Wan 2.2 T2V 720p LoRA
Playground
Try it on WavespeedAI!Wan 2.2 T2V 720p with custom LoRA support turns text prompts into 720p AI videos and enables unlimited video generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
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-720p-lora" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"size": "1280*720",
"duration": 5,
"seed": -1
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| negative_prompt | string | No | - | The negative prompt for the generation. | |
| size | string | No | 1280*720 | 1280*720, 720*1280 | The size of the generated media in pixels (width*height). |
| duration | integer | No | 5 | 5, 8 | The duration of the generated media in seconds. |
| loras | array | No | max 3 items | List of LoRAs to apply (max 3). | |
| loras[].path | string | Yes | - | Path to the LoRA model | |
| loras[].scale | float | Yes | - | 0.0 ~ 4.0 | Scale of the LoRA model |
| high_noise_loras | array | No | - | - | List of high noise LoRAs to apply (max 3). |
| low_noise_loras | array | No | - | - | List of low noise LoRAs to apply (max 3). |
| 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 |