Wan 2.2 T2V 480p

Playground

Generate unlimited AI videos with Wan 2.2 text to video model.

Features

Wan 2.2 AI Video Model

Wan 2.2 is a new generation multimodal generative model launched by WAN AI. This model adopts an innovative MoE (Mixture of Experts) architecture, consisting of high-noise and low-noise expert models. It can divide expert models according to denoising timesteps, thus generating higher quality video content.

Key Features of Wan 2.2

cinematic-level aesthetic control, deeply integrating professional film industry aesthetic standards, supporting multi-dimensional visual control such as lighting, color, and composition;
large-scale complex motion, easily restoring various complex motions and enhancing the smoothness and controllability of motion;
precise semantic compliance, excelling in complex scenes and multi-object generation, better restoring users’ creative intentions. The model supports multiple generation modes such as text-to-video and image-to-video, suitable for content creation, artistic creation, education and training, and other application scenarios.

Model Highlights

Cinematic-level Aesthetic Control: Professional camera language, supports multi-dimensional visual control such as lighting, color, and composition
Large-scale Complex Motion: Smoothly restores various complex motions, enhances motion controllability and naturalness
Precise Semantic Compliance: Complex scene understanding, multi-object generation, better restoring creative intentions

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/wavespeed-ai/wan-2.2/t2v-480p" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "prompt": "",
    "size": "832*480",
    "duration": 5,
    "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
prompt	string	Yes		-	The prompt for generating the output.
size	string	No	832*480	832480, 480832	The size of the generated media in pixels (width*height).
duration	integer	No	5	5, 8	The duration of the generated media in seconds.
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

Result Query Parameters

Result Request Parameters

Parameter	Type	Required	Default	Description
id	string	Yes	-	Task ID

Result Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data	object	The prediction data object containing all details
data.id	string	Unique identifier for the prediction, the ID of the prediction to get
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

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