Gemini Omni Flash Text-to-Video

Gemini Omni Flash Text-to-Video is Google DeepMind's flagship unified multimodal model under the Gemini Omni series. Integrating Gemini's advanced reasoning with Veo's video generation capability, it enables native "any-to-any" generation, producing high-quality 24 FPS videos with synchronized audio directly from text prompts. It supports 16:9 and 9:16 aspect ratios, 3–10s video duration, and up to 1080P/4K supersampled output. Featuring multi-turn conversational video editing with context retention and built-in SynthID digital watermarking, it is ideal for short-form video creation, commercial ads, film VFX, and multimodal Agent workflows.

Gemini Omni Flash Text-to-Video

Base URL

https://api.icreat.ai

Authentication

All API requests must be authenticated with an API Key. You can obtain an API Key from the console.

export ICREAT_API_KEY="your-api-key-here"

HTTP Request Headers

import os

API_KEY = os.environ.get("ICREAT_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer " + API_KEY,
}

Protect your API Key

Never expose your API Key in client-side code or public repositories. Use environment variables or a backend proxy.

Code Examples

Image and video generation uses a two-step async flow: submit a task to get task_id, then poll via query task result; the response includes status and result ([] while processing; on SUCCEEDED, result holds resources and costUSD is present). The examples below use the same task_id across both steps.

1. Submit Task

Send a generation request to the submit endpoint.

POST/v1/task/submit/atlas/gemini-omni-flash/text-to-video

curl --fail-with-body --connect-timeout 10 --max-time 60 \
  -X POST https://api.icreat.ai/v1/task/submit/atlas/gemini-omni-flash/text-to-video \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -H "X-ICREAT-AI-GROUP: atlas" \
  -d '{
  "input": [
    {
      "type": "text",
      "text": "Slowly pan the camera to reveal the changing light and shadows within the still image"
    },
    {
      "type": "image",
      "url": "https://example.com/example.png"
    }
  ],
  "response_format": {
    "type": "video",
    "aspect_ratio": "9:16",
    "duration": 4,
    "resolution": "720p"
  }
}'

2. Query Task Result (Poll)

Use the task_id from submit to poll progress (repeat until terminal). The response includes status and result: result is [] while processing; on SUCCEEDED, result holds resources and costUSD is included; FAILED means the task failed.

POST/v1/task/result

curl --fail-with-body --connect-timeout 10 --max-time 60 \
  -X POST "https://api.icreat.ai/v1/task/result" \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{"task_id": "task-xxx"}'

Input Schema

Submit Task — Input

Total: 2 Required: 2 Optional: 0

inputobject[]required

An array of multimodal input content containing the text and reference image used to control video generation.

response_formatobjectrequired

An object that configures the output video specifications.

Query Task Result — Input

Total: 1 Required: 1 Optional: 0

task_idstringrequired

The task ID returned from the submit endpoint.

Output Schema

Submit Task — Output

Total: 1

task_idstring

Async task identifier.

Query Task Result — Output

Total: variable

statusstring

Current task status. result is usually [] until success; on SUCCEEDED, result holds resources and costUSD is present.

SUBMITTEDSUCCEEDEDFAILED

resultarray[object]

Generated resources. Empty array while processing or on failure; array of objects on success.

costUSDnumber

Task cost in USD. Present only when status is SUCCEEDED.

LLM Prompt

The Markdown below is an LLM-friendly prompt you can paste into AI assistants (e.g. Cursor, ChatGPT) to help them understand this model's API, call flow, and key parameters. Use Copy for AI or copy from the code block below.

# atlas/gemini-omni-flash/text-to-video

> Gemini Omni Flash Text-to-Video is Google DeepMind's flagship unified multimodal model under the Gemini Omni series.

## Overview

Use the iCreat two-step async task API: submit a generation request, then poll the query task result endpoint; on success read resources from `result` (includes `costUSD`).

## API Info

- **Base URL**：`https://api.icreat.ai`
- **Submit endpoint (POST)**：`/v1/task/submit/atlas/gemini-omni-flash/text-to-video`
- **Query result endpoint (POST)**：`/v1/task/result`
- **Model ID**：`atlas/gemini-omni-flash/text-to-video`
- **Auth**：`Authorization: Bearer ${ICREAT_API_KEY}`

## Call Flow

1. **Submit**: POST submit path with body per Input Notes; response `{ "task_id": "..." }`
2. **Query result**: POST `/v1/task/result` with `{ "task_id": "..." }`; response includes `status` and `result` (`[]` while processing); on `SUCCEEDED`, `result` holds resources and `costUSD` is present; read `url` or `download_url` when `type` is `Video`

### Input Notes

- Request body uses top-level flat fields
- Required: `input`, `response_format`
- `input` (required): An array of multimodal input content containing the text and reference image used to control video generation.
- `response_format` (required): An object that configures the output video specifications.

### Output Notes

- Poll: read `status`; `result` is `[]` while processing
- Success: `result` is `[{ "type": "Video", "url": "...", "download_url": "..." }]` plus `costUSD`

## Notes

- Use the same `task_id` across both steps; `result` is `[]` while processing — keep polling
- `FAILED` is terminal — check request parameters or reference media