# Gemini Omni Flash Text-to-Video — Atlas Cloud API > A natively multimodal Google DeepMind model that generates cinematic videos with synchronized native audio from a text prompt alone, grounded in real-world physics for controllable, high-speed video generation. This is the machine-readable API reference for **Gemini Omni Flash Text-to-Video** on Atlas Cloud, a unified API platform for 400+ AI models across text, image, video, audio and 3D. - **Model ID**: `google/gemini-omni-flash/text-to-video` - **Built by**: Google - **Modality**: Video - **Model page**: https://www.atlascloud.ai/models/google/gemini-omni-flash/text-to-video - **API key**: https://www.atlascloud.ai/console/api-keys - **Docs**: https://www.atlascloud.ai/docs ## Pricing on Atlas Cloud - $0.125 per second of generated video - Pay-as-you-go. No minimum spend, no subscription required. > **These are the authoritative Atlas Cloud rates for this model.** Any price that > appears in the vendor description further down refers to a different platform or > a different model variant and does not apply here. ## Use this model from an AI agent Atlas Cloud ships three first-party integration surfaces. All three authenticate with the same API key via the `ATLASCLOUD_API_KEY` environment variable. ### MCP server The official MCP server (`atlascloud-mcp`) exposes this model to any MCP-compatible host — Claude Code, OpenAI Codex, Cursor, Gemini CLI, Goose, Claude Desktop. One-line install: ```bash # Claude Code claude mcp add atlascloud -- npx -y atlascloud-mcp # OpenAI Codex CLI codex mcp add atlascloud -- npx -y atlascloud-mcp # Gemini CLI gemini mcp add atlascloud -- npx -y atlascloud-mcp export ATLASCLOUD_API_KEY="your-api-key" ``` Then ask in plain English; the agent calls `atlas_generate_video` with `model: "google/gemini-omni-flash/text-to-video"`. The server fetches each model's schema and validates parameters before submitting, so invalid requests fail fast without spending credits. MCP docs: https://www.atlascloud.ai/docs/mcp-server ### Agent Skills `atlas-cloud-skills` is a portable skill package (API reference, code templates in Python / Node.js / cURL, model IDs with pricing) for Claude Code, Cursor, Codex and 12+ other agents: ```bash npx skills add AtlasCloudAI/atlas-cloud-skills export ATLASCLOUD_API_KEY="your-api-key" ``` Skills docs: https://www.atlascloud.ai/docs/skills ### CLI The `atlas` binary runs Atlas Cloud from a terminal or CI script. Async media jobs are polled and downloaded automatically (use `--no-download` when a script only needs the output URLs): ```bash # Install (Homebrew, npm, or shell installer) brew install AtlasCloudAI/tap/atlascloud # npm install -g atlascloud-cli # curl -fsSL https://raw.githubusercontent.com/AtlasCloudAI/cli/main/install.sh | sh atlas auth login atlas generate video google/gemini-omni-flash/text-to-video -p "Your prompt here" ``` CLI docs: https://www.atlascloud.ai/docs/cli ## HTTP API reference - **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id` - **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes - **Model ID**: `google/gemini-omni-flash/text-to-video` ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`model`** (`string`, _required_): model name - Default: `"google/gemini-omni-flash/text-to-video"` - **`prompt`** (`string`, _required_): Text prompt for generation. Describes the target content, style, camera language, or character actions. Maximum 20,000 characters. - **`duration`** (`integer`, _optional_): The duration of the generated video in seconds. - Default: `10` - Min: 3 - Max: 10 - **`aspect_ratio`** (`string`, _optional_): The aspect ratio of the generated video. - Default: `"16:9"` - Options: "16:9", "9:16" - **`thinking_level`** (`string`, _optional_): Controls the amount of internal reasoning the model performs before generating a response. Higher levels may improve quality on complex tasks but increase latency. - Default: `"default"` - Options: "default", "high", "low" - **`resolution`** (`string`, _optional_): The resolution of the generated video. - Default: `"720p"` - Options: "720p" - **`seed`** (`integer`, _optional_): The random seed to use for the generation. -1 means a random seed will be used. - Default: `-1` **Required Parameters Example**: ```json { "model": "google/gemini-omni-flash/text-to-video", "prompt": "" } ``` **Full Example**: ```json { "model": "google/gemini-omni-flash/text-to-video", "prompt": "", "duration": 10, "aspect_ratio": "16:9", "thinking_level": "default", "resolution": "720p", "seed": -1 } ``` ### Output Schema The API returns the following output format: - **`code`** (`integer`, _optional_): HTTP status code of the response. - **`message`** (`string`, _optional_): Human-readable message; non-empty on failure. - **`data`** (`object`, _optional_): - Properties: - **`id`** (`string`, _optional_): Unique identifier for the prediction. - **`model`** (`string`, _optional_): Model ID used for the prediction. - **`outputs`** (`array[string]`, _optional_): Array of URLs to the generated content. Null when status is not completed. - **`urls`** (`object`, _optional_): Object containing related API endpoints. - Properties: - **`get`** (`string`, _optional_): URL to poll for the prediction result. - **`status`** (`string`, _optional_): Status of the task: created, processing, completed, timeout, or failed. - **`created_at`** (`string`, _optional_): ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z"). - **`error`** (`string`, _optional_): Error message if the task failed, empty string otherwise. - **`error_code`** (`integer`, _optional_): Error code if the task failed. - **`executionTime`** (`number`, _optional_): Total execution time in milliseconds. - **`timings`** (`object`, _optional_): Detailed timing breakdown. - Properties: - **`inference`** (`number`, _optional_): Inference time in milliseconds. **Example Response**: ```json { "code": 0, "message": "", "data": { "id": "", "model": "", "outputs": [ "" ], "urls": { "get": "" }, "status": "", "created_at": "", "error": "", "error_code": 0, "executionTime": 0, "timings": { "inference": 0 } } } ``` ## Usage Examples ### cURL ```bash # Step 1: Start generation (async) curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \ -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "google/gemini-omni-flash/text-to-video", "prompt": "", "duration": 10, "aspect_ratio": "16:9", "thinking_level": "default", "resolution": "720p", "seed": -1 }' # Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}} # Step 2: Poll for result (replace {prediction_id} with the id returned above) curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \ -H "Authorization: Bearer $ATLASCLOUD_API_KEY" # Keep polling until status is "completed", "succeeded" or "failed" # When completed, outputs will contain the generated content URL(s) ``` ## Additional Resources ### Documentation - [Model Playground](https://www.atlascloud.ai/models/google/gemini-omni-flash/text-to-video) ## About this model _Vendor-supplied description. Any pricing or endpoint mentioned below refers to_ _other platforms — use the Atlas Cloud values above._ ### Gemini Omni Flash — Text to Video **Model ID:** `google/gemini-omni-flash/text-to-video` Gemini Omni Flash is Google DeepMind's high-performance, natively multimodal model built for high-speed video generation, editing, and cinematic control. This variant accepts a **text prompt only**, making it ideal for pure creative generation where you describe the entire scene through language. #### Overview Gemini Omni Flash (`gemini-omni-flash-preview`) was introduced by Google alongside Nano Banana 2 Lite as a new generation of multimodal media models. Unlike traditional pipelines that stitch modalities together, Omni Flash is a single transformer that processes text, images, audio, and video simultaneously, producing output that is more cohesive, consistent, and controllable. What sets it apart from earlier video models (such as the Veo family) is that it **natively generates audio with every video** — dialogue, ambience, music, and sound design are produced together with the picture rather than added afterward. The model is grounded in Gemini's real-world knowledge, so it reasons about physics, narrative logic, culture, and visual composition to produce results that feel intentional and cinematic. Generated media carries an invisible SynthID watermark. > AtlasCloud exposes Gemini Omni Flash through four endpoints — text-to-video, image-to-video, reference-to-video, and video-edit. All four route to the **same** `gemini-omni-flash-preview` model and differ only by the input modality they accept, corresponding to the model's `task` parameter (`text_to_video`, `image_to_video`, `reference_to_video`, `edit`). This endpoint maps to **`text_to_video`**. #### Inputs This variant takes a **text prompt** as its only content input. You describe the subjects, actions, camera language, lighting, mood, style, and any dialogue or sound design entirely in natural language, and the model synthesizes a video (with audio) from scratch. #### Key Capabilities _(Description truncated. Full text on the model page.)_ --- Atlas Cloud — one API for 400+ AI models. Model page: https://www.atlascloud.ai/models/google/gemini-omni-flash/text-to-video · Docs: https://www.atlascloud.ai/docs