Wan 2.2 T2V 5b 720p

Wan 2.2 T2V 5b 720p

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Wan 2.2 T2V 5B is a 720P text-to-video model that generates unlimited AI videos from simple text prompts, producing consistent high-quality 720p outputs. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Wan 2.2 Text-to-Video 5B 720p is a powerful text-to-video generation model built on a 5 billion parameter architecture. Generate high-quality 720p HD videos from text descriptions at an incredibly affordable price — perfect for content creators, marketers, and creative projects.


Why It Stands Out

  • 5B parameter model: Large-scale architecture for superior video quality and prompt understanding.
  • HD 720p output: Generate crisp 1280×720 videos with rich detail and visual clarity.
  • Ultra-affordable: High-quality video generation at just $0.05 per video.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Smooth motion: Advanced temporal modeling ensures natural, fluid movement.
  • Reproducibility: Use the seed parameter to recreate exact results or explore variations.

Parameters

ParameterRequiredDescription
promptYesText description of the video you want to generate.
sizeNoOutput resolution (default: 1280×720).
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. Select size — choose the resolution that fits your needs.
  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 — Create engaging video clips for TikTok, Reels, and Shorts.
  • Marketing & Advertising — Produce concept videos and promotional content affordably.
  • Storytelling & Animation — Generate scenes for short films and creative projects.
  • Rapid Prototyping — Test video concepts quickly before committing to higher budgets.
  • Creative Exploration — Experiment with different prompts and styles at minimal cost.

Pricing

OutputPrice
Per video$0.05

Pro Tips for Best Quality

  • Be detailed in your prompt — describe subject, action, environment, lighting, and mood.
  • Include style keywords like “cinematic,” “realistic,” “anime,” or “documentary” to guide the aesthetic.
  • Describe camera movements like “slow pan,” “tracking shot,” or “static wide angle.”
  • Keep prompts focused — overly complex descriptions may dilute the output quality.
  • Fix the seed when iterating to compare different prompt adjustments.

Notes

  • 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",
  "size": "1280*720",
  "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/t2v-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.
sizestringNo1280*7201280*720, 720*1280The size of the generated media in pixels (width*height).
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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