Wan 2.2 I2V 5b 720p API Documentation

Wan 2.2 I2V 5b 720p API Documentation

Playground

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Wan 2.2 I2V 5B converts images into high-quality 720P videos using a 5B image-to-video model for AI video generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.2 Image-to-Video 5B 720p is a powerful image-to-video generation model built on a 5 billion parameter architecture. Transform static images into dynamic 720p HD videos with smooth motion and cinematic quality — all at an incredibly affordable price.


Why It Stands Out

  • 5B parameter model: Large-scale architecture for superior video quality and motion understanding.
  • Image-driven generation: Animate any image while preserving its original style and composition.
  • HD 720p output: Generate crisp videos with rich detail and visual clarity.
  • Ultra-affordable: High-quality video generation at just $0.05 per video.
  • Prompt-guided motion: Describe camera movements, actions, and atmospheric effects.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Reproducibility: Use the seed parameter to recreate exact results or explore variations.

Parameters

ParameterRequiredDescription
imageYesSource image to animate (upload or public URL).
promptYesText description of desired motion and style.
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. Set a seed (optional) for reproducible results.
  4. Click Run and wait for your video to generate.
  5. Preview and download the result.

Best Use Cases

  • Social Media Content — Turn photos into engaging video posts for TikTok, Reels, and Shorts.
  • Marketing & Advertising — Animate product images and hero shots affordably.
  • Storytelling & Art — Bring illustrations, portraits, and artwork to life.
  • E-commerce — Create dynamic product showcases from static photography.
  • Creative Exploration — Experiment with different animations at minimal cost.

Pricing

OutputPrice
Per video$0.05

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.
  • Include motion keywords like “slow pan,” “tracking shot,” “zoom in,” or “drifting.”
  • Describe environmental effects like dust, wind, light rays, or clouds for added realism.
  • Fix the seed when iterating to compare different prompt variations.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Processing time varies based on current queue load.
  • Please ensure your prompts comply with content guidelines.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2/i2v-5b-720p" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagestringYes-The image for generating the output.
seedintegerNo-1-The 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.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (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

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.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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