Gemini Omni is Google’s released multimodal creation model built to create from different kinds of input, starting with video. Gemini Omni Flash is the first model in the Omni family, supporting practical video generation and editing workflows such as natural language edits, reference-based creation, scene transformation, and coherent visual storytelling.
Describe the image you want to generate.
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Supported formats: JPEG, PNG, WEBP, JPG Maximum file size: 10MB; Maximum files: 7
Reference images. Available image slots: 7/7. Video uses 2 slots and each character_id uses 1 slot.
Audio ID list. Up to 1 ID is allowed.
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Optional video input. Only 1 video is allowed and it uses 2 image slots.
Character ID list. Each character ID uses 1 image slot. Available character slots: 3/7. Remaining image slots: 7/7.
Note: when video input is provided, the output duration is determined by the model automatically. This duration parameter will not take effect.
Video ratio
Output video resolution. Valid values: 720P(default), 1080P, 4k.
Random seed. Range: [0, 2147483647]. If not specified, the system generates a seed automatically. Fixing the seed can improve reproducibility, but results may still vary due to the model’s stochasticity.
Explore different use cases and parameter configurations
Input description
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Supported formats: JPEG, PNG, WEBP Maximum file size: 20MB; Maximum files: 1
Upload an image file to use as input for the API
Audio ID list. Up to 1 IDs are allowed.
Character Description
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Basic Voice
Input description
Textarea description
Input description
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Build video generation and editing products with Gemini Omni API on Kie.ai. Turn text, image, video, and voice input into coherent video results with natural language control, reference guidance, and cost-effective API access.
In the context of Google I/O 2026, Gemini Omni represents a new step in multimodal AI creation. It is designed to create from different kinds of input, starting with video, and brings Gemini’s reasoning ability together with generative media systems. This allows the model to understand scenes, actions, environments, physical behavior, and real-world context more deeply, so video generation and editing can move beyond simple prompt-to-video output. Gemini Omni Flash is the first model in the Omni family, built for practical video creation and editing workflows where users can transform footage, guide results with references, and refine scenes through natural language.
Text input lets users describe the video they want to create or edit using natural language. A prompt can define the scene, subject, action, camera movement, style, lighting, or specific transformation, making Gemini Omni Flash useful for text-to-video generation and conversational video refinement.
Image input can guide the generated video with a subject, character, object, scene, sketch, or visual style. Gemini Omni Flash can use image references to preserve key visual details, apply a chosen look, or turn a static idea into a moving video sequence.
Video input allows an existing clip to become the starting point for a new result. Gemini Omni Flash can transform the environment, change what happens in the scene, add objects, adjust camera perspective, or apply new effects while keeping the video coherent.
Voice input supports speech-driven and avatar-style video workflows where vocal delivery can guide the final result. This makes it useful for presenter videos, character dialogue, narrated scenes, and generated clips where voice, expression, and on-screen action need to feel connected.
Gemini Omni API supports natural language video editing, allowing users to refine a scene step by step instead of rebuilding the full prompt each time. A user can change the environment, adjust the action, replace objects, shift the camera angle, or add visual effects while keeping the original scene coherent. This makes it useful for AI video editors, creator tools, and applications where users need a more intuitive way to transform existing footage.
With Google Gemini Omni API, generated videos can better reflect how scenes, objects, and actions should behave in context. The model is designed to connect visual creation with knowledge of physics, history, biology, culture, and narrative logic, helping outputs feel less random and more intentional. This matters for explainers, cinematic storytelling, product concepts, and any video experience where the result needs to make sense beyond visual style.
Gemini Omni Flash API turns mixed creative inputs into a more controllable video creation process. Text can define the direction, images can guide subjects or style, video can provide motion and scene context, and voice input can support speech-driven content. This helps users begin from real creative materials instead of relying only on a blank text prompt.
Gemini Omni Model API can support digital avatar video scenarios where character presence, expression, and delivery need to feel connected within the scene. Instead of treating an avatar as a flat visual layer, the final video can bring the subject, environment, and performance into a more integrated result. This direction is especially relevant for presenter clips, character-led content, interactive media, and future-facing creative video products.
Gemini Omni can support video products where users do not begin from a blank prompt alone. A real workflow may start with a source clip, a product asset, a visual reference, a storyboard, or a compact educational idea. For developers, Gemini Omni API makes these inputs easier to turn into editable, coherent, and context-aware video experiences.
An AI video editor can use Gemini Omni API to let users transform existing footage through plain language. A creator might upload a simple room video and ask for a futuristic studio, a street clip and ask for a rainy cinematic look, or a product shot and ask for a more dramatic launch scene. The value is not just generating a new clip, but giving users a way to revise real footage without manually adjusting timelines, masks, layers, or frame-by-frame effects.
Learning platforms can use Google Gemini Omni API to turn abstract ideas into short visual lessons. A science app could generate a claymation protein-folding explainer, a training product could visualize a complex workflow, or an education tool could compare classical computing and quantum computing through animated scenes. This use case depends on more than attractive visuals: the video needs to connect objects, actions, and context in a way that helps the viewer understand the topic.
Marketing and creator tools can use Gemini Omni Flash API to turn existing assets into fast video concepts. A product image can become a lifestyle teaser, a brand visual can guide the style of a social ad, or a short reference clip can shape the motion of a campaign video. This is especially useful for e-commerce teams, creative agencies, and social media tools that need quick variations before committing to a full production workflow.
A storyboard-to-video product can use Gemini Omni Video API to help users define the structure before generating the final clip. A creator may upload a rough storyboard, describe camera movement, keep a character or object consistent across shots, and apply a specific style to the full sequence. This use case fits concept design, previsualization, narrative shorts, and creative planning tools where the output needs to follow a planned visual arc rather than a single isolated prompt.
Gemini Omni API can help users create stronger video results when each request gives clear creative direction. A good prompt should define the scene, action, camera behavior, visual style, lighting, references, and consistency requirements instead of relying on a short subject description alone. For editing workflows, Gemini Omni Flash API also works better when users refine the result step by step, changing one part of the video while preserving the elements that already work.
Before adding advanced edits or effects, users should define the basic elements that shape the final video: shot framing, camera movement, style, lighting, location, and action. These details help Gemini Omni API understand how the video should look, move, and feel from the beginning. A stronger request does not only say what appears in the scene; it also explains how the scene should be filmed, what mood it should create, and what should happen over time.
For editing an existing clip, users should describe the exact change they want instead of rewriting the entire prompt. Gemini Omni Flash API can be guided through focused follow-up instructions, such as changing the background, replacing an object, adjusting the camera angle, modifying the action, or adding a new effect while keeping the rest of the video stable.
Camera language helps control how viewers experience the scene. When using Gemini Omni API, users can describe shot size, perspective, movement, and pacing, such as close-up, wide shot, over-the-shoulder view, locked-off camera, handheld motion, push-in, tilt-up, dolly zoom, or one continuous shot. Clear camera direction gives the final video a more intentional visual structure.
For educational, scientific, historical, or conceptual videos, users should state the idea clearly and define the desired visual format. Gemini Omni Flash API prompts can describe what needs to be explained, how the concept should unfold, and what kind of visual style should present it. This helps the final video connect objects, actions, and context in a more understandable way.
When a video includes captions, labels, animated words, signs, or lower thirds, users should explain how the text should appear and how it should connect with the action. Gemini Omni API prompts can include placement, timing, sequence, exposure, animation style, and whether the text should sync with movement, rhythm, or speech. This is especially useful for explainers, social clips, product demos, and visual storytelling.
For advanced motion or transformation scenes, users should focus on the action and its visible result. Gemini Omni Flash API prompts should explain what triggers the change, how the environment responds, and what the final state should become. This works well for physical reactions, object transformations, material changes, motion effects, and scenes where one action should clearly cause another.
For videos with multiple beats, users should describe the sequence and preserve important details across the result. Gemini Omni API prompts can include storyboard order, character consistency, clothing details, product design, object materials, environment layout, or visual style. This is useful for narrative clips, product stories, educational sequences, and planned creative videos.
Kie.ai offers affordable Gemini Omni API Pricing for teams that need to test, build, and scale video generation features with better cost control. Developers can start from early experimentation, estimate usage more clearly, and expand API calls as product demand grows without making the initial build phase unnecessarily expensive.
Kie.ai offers complete Gemini Omni API documentation to help developers understand API key setup, authentication, request parameters, supported inputs, response handling, task status, and deployment logic. Clear documentation makes Kie.ai a more efficient platform for connecting Gemini Omni API to apps, backend services, video editors, and creative automation tools.
Kie.ai offers 24/7 Gemini Omni API support for developers using the API in real projects. Whether teams need help with API keys, playground testing, request errors, integration logic, or production deployment, always-available support helps reduce delays and keeps development moving more smoothly.