Hunyuan Video T2V

Hunyuan Video T2V

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Hunyuan Video (t2v) is an advanced text-to-video model that generates high-quality videos from text prompts. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Transform your ideas into stunning videos with Hunyuan Video Text-to-Video. This state-of-the-art model from Tencent generates high-quality 720p videos directly from text descriptions — bringing your imagination to life with smooth motion and cinematic visuals.

Why It Stands Out

  • Pure text-to-video generation: No source image required — simply describe your vision and watch it unfold.
  • HD output: Generate crisp 1280×720 videos with rich detail and visual clarity.
  • Prompt Enhancer: Built-in AI-powered prompt optimization helps craft better descriptions for improved results.
  • Smooth motion: Advanced temporal modeling ensures natural, fluid movement across frames.
  • Flexible sizing: Multiple aspect ratio options to fit your content needs.
  • Reproducibility: Use the seed parameter to recreate exact results or explore variations.

Pricing

OutputPrice
Per video$0.40

Parameters

ParameterRequiredDescription
promptYesText description of the video you want to generate.
sizeNoOutput resolution (default: 1280×720).
seedNoSet for reproducibility; -1 for random.
num_inference_stepsNoQuality/speed trade-off (default: 30).

How to Use

  1. Write a prompt describing the scene, characters, action, and style you want. Use the Prompt Enhancer for AI-assisted optimization.
  2. Select size — choose the aspect ratio that fits your content.
  3. Adjust inference steps — higher values may improve quality at the cost of speed.
  4. Set a seed (optional) for reproducible results.
  5. Click Run and wait for your video to generate.
  6. Preview and download the result.

Best Use Cases

  • Social Media Content — Create viral-worthy video clips for TikTok, Reels, and Shorts.
  • Marketing & Advertising — Produce concept videos and promotional content without filming.
  • Storytelling & Animation — Generate scenes for short films, music videos, or creative projects.
  • Game & App Previews — Create cinematic trailers and gameplay concepts from descriptions.
  • Educational Content — Visualize complex concepts and scenarios for learning materials.

Pro Tips for Best Quality

  • Be detailed in your prompt — describe subject, action, environment, lighting, mood, and camera movement.
  • Include style keywords like “cinematic,” “realistic,” “anime,” or “futuristic” to guide the aesthetic.
  • Start with lower inference steps for quick previews, then increase for final renders.
  • Fix the seed when iterating to compare the effect of different prompt adjustments.
  • Keep prompts focused — overly complex descriptions may dilute the output quality.

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,
  "num_inference_steps": 30
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/hunyuan-video/t2v" \
  -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.
num_inference_stepsintegerNo302 ~ 30The number of inference steps to perform.

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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