Google Veo3.1 Fast Image To Video

Google Veo3.1 Fast Image To Video

Playground

Google Veo 3.1 Fast is an Image-to-Video model with native 1080p output for high-detail videos from images and fast performance. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Veo 3 I2V Fast is the high-speed, cost-optimized variant of Google DeepMind’s Veo 3 image-to-video model. It transforms static images into cinematic 1080p videos with smooth, realistic motion and natural lighting — all while delivering results up to 30% faster than the standard version. Perfect for creators who need rapid, high-quality motion generation for social content, concept visualization, and creative storytelling.

🎬 Why it stands out

• From Image to Motion Transform a single image into a natural, dynamic video sequence while preserving its original composition and style.

• Cinematic Realism Produces high-fidelity motion with natural lighting, accurate perspective, and fluid camera transitions.

• Native Audio Generation Automatically generates synchronized sound—including ambient noise, effects, and light music—perfectly aligned with the visuals.

• Dialogue & Lip-Sync Enables speaking characters or realistic expressions, ideal for storytelling, marketing, and short-form content.

• Consistent Subject & Style Retains the identity, color tone, and visual integrity of your input image throughout the motion sequence.

💰 Pricing

Every run needs $1.2 (both 720p and 1080p)

Without audio needs $0.8

✅ Commercial use allowed

🚀 How to Use

1. Upload an Image Choose a clear, high-quality still image—this defines the subject, framing, and overall style.

2. Write a Prompt Describe the desired motion, mood, and camera movement.

> Example: “Slow cinematic zoom out as wind moves through the trees and sunlight flickers across the leaves.”

3. Adjust Settings Select the video duration (up to 8 seconds) and output resolution (up to 1080p).

4. Generate the Video Submit your prompt and image—Veo 3 I2V automatically creates motion, lighting, and audio.

5. Preview & Download Review the result, refine the prompt if needed, and download the final MP4.

💡 Pro Tips

• Use bright, high-contrast images for clearer motion and lighting.
• Keep prompts focused on a single subject or action for best stability.
• Add camera directions like “tracking shot,” “slow pan,” or “handheld style” to control movement.
• Specify lighting and mood (e.g., bright daylight, soft sunset glow).
• Avoid conflicting motion requests to maintain smooth results.

📝 Notes

• Actual processing time depends on queue load and resolution.
• Optimized for cinematic shorts, ads, and social media clips.
• Ensure your uploaded image is clear, accessible, and legally usable.
• Please ensure your prompts comply with Google’s Safety Guidelines — if an error occurs, revise your prompt and try again.

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",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "aspect_ratio": "16:9",
  "duration": 8,
  "resolution": "1080p",
  "generate_audio": true
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/google/veo3.1-fast/image-to-video" \
  -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

Response Parameters

Result Request Parameters

Result Response Parameters