Gemini Omni is Google's new multimodal creation model family, announced at Google I/O 2026 on May 19, 2026. The first model in the family is Gemini Omni Flash, and its first public focus is video: creating and editing videos from combinations of text, images, video, and audio inputs.
That makes Gemini Omni more than another text-to-video tool. Google is positioning it as a step toward "any input to any output" creation, where Gemini's reasoning is combined with generative media models. Today, the practical question is narrower: what can Gemini Omni Flash do for video creators, marketers, and teams who already use AI video tools?
If you want to test Gemini Omni prompts right now, use the dedicated . You can also start in or use the when you want a separate structured AI video workflow.
AI video generation and conversational video editing
Inputs
Text, images, video, and audio references
Current output focus
Video first
Future outputs
Google says image and audio outputs will come later
Consumer access
Gemini app and Google Flow for Google AI Plus, Pro, and Ultra subscribers
YouTube access
Rolling out at no cost in YouTube Shorts Remix and YouTube Create
API access
Google's official developer API is rolling out separately; C Dance AI supports Gemini Omni generation
Transparency
Omni videos include SynthID watermarking, with broader verification through Google products
The important nuance is that "any input, any output" is the long-term direction. At launch, Gemini Omni Flash is mainly a video creation and editing product.
Gemini Omni is a new Google model family built around multimodal creation. In plain English, it is designed to understand different kinds of inputs together - text, images, video, and audio - then generate a coherent media output from them.
Google's official announcement describes Omni as the place where Gemini's reasoning meets its ability to create. That matters because video generation is not only about pretty frames. A useful video model needs to understand:
what the user is asking for
what objects should stay consistent
what physical motion should look plausible
how a reference image, video, or audio track should influence the result
how one edit should build on the previous edit
That is why Gemini Omni is especially interesting for people who already work with AI video. It points toward a workflow where the model does not simply generate a clip once. It keeps the scene in context while you ask for revisions.
The headline feature is natural language video editing. Instead of generating a clip, finding a flaw, rewriting the full prompt, and starting again, you can ask Gemini Omni to make changes through conversation.
Examples include changing an object, adjusting the environment, modifying the action, shifting the camera angle, or refining the visual style across multiple turns.
This is a real workflow shift. Traditional video tools make you edit on a timeline. Early AI video tools make you regenerate. Gemini Omni is moving toward an instruction-based editing loop: "keep this scene, change that part."
Gemini Omni can use different types of inputs together. A creator might combine:
a product image
a short reference video
a music or voice reference
a text instruction
The goal is not to stitch files together manually. The goal is for the model to reason across the references and create one coherent output.
That is useful for product ads, creator clips, education videos, and social remixes where the final video must preserve a style, object, person, or motion reference.
Google emphasizes that Gemini Omni combines visual generation with Gemini's world knowledge. The promise is not just photorealism, but scenes that better understand what should happen next.
For AI video, this matters in small but visible ways:
gravity should feel grounded
fluids should move believably
objects should react in plausible ways
educational explainers should follow the idea being explained
text and visuals should stay connected to the action
No model will be perfect here, especially at launch. But this is the right direction for video workflows that need more than a surprising visual demo.
Google also connects Omni with avatar creation, including videos that can look and sound like the user after a consent-based setup. This is powerful for creators, but it also raises obvious safety and likeness questions.
For businesses, the safe version of this use case is controlled spokesperson content: internal training, product explainers, founder updates, and localized video drafts. Every final output still needs human review.
Google says Gemini Omni Flash is available to Google AI Plus, Pro, and Ultra subscribers globally through Gemini and Flow. YouTube is also rolling out Omni remixing at no cost in Shorts Remix and YouTube Create.
For developers and enterprise teams, Google's official API access is rolling out separately. C Dance AI now provides a Gemini Omni generator for practical video generation, while teams that require direct Google contracts, rate limits, and enterprise data terms should still wait for Google's official developer channel.
There is no single "Gemini Omni free generator" across every Google product. Gemini Omni Flash is tied to Google AI Plus, Pro, and Ultra inside Gemini and Flow, while YouTube says Omni remixing is rolling out at no cost in Shorts Remix and YouTube Create.
If your goal is to generate AI video today without waiting for Google's official Gemini Omni developer API, you can use the Gemini Omni Video Generator on C Dance AI or use Seedance 2.0 as a separate AI video workflow.
Gemini Omni's prompt guide emphasizes details like shot framing, camera motion, style, lighting, location, and action. That is the same pattern we see across practical AI video workflows: better prompts are not just longer, they are easier to stage.
Use this structure:
Subject: what appears on screen
Action: what changes over time
Input references: what image, video, or audio should guide the output
Camera: framing, angle, and movement
Lighting: where light comes from and how it feels
Style: realistic, cinematic, claymation, anime, product ad, documentary, etc.
Constraints: what should stay unchanged or what to avoid
Output goal: social ad, explainer, product demo, remix, or concept test
Here is a Gemini Omni-style prompt you can adapt:
Create a 10-second vertical product video from the uploaded product image.
Keep the product shape and logo stable.
Place it on a clean reflective studio surface with soft daylight from the left.
The camera starts in a close-up, then slowly pulls back to reveal water droplets and a premium lifestyle background.
Use calm cinematic motion, realistic reflections, and no extra objects.
Keep all text readable and avoid warped packaging.
If you are using C Dance AI today, the same structure works well for Seedance-style workflows. Start with Create, keep the subject narrow, then revise only one variable at a time.
Gemini Omni and Veo should not be treated as identical.
Comparison point
Gemini Omni
Veo
Core position
Multimodal creation and editing model family
Dedicated video generation model family
Interaction style
Conversational creation and iterative editing
Prompt-based video generation and cinematic control
Input direction
Text, images, video, and audio together
Text/image/video workflows depending on product integration
Best mental model
"Edit and create through Gemini context"
"Generate high-quality video clips"
Current launch signal
Starts with Gemini Omni Flash for video
Existing Google video model family
The easiest way to think about it:
Veo is Google's specialized video generation engine.
Gemini Omni is Google's broader multimodal creation direction, starting with video and conversational editing.
That distinction matters for anyone choosing a tool. If you are asking "Gemini Omni vs Veo," you probably want to know whether Omni replaces Veo. The safer answer is: not necessarily. Omni appears to combine Gemini intelligence with generative media capabilities, while Veo remains part of Google's dedicated video model story.
Gemini Omni is new and strategically important, but most creators still need to make videos today. That is where practical workflow tools matter.
Use case
Gemini Omni
Seedance 2.0 workflow
Early trend exploration
Very strong, because it is the new Google model family
Useful when you want to compare against existing AI video workflows
Prompt discipline
Still important, especially for conversational edits
Very important for stable first-pass output
Commercial drafts
Promising, especially for Google Flow and Shorts remix
Practical for product ads, social hooks, and controlled prompt tests
API readiness
Available on C Dance AI; Google's official developer API is separate
Depends on the platform you use
Best current role
Watch closely, test access if available
Use now for repeatable AI video production practice
C Dance AI now includes a Gemini Omni generator alongside its Seedance-style workflow, so readers can compare prompt behavior and pricing without treating every model as the same product.
Gemini Omni shows where AI video is going. C Dance AI helps you build the prompt workflow you can use now.
That gives you a clean conversion path without risky claims. A reader who came for Gemini Omni can try the Gemini Omni Video Generator, compare it with the Seedance 2.0 Video Generator, and learn the workflow they will need across future video models.
Gemini Omni also competes in a broader field that includes Sora, Seedance, Kling, Runway, Luma, and other AI video tools. The comparison should be based on workflow, not hype.
Creators should evaluate:
how well the model follows the prompt
how stable people, products, and objects remain
whether editing is targeted or requires full regeneration
how easy it is to use image, video, or audio references
cost per usable output, not just cost per generation
whether the output can be reviewed and approved for commercial use
Gemini Omni's biggest promise is not only quality. It is the possibility of collapsing several steps - ideation, reference use, generation, editing, remixing - into one conversational workflow.
Because Gemini Omni is new, teams should avoid overbuilding plans around assumptions.
The biggest open questions are:
API pricing and rate limits
maximum video length by tier
how consistent outputs are outside official demos
whether Pro or higher-quality Omni models will arrive
how strict content policies will be in different use cases
what data and enterprise controls will apply through APIs
how well Omni handles exact text, logos, faces, and product details
There is also a common AI video risk: over-editing. If a prompt is too vague, the model may change parts of the scene the user intended to keep. The fix is to write edits like a creative director:
Keep the person, room, camera angle, and lighting unchanged.
Only replace the object in the person's hand with a matte black smartphone.
Preserve the original motion and timing.
That kind of precision will matter in Gemini Omni, Seedance, Sora, and nearly every serious AI video workflow.
You should test Gemini Omni Flash if you already have access through Gemini, Google Flow, YouTube Shorts, or YouTube Create. It is especially worth testing for:
short-form social remixes
product concept videos
explainer drafts
reference-based edits
creator avatar experiments
fast campaign variations
You should wait for Google's official developer API if you need direct Google enterprise governance, direct contract terms, or platform-native rate-limit commitments.
For teams that need to keep moving now, use this moment to improve your AI video process. Build better prompt templates, define review rubrics, and compare outputs across tools. You can start with the Seedance 2.0 Video Generator, then use our Seedance 2.0 prompt examples to practice structured scene design.
This article is based on Google's official Gemini Omni announcement, Google DeepMind's Gemini Omni product page, the Google DeepMind prompt guide, and YouTube's I/O 2026 creator announcement:
Gemini Omni is important because it makes the future of AI video feel more conversational, multimodal, and iterative. Instead of asking a model to generate a clip once, creators will increasingly expect to build from references, revise through conversation, and preserve context across edits.
Gemini Omni Flash is the first step in that direction. It starts with video, with image and audio outputs planned later. C Dance AI now offers Gemini Omni generation inside C Dance AI, and real-world quality will become clearer as more people test it outside official demos.
For now, the best move is practical: learn the workflow, test the prompts, and build a repeatable review process. If you want to start creating AI video today, try the Gemini Omni Video Generator, open Create, or use the Seedance 2.0 Video Generator.
Gemini Omni is Google's new multimodal creation model family. The first model, Gemini Omni Flash, starts with AI video generation and conversational video editing from combinations of text, images, video, and audio inputs.
Gemini Omni Flash is the first model in the Gemini Omni family. It is the version Google is rolling out first through Gemini, Google Flow, and YouTube creation surfaces.
Gemini Omni Flash is rolling out through the Gemini app and Google Flow for Google AI Plus, Pro, and Ultra subscribers. It is also rolling out through YouTube Shorts Remix and YouTube Create starting this week.
Gemini Omni Flash is included for Google AI Plus, Pro, and Ultra subscribers through Gemini and Google Flow. YouTube says Omni remixing is rolling out at no cost in YouTube Shorts Remix and YouTube Create.
It is too early to make a universal quality claim. Veo is a dedicated Google video model family, while Gemini Omni is a broader multimodal creation model family that starts with video and conversational editing.
