WaveSpeedAI APIWan I2V 480p LoRA

Wan I2V 480p LoRA

Wan-2.1 i2v model with LoRA, generate high-quality videos with superior visual quality and motion diversity

Features

Wan2.1-i2v-480p-lora is an open-source AI video generation model developed by Alibaba Cloud, designed for image-to-video tasks. It incorporates Low-Rank Adaptation (LoRA) techniques, enabling efficient fine-tuning of pre-trained models to generate videos with specified effects from reference images. 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-i2v-480p-lora 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

  • Exceptional Image-to-Video Performance: Specially optimized for converting images into videos, WAN-2.1/i2v-480p-lora delivers state-of-the-art visual quality and natural motion dynamics.
  • Trained on the Wan2.1 14B 480p I2V base model.
  • Consistent results across different object types .
  • Simple prompt structure that's easy to adapt.
  • Squish :Transform any image into a video of it being rotated.
  • Rotate : Transform any image into a video of it being squished.
  • Cakeify:Transform any image into a video of it being cakeified.
  • Crush:Transform any image into a video of it being crushed.
  • Painting:Transform any image into a video of the subject as a historic painting version of themselves!
  • Deflate:Transform any image into a video of it being deflated.
  • Optimized for Speed: Leveraging advanced inference acceleration techniques from WaveSpeedAI, the system minimizes computational overhead and latency, ensuring rapid video generation without sacrificing output quality.

ComfyUI

wan-2.1/i2v-480p-lora 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: WAN-2.1/i2v-480p-lora is designed exclusively for creative image-to-video transformation and is not intended for generating factually accurate content.
  • Statistical Biases: As with other data-driven models, there is potential for inadvertently propagating biases found in its training data.
  • Prompt Sensitivity: The model’s performance is influenced by the clarity and precision of the input image; less detailed images may lead to variations in output quality.
  • Scope of Functionality: This model is solely focused on image-to-video generation and does not support other video generative tasks such as text-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/i2v-480p-lora" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "image": "https://d2g64w682n9w0w.cloudfront.net/media/images/1745077093052414125_462ZVSNL.jpg",
    "prompt": "The video opens with a cat woman. As the video progresses, the cat woman begins to d3d1at3 deflate it, gradually shrinking and losing shape, eventually flattening completely into a lifeless, deflated mass on the ground",
    "negative_prompt": "",
    "loras": [
        {
            "path": "Remade-AI/Deflate",
            "scale": 1
        }
    ],
    "size": "832*480",
    "num_inference_steps": 30,
    "duration": 5,
    "guidance_scale": 5,
    "flow_shift": 3,
    "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

ParameterTypeRequiredDefaultRangeDescription
imagestringYeshttps://d2g64w682n9w0w.cloudfront.net/media/images/1745077093052414125_462ZVSNL.jpg-The image for generating the output.
promptstringYesThe video opens with a cat woman. As the video progresses, the cat woman begins to d3d1at3 deflate it, gradually shrinking and losing shape, eventually flattening completely into a lifeless, deflated mass on the ground-The prompt for generating the output.
negative_promptstringNo--The negative prompt for generating the output.
lorasarrayNo[]max 3 itemsThe LoRA weights for generating the output.
loras[].pathstringYes-Path to the LoRA model
loras[].scalefloatYes-0.0 ~ 4.0Scale of the LoRA model
sizestringNo832*480832*480, 480*832The size of the output.
num_inference_stepsintegerNo301 ~ 40The number of inference steps.
durationintegerNo55 ~ 10Generate video duration length seconds.
guidance_scalenumberNo51.01 ~ 10.00The guidance scale for generation.
flow_shiftnumberNo31.0 ~ 10.0The shift value for the timestep schedule for flow matching.
seedintegerNo-1-1 ~ 9999999999The seed for random number generation.
enable_safety_checkerbooleanNotrue-Whether to enable the safety checker.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Query Parameters

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
© 2025 WaveSpeedAI. All rights reserved.