Wan T2V 720p
Turbo-charged inference for Wan 2.1 14B. Unleashing high-res text-to-video prowess with cutting-edge suite of video foundation models
Features
Wan2.1/t2v-720p is an open-source AI video generation model developed by Alibaba Cloud, designed for text-to-video tasks. The 14-billion-parameter professional version excels in generating complex motions and simulating physical dynamics, delivering exceptional performance.
Built upon a causal 3D Variational Autoencoder (VAE) and Video Diffusion Transformer architecture, Wan2.1/t2v-720p efficiently models spatiotemporal dependencies. In the authoritative VBench evaluation, the 14B version achieved a leading score of 86.22%, surpassing models like Sora, Luma, and Pika, and securing the top position. The model is available on Wavespeed AI, providing convenient access for developers.
Key Features
- High-Resolution Video Output: Capable of generating sharp 720p videos from text prompts, ensuring superior visual quality and motion diversity.
- State-of-the-Art Performance: Consistently outperforms existing open-source and commercial solutions across multiple benchmarks, setting a new standard in text-to-video generation.
- Consumer-Grade GPU Compatibility: Optimized to run efficiently on widely available hardware, enabling broad accessibility for developers and creators.
- Accelerated Inference: Utilizes advanced acceleration techniques to reduce latency and computational overhead, enabling faster video generation without compromising quality.
- Multilingual Text Generation: Supports the generation of videos containing text in both Chinese and English, enhancing its adaptability for global applications.
- Powerful Video VAE: Integrates a robust variational autoencoder capable of encoding and decoding 1080p videos while preserving temporal information, making it an ideal foundation for video generation.
ComfyUI
wan-2.1/t2v-720p is also available on ComfyUI, providing local inference capabilities through a node-based workflow, ensuring flexible and efficient image generation on your system.
Limitations
- Creative Focus: Designed for creative video synthesis from text; not intended for generating factually accurate or reliable content.
- Inherent Biases: As with any data-driven model, outputs may reflect biases present in the training data.
- Input Sensitivity: The quality and consistency of generated videos depend significantly on the quality of the input text prompt; subtle variations may lead to output variability.
- Task Scope: This model is exclusively built for text-to-video conversion at high resolution and does not support additional video generation tasks such as image-to-video or video editing.
Out-of-Scope Use
The model and its derivatives may not be used in any way that violates applicable national, federal, state, local, or international law or regulation, including but not limited to:
- Exploiting, harming, or attempting to exploit or harm minors, including solicitation, creation, acquisition, or dissemination of child exploitative content.
- Generating or disseminating verifiably false information with the intent to harm others.
- Creating or distributing personal identifiable information that could be used to harm an individual.
- Harassing, abusing, threatening, stalking, or bullying individuals or groups.
- Producing non-consensual nudity or illegal pornographic content.
- Making fully automated decisions that adversely affect an individual’s legal rights or create binding obligations.
- Facilitating large-scale disinformation campaigns.
Accelerated Inference
Our accelerated inference approach leverages advanced optimization technology from WavespeedAI. This innovative fusion technique significantly reduces computational overhead and latency, enabling rapid image generation without compromising quality. The entire system is designed to efficiently handle large-scale inference tasks while ensuring that real-time applications achieve an optimal balance between speed and accuracy. For further details, please refer to the blog post.
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-2.1/t2v-720p" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"prompt": "A rugged male secret agent in a torn tactical suit sprints through a war-torn urban alley, pistol in one hand, a bleeding gash on his brow. His eyes are sharp and calculating, sweat glistening on his tense face. Explosions light up the background as he dives into cover in slow motion",
"negative_prompt": "",
"size": "1280*720",
"num_inference_steps": 30,
"duration": 5,
"guidance_scale": 5,
"flow_shift": 5,
"seed": -1,
"enable_safety_checker": true
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
Parameter | Type | Required | Default | Range | Description |
---|---|---|---|---|---|
prompt | string | Yes | A rugged male secret agent in a torn tactical suit sprints through a war-torn urban alley, pistol in one hand, a bleeding gash on his brow. His eyes are sharp and calculating, sweat glistening on his tense face. Explosions light up the background as he dives into cover in slow motion | - | The prompt for generating the output. |
negative_prompt | string | No | - | - | The negative prompt for generating the output. |
size | string | No | 1280*720 | 1280*720, 720*1280 | The size of the output. |
num_inference_steps | integer | No | 30 | 0 ~ 40 | The number of inference steps. |
duration | integer | No | 5 | 5 ~ 10 | Generate video duration length seconds. |
guidance_scale | number | No | 5 | 1.01 ~ 10.00 | The guidance scale for generation. |
flow_shift | number | No | 5 | 1.0 ~ 10.0 | The shift value for the timestep schedule for flow matching. |
seed | integer | No | -1 | -1 ~ 9999999999 | The seed for random number generation. |
enable_safety_checker | boolean | No | true | - | Whether to enable the safety checker. |
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 |
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 |