# Gemini Omni 1.2 Flash Video Edit — Atlas Cloud API > A natively multimodal Google DeepMind model that applies a plain-language edit to an existing clip of up to 15 seconds, such as swapping a product or background, changing the lighting, or restyling the look, while preserving the performance, camera motion, and everything the prompt does not mention. This is the machine-readable API reference for **Gemini Omni 1.2 Flash Video Edit** on Atlas Cloud, a unified API platform for 400+ AI models across text, image, video, audio and 3D. - **Model ID**: `google/gemini-omni-1.2-flash/video-edit` - **Built by**: Google - **Modality**: Video - **Model page**: https://www.atlascloud.ai/models/google/gemini-omni-1.2-flash/video-edit - **API key**: https://www.atlascloud.ai/console/api-keys - **Docs**: https://www.atlascloud.ai/docs ## Pricing on Atlas Cloud - $0.025 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-1.2-flash/video-edit"`. 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-1.2-flash/video-edit -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-1.2-flash/video-edit` ## 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-1.2-flash/video-edit"` - **`prompt`** (`string`, _required_): Text prompt describing the edit to apply to the source video (e.g., swap a product or background, change the lighting, weather, or camera angle). Simple, direct instructions work best; add "Keep everything else the same." to preserve the rest of the scene. Maximum 20,000 characters. - **`video`** (`string`, _required_): The source video to edit. Must be a publicly accessible URL, 3 to 15 seconds long. The edited video has the same duration as the source video. Supported format: MP4. - **`reference_images`** (`array[string]`, _optional_): Images to use as character, product, or style references for the edit. Accepts 1 to 10 images. Supported formats: PNG, JPEG, JPG, WebP. Each image is limited to 20MB. Supports both a public URL and a base64-encoded image for each item. - Min items: 1 - Max items: 10 - **`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" - **`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-1.2-flash/video-edit", "prompt": "", "video": "" } ``` **Full Example**: ```json { "model": "google/gemini-omni-1.2-flash/video-edit", "prompt": "", "video": "", "reference_images": [ "" ], "thinking_level": "default", "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-1.2-flash/video-edit", "prompt": "", "video": "", "reference_images": [ "" ], "thinking_level": "default", "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-1.2-flash/video-edit) ## About this model _Vendor-supplied description. Any pricing or endpoint mentioned below refers to_ _other platforms — use the Atlas Cloud values above._ ### Gemini Omni 1.2 Flash — Video Edit **Model ID:** `google/gemini-omni-1.2-flash/video-edit` Gemini Omni 1.2 Flash is Google DeepMind's natively multimodal model for video generation and editing. This variant takes **an existing video plus a plain-language instruction** and changes only what you ask for. It can swap a product or background, change the lighting, weather, or camera angle, or restyle the whole look, while keeping the performance, the camera motion, and everything else intact. In 1.2, edits work on full **15-second** clips. #### Overview Gemini Omni 1.2 Flash is Google DeepMind's next step toward models that can create and edit anything from any input, starting with video. It generates, edits, extends, and upscales clips **with synchronized audio up to 15 seconds long** at 360p, 720p, 1080p, or 4K, in landscape (16:9) or portrait (9:16). It follows both simple and complex instructions, simulates real-world physics, and lets you refine footage through plain-language edits, one turn at a time. Gemini Omni Flash is a single transformer that processes text, images, audio, and video together. It does not stitch separate per-modality pipelines together, so its output is more cohesive, more consistent across turns, and more controllable than a generate-then-dub workflow. **Audio is generated natively with every video**: dialogue, ambience, music, and sound effects are produced together with the picture, not added afterward. The model uses Gemini's real-world knowledge to reason about physics, narrative logic, and visual composition. Every output carries an imperceptible SynthID watermark, and Content Credentials (C2PA) are supported for provenance verification. ##### What's new in 1.2 Version 1.2 improves on Omni 1.1 Flash in length, consistency, and cost: _(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-1.2-flash/video-edit · Docs: https://www.atlascloud.ai/docs