Browse ModelsViduVidu Text To Video 2.0

Vidu Text To Video 2.0

Vidu Text To Video 2.0

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Vidu Text-to-Video 2.0 converts text prompts into high-quality 720p videos with exceptional visual detail and diverse motion dynamics. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

🎬 Vidu Text-to-Video 2.0

Vidu Text-to-Video 2.0 turns your imagination into motion — a next-generation text-to-video model that produces cinematic 720p videos with smooth, expressive, and visually coherent motion. Now with flexible duration control, you can generate 5s or 8s clips for storytelling, concept visualization, or creative motion studies.


🌟 Why it looks amazing

  • Cinematic realism: generates film-like motion, lighting, and depth of field.
  • Temporal consistency: prevents flicker and ghosting between frames.
  • Expressive movement: animates both camera and subject naturally for lifelike motion.
  • Scene understanding: interprets your text prompt accurately to match composition, emotion, and action.
  • 720p output: crisp visuals ready for editing, sharing, or production use.

⚙️ Parameters and Controls

  • prompt — describe your scene (e.g., “A woman walking through a rainy street under neon lights”).

  • movement_amplitude — controls the motion strength of objects in the frame:

    • auto (default): automatically adjusts motion scale.
    • small: subtle, gentle movements (good for portraits or static shots).
    • medium: balanced motion, ideal for everyday scenes.
    • large: dramatic, cinematic camera or subject motion.
  • duration — select video length:

    • 5: short clips, ideal for previews or teasers.
    • 8: extended motion for storytelling or scene development.
  • seed — use a fixed number for reproducibility or leave empty for random generation.


💰 Pricing

ResolutionDurationCost per Clip
720p5s$0.60
720p8s$0.60

🚀 How to Use

  1. ✍️ Write your prompt describing the scene or story.
  2. 🎥 Choose movement_amplitude (auto, small, medium, or large).
  3. ⏱️ Select duration (5 or 8 seconds).
  4. 🎲 Optionally set a seed for reproducibility.
  5. ▶️ Click Run to generate your cinematic video.

💡 Pro Tips

  • Keep prompts concise but descriptive — include subject, setting, and atmosphere.
  • Use small amplitude for subtle character shots, large for dynamic scenes.
  • Choose 8s duration for narrative continuity or action sequences.
  • Experiment with different seeds to explore creative variations.

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/vidu/text-to-video-2.0" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "duration": 5,
    "resolution": "720p",
    "movement_amplitude": "auto"
}'

# 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.
durationintegerNo55, 8The duration of the generated media in seconds.
resolutionstringNo720p720pThe resolution of the generated media.
movement_amplitudestringNoautoauto, small, medium, largeThe movement amplitude of objects in the frame. Defaults to auto, accepted value: auto small medium large.
seedintegerNo--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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