Browse ModelsWavespeed AIWan 2.1 I2V 480p Ultra Fast

Wan 2.1 I2V 480p Ultra Fast

Wan 2.1 I2V 480p Ultra Fast

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Wan 2.1 i2v 480p Ultra-Fast enables unlimited image-to-video generation at 480p for fast, reliable video creation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.1 Image-to-Video 480p Ultra Fast

Wan 2.1 Image-to-Video 480p Ultra Fast is a lightning-fast image-to-video generation model optimized for speed and efficiency. Transform static images into dynamic videos in seconds — perfect for rapid iteration, previews, and high-volume processing.


Why It Stands Out

  • Ultra-fast processing: Optimized for speed without sacrificing quality.
  • Image-driven generation: Animate any image while preserving its original style.
  • Prompt-guided motion: Describe camera movements, actions, and atmospheric effects.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Negative prompt support: Exclude unwanted elements for cleaner outputs.
  • Fine-tuned control: Adjust guidance scale and flow shift for precise results.
  • Affordable pricing: Cost-effective option for prototyping and batch processing.
  • Reproducibility: Use the seed parameter to recreate exact results.

Parameters

ParameterRequiredDescription
imageYesSource image to animate (upload or public URL).
promptYesText description of desired motion and style.
negative_promptNoElements to avoid in the output.
sizeNoOutput resolution (default: 832×480).
num_inference_stepsNoQuality/speed trade-off (default: 30).
durationNoVideo length: 5 or 10 seconds (default: 5).
guidance_scaleNoPrompt adherence strength (default: 5).
flow_shiftNoMotion flow control (default: 3).
seedNoSet for reproducibility; -1 for random.

How to Use

  1. Upload your source image — drag and drop a file or paste a public URL.
  2. Write a prompt describing the motion, camera movement, and atmosphere you want. Use the Prompt Enhancer for AI-assisted optimization.
  3. Add a negative prompt (optional) — specify elements to exclude.
  4. Adjust parameters — set duration, guidance scale, and other settings as needed.
  5. Click Run and wait for your video to generate.
  6. Preview and download the result.

Best Use Cases

  • Rapid Prototyping — Quickly test animation concepts before committing to higher resolutions.
  • Batch Processing — Transform multiple images into videos affordably at scale.
  • Content Previews — Generate quick previews for client approval.
  • Social Media Content — Create stylized videos for platforms where 480p is sufficient.
  • Creative Exploration — Experiment with different animations at minimal cost.

Pricing

DurationPrice
5 seconds$0.125
10 seconds$0.1875

Pro Tips for Best Quality

  • Use high-resolution, well-lit source images for optimal results.
  • Be specific in your prompt — describe camera movement, subject actions, and atmospheric details.
  • Use negative prompts to reduce artifacts like blur, distortion, or unwanted motion.
  • Start with 480p Ultra Fast for testing, then upgrade to 720p for final delivery.
  • Fix the seed when iterating to compare different prompt variations.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Processing time is optimized for speed — expect quick turnaround.
  • For higher resolution output, consider Wan 2.1 I2V 720p.
  • Please ensure your prompts comply with content guidelines.

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-ultra-fast" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "size": "832*480",
    "num_inference_steps": 30,
    "duration": 5,
    "guidance_scale": 5,
    "flow_shift": 3,
    "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

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-The image for generating the output.
promptstringYes-The positive prompt for the generation.
negative_promptstringNo-The negative prompt for the generation.
sizestringNo832*480832*480, 480*832The size of the generated media in pixels (width*height).
num_inference_stepsintegerNo301 ~ 40The number of inference steps to perform.
durationintegerNo55 ~ 10The duration of the generated media in seconds.
guidance_scalenumberNo50.00 ~ 20.00The guidance scale to use for the generation.
flow_shiftnumberNo31.0 ~ 10.0The shift value for the timestep schedule for flow matching.
seedintegerNo-1-1 ~ 2147483647The random seed to use for the generation. -1 means a random seed will be used.

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 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, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray 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.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
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