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Gemini Omni Flash Reference to Video API

google /

Gemini Omni Flash Reference to Video creates short AI videos with synchronized audio from one or more reference images and a text prompt, preserving visual identity and following the provided references for guided multimodal video generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

image-to-video
इनपुट

निष्क्रिय

$0.16प्रति रन·~62 / $10

आगे:

उदाहरणसभी देखें

The man slowly moves his hand through frozen coffee droplets floating in the air. Outside the window, tunnel lights stretch into long blue lines, one passenger’s watch starts ticking again, and the camera rotates around the frozen subway car. Then look at the watch in Figure 2.

संबंधित मॉडल

README

Gemini Omni Flash Reference-to-Video

Gemini Omni Flash Reference-to-Video creates short videos from one or more reference images and a text prompt. Reference images can guide the subject, style, layout, and visual direction of the generated video, while the prompt controls motion, scene development, pacing, and audio direction.

Why Choose This?

  • Reference-to-video generation
    Generate a short video from multiple reference images and a text prompt.

  • Subject and style guidance
    Use reference images to guide characters, objects, visual style, layout, or scene composition.

  • Synchronized audio
    Generate audio together with the video output.

  • Prompt-guided motion
    Describe the scene, camera movement, subject behavior, pacing, and audio direction in natural language.

  • Simple aspect ratio control
    Choose 16:9 for landscape videos or 9:16 for portrait videos.

Parameters

ParameterRequiredDescription
imagesYesReference image URLs to incorporate into the video.
promptYesText prompt describing the video, including scene, motion, pacing, and audio direction.
aspect_ratioNoOutput aspect ratio: 16:9 or 9:16. Default: 16:9.
durationNoOutput duration in seconds. Range: 3 to 10. Default: 8.

How to Use

  1. Upload reference images — Provide one or more images to guide the subject, style, layout, or scene composition.
  2. Write your prompt — Describe the video scene, motion, camera behavior, pacing, and audio direction.
  3. Choose aspect ratio — Use 16:9 for landscape video or 9:16 for portrait video.
  4. Set duration — Choose a duration from 3 to 10 seconds.
  5. Submit — Generate the final video with synchronized audio.

Pricing

Pricing is $0.16 per second of generated video.

DurationPrice
3s$0.48
5s$0.80
8s$1.28
10s$1.60

Best Use Cases

  • Reference-guided video generation — Create videos using one or more images as visual references.
  • Character and subject consistency — Use reference images to guide people, products, objects, or visual identity.
  • Style-driven clips — Generate videos that follow a specific visual style, layout, or mood.
  • Audio-video scenes — Create short videos with synchronized sound from reference images and text.
  • Creative prototyping — Test video concepts, motion ideas, and scene directions from visual references.

Pro Tips

  • Use clear reference images that strongly represent the subject or style you want.
  • Use multiple references when character, object, or style consistency matters.
  • Be specific about motion, camera movement, pacing, and audio direction in the prompt.
  • Use 16:9 for landscape scenes and 9:16 for vertical mobile content.
  • Use shorter durations for quick testing and longer durations when the scene needs more time to develop.
नोट:यह वेबसाइट तृतीय पक्षों द्वारा प्रदान किए गए AI मॉडलों का उपयोग करती है।

Gemini Omni Flash Reference To Video API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/google/gemini-omni-flash/reference-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Gemini Omni Flash Reference To Video below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "images": [
        "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
    ],
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "16:9",
    "duration": 8
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/google/gemini-omni-flash/reference-to-video" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; 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' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$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
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/google/gemini-omni-flash/reference-to-video";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "images": [
                "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
        ],
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "aspect_ratio": "16:9",
        "duration": 8
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "images": [
        "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
    ],
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "aspect_ratio": "16:9",
    "duration": 8
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/google/gemini-omni-flash/reference-to-video", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Gemini Omni Flash Reference To Video API — Frequently asked questions

What is the Gemini Omni Flash Reference To Video API?

Gemini Omni Flash Reference To Video is a Google model for video generation from images, exposed as a REST API on WaveSpeedAI. Gemini Omni Flash Reference to Video creates short AI videos with synchronized audio from one or more reference images and a text prompt, preserving visual identity and following the provided references for guided multimodal video generation. 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 Gemini Omni Flash 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/google/google-gemini-omni-flash-reference-to-video.

How much does Gemini Omni Flash Reference To Video cost per run?

Gemini Omni Flash Reference To Video starts at $0.16 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 Gemini Omni Flash Reference To Video accept?

Key inputs: `prompt`, `images`, `aspect_ratio`, `duration`. 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-gemini-omni-flash-reference-to-video.

How long does Gemini Omni Flash Reference To Video take to generate?

Median end-to-end generation time on WaveSpeedAI is around 45 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Gemini Omni Flash 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.

Gemini Omni Flash Reference to Video API | WaveSpeedAI