Alibaba Wan 2.2 I2V Plus 480p
Playground
Try it on WavespeedAI!Generate unlimited AI videos with Alibaba WAN 2.2 image-to-video model.
Features
Alibaba WAN 2.2 Image-to-Video Plus (480p)
The Alibaba WAN 2.2 I2V-Plus model is a state-of-the-art image-to-video generator available on Alibaba Cloud’s DashScope platform. It uses an innovative Mixture of Experts (MoE) architecture to create smooth and realistic videos from static images at a 480p resolution. This model is designed for short, high-quality clips.
Why it looks great
- MoE architecture: dynamically directs tasks to specialized experts for improved detail and motion accuracy.
- Natural motion synthesis: creates smooth and realistic transitions from a still image.
- Detail preservation: keeps sharp textures and clear faces in dynamic shots.
- Temporal stability: reduces flicker and frame inconsistencies.
- Optimized for portraits: excels at transforming human photos into realistic talking or moving videos.
Limits and Performance
- Output resolution: fixed at 480p
- Max clip length per job: 5 seconds
- Processing speed: ~5–10 seconds of wall time per second of video (varies by queue and complexity)
Pricing
| Output Resolution | Cost per 5 seconds | Max Length |
|---|---|---|
| 480p | $0.20 | 5 seconds |
Billing Rules
- Minimum charge = 5 seconds (one clip)
- No partial billing — all jobs are billed as a 5-second generation
- Total cost = number of clips × $0.20
How to Use
- Upload a source image (clear, high-quality recommended).
- (Optional) Add a prompt to guide motion or scene style.
- Select output length (5 seconds).
- Run the job and download the 480p video.
Notes
- This version only supports 480p and up to 5 seconds per clip.
- For longer or higher-resolution outputs, check newer WAN versions (WAN 2.5).
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/alibaba/wan-2.2/i2v-plus-480p" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"duration": 5,
"enable_prompt_expansion": false,
"seed": -1
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| image | string | Yes | - | The image for generating the output. | |
| prompt | string | No | - | The positive prompt for the generation. | |
| duration | integer | No | 5 | 5 | The duration of the generated media in seconds. |
| enable_prompt_expansion | boolean | No | false | - | If set to true, the prompt optimizer will be enabled. |
| negative_prompt | string | No | - | The negative prompt for the generation. | |
| seed | integer | No | -1 | -1 ~ 2147483647 | The random seed to use for the generation. -1 means a random seed will be used. |
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Array of URLs to the generated content (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
| data.status | string | Status of the task: created, processing, completed, or failed |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |