: Comparative Analysis
-
Wan 3.0 vs. Wan 2.7 Image-to-Video
Wan 2.7 can animate a start frame with optional end-frame guidance. Wan 3.0 requires both frames, making the intended beginning and ending explicit in every request. -
Wan 3.0 vs. Vidu Q3 Image-to-Video
Vidu Q3 supports image-led video workflows and transition variants. Wan 3.0 offers a Wan-family path centered on mandatory start-and-end-frame control. -
Wan 3.0 vs. PixVerse C1 Image-to-Video
PixVerse C1 separates first-frame animation and transition workflows. Wan 3.0 combines required endpoint images with one prompt and a consistent set of video controls. -
Wan 3.0 vs. Kling 3.0 Turbo Image-to-Video
Kling 3.0 Turbo targets fast image animation. Wan 3.0 is an alternative for teams that prioritize explicit final-frame direction within an Alibaba-oriented API workflow. -
Wan 3.0 vs. Veo 3.1 Image-to-Video
Veo 3.1 provides Google's image-to-video integration. Wan 3.0 gives developers another production option with required endpoint frames and flexible output settings.
Use the Wan 3.0 Image to Video 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.
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