Veo3.1 Reference to Video | Fast Image-to-Video API

Google Veo 3.1 — Reference-to-Video Model

Veo 3.1 Reference-to-Video brings static images to life by combining visual reference consistency with cinematic motion generation. Powered by Google DeepMind’s next-generation Veo 3.1 architecture, this model transforms up to three reference images into coherent 5-second videos with smooth motion, accurate visual alignment, and synchronized native audio.

🌟 Key Features

🧠 Multi-Image Reference Support

Accepts up to three reference images to define the subject, environment, or style.
Maintains consistent identity, lighting, and appearance across frames.
Ideal for animating people, objects, or scenes with reliable fidelity.

🎬 Cinematic Video Generation

Produces 5-second motion clips at 1080p or 720p resolution.
Adds camera dynamics such as panning, zooming, or subtle perspective drift.
Supports synchronized audio generation, matching dialogue or ambient context.

💡 Smart Prompt Adherence

Interprets both text instructions and visual cues for precise motion storytelling.
Automatically harmonizes character interactions, props, and backgrounds.

⚙️ Capabilities

Input:
Up to 3 reference images (JPEG / PNG / WEBP)
Text prompt describing motion, action, and scene context
Output:
8-second MP4 video (720p or 1080p)
Optional synchronized audio
Negative Prompt (optional):
Exclude unwanted artifacts or elements (e.g., “no text”, “no flicker”).
Seed (optional):
Reproduce specific results for consistent creative control.

💰 Pricing

Duration	Resolution	With Audio	Without Audio
8 seconds	720p	$3.20	$1.60
8 seconds	1080p	$3.20	$1.60

✅ Commercial use allowed

🧩 How to Use

Upload up to 3 reference images — define the subject, object, or visual style.
Write a text prompt — describe the action, setting, and camera motion.
(Optional) Add a negative prompt to remove unwanted details.
Choose resolution (720p or 1080p).
(Optional) Enable audio generation for synchronized sound.
Click Run to generate your 5-second cinematic video.

💡 Best Practices

Use clear, well-lit reference images with similar styles and proportions.
Keep prompts concise but specific (e.g., “The man in image 1 waves to the penguins in image 2 under bright sunlight”).
Avoid overly complex scenarios with many characters or fast movement.
Enable audio for more immersive storytelling results.

📝 Notes

Ensure uploaded images are valid and accessible URLs or uploaded locally.
If the output looks unstable, reduce reference count or simplify the prompt.
Follow Google’s content safety rules; modify the prompt if flagged.
For best performance, prefer portrait-oriented subjects and balanced lighting.

Veo3.1 Reference To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/google/veo3.1/reference-to-video with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Veo3.1 Reference To Video below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/google/veo3.1/reference-to-video" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "resolution": "1080p",
    "generate_audio": true,
    "negative_prompt": "blurry, low quality, distorted",
    "seed": 0
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("google/veo3.1/reference-to-video", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "resolution": "1080p",
        "generate_audio": true,
        "negative_prompt": "blurry, low quality, distorted",
        "seed": 0
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "google/veo3.1/reference-to-video",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "resolution": "1080p",
    "generate_audio": true,
    "negative_prompt": "blurry, low quality, distorted",
    "seed": 0
}
)

print(output["outputs"][0])  # → URL of the generated output

Veo3.1 Reference To Video API — Frequently asked questions

What is the Veo3.1 Reference To Video API?

Veo3.1 Reference To Video is a Google model for video generation from images, exposed as a REST API on WaveSpeedAI. Google Veo3.1 Reference-to-Video performs image-to-video generation that preserves a specific subject's appearance and identity from provided reference images, enabling consistent character or product motion across frames. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Veo3.1 Reference To Video API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/google/google-veo3.1-reference-to-video.

How much does Veo3.1 Reference To Video cost per run?

Veo3.1 Reference To Video starts at $3.20 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Veo3.1 Reference To Video accept?

Key inputs: `prompt`, `images`, `resolution`, `seed`, `negative_prompt`, `generate_audio`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/google/google-veo3.1-reference-to-video.

How long does Veo3.1 Reference To Video take to generate?

Average end-to-end generation time on WaveSpeedAI is around 327 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Veo3.1 Reference To Video outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Google). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

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