Wan 2.1 I2V 720p

Wan 2.1 I2V 720p

Playground

Try it on WavespeedAI!

WAN 2.1 i2v converts images into unlimited 720P AI videos for scalable content generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.1 Image-to-Video 720p

Transform your static images into dynamic, cinematic videos with Wan 2.1 Image-to-Video 720p. This state-of-the-art model brings your photos to life with smooth motion, natural transitions, and high visual fidelity — all guided by simple text prompts.

Why It Stands Out

  • Image-driven generation: Start from any image and animate it into a coherent video while preserving the original style and composition.
  • Prompt-guided motion: Describe the action you want — camera movements, character expressions, environmental changes — and watch your vision unfold.
  • Negative prompt support: Exclude unwanted elements or artifacts for cleaner, more controlled outputs.
  • Prompt Enhancer: Built-in AI-powered prompt optimization helps you craft better descriptions for improved results.
  • Flexible duration: Generate 5-second or 10-second clips depending on your needs.
  • Reproducibility: Use the seed parameter to recreate exact results or iterate on variations.

Pricing

DurationPrice
5 seconds$0.30
10 seconds$0.45

Parameters

ParameterRequiredDescription
imageYesSource image (upload or public URL).
promptYesText description of desired motion and style.
negative_promptNoElements to avoid in the generated video.
sizeNoOutput resolution (default: 1280×720).
num_inference_stepsNoQuality/speed trade-off (default: 30).
durationNoVideo length in seconds: 5 or 10 (default: 5).
guidance_scaleNoPrompt adherence strength (default: 5).
flow_shiftNoMotion intensity control (default: 5).
seedNoSet for reproducibility; -1 for random.

How to Use

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

Best Use Cases

  • Social Media Content — Turn product photos or portraits into eye-catching video posts.
  • Marketing & Advertising — Animate hero images for campaigns without expensive video shoots.
  • Storytelling & Concept Art — Bring storyboards and illustrations to life for pitches and presentations.
  • E-commerce — Create dynamic product showcases from static photography.
  • Personal Projects — Animate family photos, travel shots, or creative artwork.

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.
  • Start with lower inference steps (20–25) for quick previews, then increase for final renders.
  • Use negative prompts to reduce artifacts like blur, distortion, or unwanted motion.
  • Fix the seed when iterating to compare the effect of different parameters.

Notes

  • Ensure uploaded images or URLs are publicly accessible.
  • Processing time varies based on duration and 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


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.1/i2v-720p" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "size": "1280*720",
    "num_inference_steps": 30,
    "duration": 5,
    "guidance_scale": 5,
    "flow_shift": 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

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-The image for generating the output.
promptstringYes-The positive prompt for the generation.
negative_promptstringNo-The negative prompt for the generation.
sizestringNo1280*7201280*720, 720*1280The 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_shiftnumberNo51.0 ~ 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
© 2025 WaveSpeedAI. All rights reserved.