Wan 2.1 T2V 720p

Wan 2.1 T2V 720p

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WAN 2.1 T2V 720P offers text-to-video 720p generation from prompts, enabling unlimited AI video creation for social and marketing. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.1 Text-to-Video 720p

Create cinematic-quality videos from text descriptions with Wan 2.1 Text-to-Video 720p. This powerful model transforms your written prompts into stunning 720p HD videos with smooth motion, rich detail, and professional visual quality — no source footage required.

Why It Stands Out

  • Pure text-to-video generation: Describe any scene, character, or action and watch it come to life in HD.
  • Cinematic quality: 720p resolution delivers sharp, detailed visuals suitable for professional use.
  • Prompt Enhancer: Built-in AI-powered prompt optimization helps you craft better descriptions for improved results.
  • Negative prompt support: Exclude unwanted elements for cleaner, more controlled outputs.
  • 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
promptYesText description of the video you want to generate.
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. Write a prompt describing the scene, action, and style you want. Use the Prompt Enhancer for AI-assisted optimization.
  2. Set parameters — adjust size, duration, guidance scale, and other settings as needed.
  3. Add a negative prompt (optional) to exclude unwanted elements.
  4. Click Run and wait for your video to generate.
  5. Preview and download the result.

Best Use Cases

  • Social Media Content — Create high-quality video content for YouTube, Instagram, and TikTok.
  • Marketing & Advertising — Produce concept videos, ad creatives, and promotional clips without filming.
  • Storytelling & Animation — Generate scenes for short films, music videos, or narrative projects.
  • Game & App Trailers — Create cinematic trailers and gameplay concepts from descriptions.
  • Creative Exploration — Bring any imaginable scene to life for art projects and experimentation.

Pro Tips for Best Quality

  • Be detailed in your prompt — describe subject appearance, action, environment, lighting, mood, and camera movement.
  • Use negative prompts to reduce common artifacts: blur, distortion, jitter, watermarks, or low quality.
  • Start with lower inference steps for quick previews, then increase for final renders.
  • Fix the seed when iterating to compare the effect of different parameters.
  • For complex scenes, break down the description into clear visual elements.

Notes

  • 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/t2v-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
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
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