omni-flash is the video creation entry point for Google Gemini Omni Flash, suitable for creating new shots starting from text concepts, still images, or existing videos. It can generate visuals from prompts and use reference materials to adjust scenes, styles, and elements. Through this platform, you can choose landscape or portrait aspect ratios and output resolutions, and integrate into asset production workflows through asynchronous tasks.
Clarify capacity, inputs and outputs, and invocation methods before selecting a model.
The above specifications are within this platform's omni-flash invocation scope; extended features of different native Gemini Omni versions must be distinguished separately.
Learn what omni-flash can bring to your work.
When starting from text, you can specify the subject, scene, action, camera movement, and lighting mood in the prompt to generate video footage for review. Compared with writing only a theme, this is better suited to fully expressing shooting intent: for example, the subject slowly turns around, the camera pushes forward, and the environment maintains soft backlighting, bringing creative discussions down to specific shots.
By guiding generation with reference images, you can continue creating dynamic footage from product photos, character images, or illustrations. Images provide the visual basis, while text describes the direction of movement, scene relationships, and desired style. This is suitable for production stages where design assets already exist but video shots have not yet been formed; clearly state whether the image serves as a subject reference or an overall visual reference.
Existing videos can also serve as a starting point for creation, generating new videos with reference images and editing instructions. You can request changes to the season, adjustments to the scene style, or additions and removals of visual elements, while specifying which compositional relationships should be retained. This workflow is suitable for creating creative variations around the same asset, rather than redescribing the entire scene each time.
Start with specific tasks to find where the model can make an impact.
Input selected product images, describe the product action, camera direction, and background atmosphere, and create showcase videos for the marketing team to review. Landscape format is suitable for pages or presentation visuals, while portrait format is suitable for vertical content layouts. After delivery, focus on checking whether the product outline, composition, and motion match the creative intent before deciding whether to proceed to formal editing.
Input an existing scene video and reference images, and use text to request changes to the weather, season, or visual style while listing the positional relationships that need to be retained. For example, turn a sunny beach into a winter scene while preserving the layout of the trees and boats. The output can be used to compare new versions across different creative directions, reducing the work of reimagining from a blank frame.
The application backend submits prompts, aspect ratios, and asset links, creates tasks with async, saves the task_id and then queries the result, or receives completion notifications through callback_url. After obtaining a successful status and video link, download and archive it, then pass it to the review or editing workflow. This is suitable for production applications that do not want to continuously maintain a generation request connection.
Choose based on task complexity, input materials, and expected results.
Choose text-to-video when you only have creative text; add image references when the subject's appearance or visual direction has already been determined; use a combination of video and images when you want to modify existing shots. The value of choosing omni-flash is that it brings these material formats into the same video workflow. For editing tasks especially, clearly state separately “what to change” and “what to preserve,” rather than submitting only vague style terms.
omni-flash is for video generation and editing and should not be confused with Gemini Flash text chat models. Gemini Omni 1.1 Flash also has a separate native version name, so do not apply first-and-last-frame or extension controls directly to this endpoint just because the names are similar. If your goal is guidance from existing materials and scene rewriting, choose the workflow here; if you depend on specific version features, select models by version.
From a small-scale task to formal integration.
Define the goal, required inputs, and output requirements, and use real business examples as a starting point.
Open the trial page, confirm the parameters supported by this endpoint, then submit a small-scale task to review the results.
Keep the complete model ID, use the request format specified in the documentation, and confirm billing rules on the Pricing page.
Before formal use, understand output quality and capability boundaries.
Answers to common questions about using omni-flash.
No. The omni-flash here is designed for video creation: submit text and optional assets through POST /gemini/videos to receive video results. It is not a Gemini Flash model that returns regular text answers through a conversational interface; during development, organize inputs, status queries, and result storage around video tasks.
Yes. You can submit an image link through image_urls and also provide the required prompt. We recommend clearly describing how the subject should move, how the camera should move, and which visual characteristics should be maintained. Images are used to guide generation; do not simply write “make it move,” or it will be difficult to convey the shot effect you actually need.
You need to submit a video link in video_urls, provide at least one reference image in image_urls, and use prompt to describe the desired modifications. You can make requests around style, scene, or visual elements, and should also specify the layout that needs to be preserved. Sending only a video without an image does not meet this workflow's input requirements.
Yes. aspect_ratio supports 16:9 and 9:16, and resolution supports 720p and 1080p, with defaults of 16:9 and 720p respectively. We recommend determining the delivery aspect ratio before creation, especially the subject position and camera movement direction, to avoid cropping after generation that causes the composition to deviate from the original intent.
After setting async to true, save the returned task_id and submit a query request to /gemini/tasks using that value as the id; you can also set callback_url to receive completion notifications. After the task succeeds, read the video_url in the result and download and save it. Continue waiting if it is still pending, and check the error information if it fails.
Model information · Updated: 2026-10-01. For request parameters and billing rules, see the API and pricing sections.
Start with a clear goal and judge from actual results whether it suits your work.
