Gemini Omni
Gemini Omni is Google's multimodal generative model family for creating from many input types, starting with video output through Gemini Omni Flash. Google describes it as combining Gemini reasoning with generative media systems so users can create and edit videos from text, image, video, and audio references.
Gemini Omni shifts Gemini media generation from separate prompt-to-media tools toward conversational, multi-input video creation. Readers need to distinguish the Gemini Omni family from the first available model, Gemini Omni Flash, and understand where it is available, what outputs are supported now, what API access is still pending, and how it differs from older video generation workflows.
Google DeepMind and the Google I/O 2026 keynote describe Gemini Omni as a model family that can create anything from any input, starting with video. The first model, Gemini Omni Flash, is rolling out to Gemini app, Google Flow, and YouTube Shorts or YouTube Create, with developer and enterprise API rollout planned in the coming weeks. Official pages say Omni can combine text, images, video, and audio inputs to produce high-quality video, supports multi-turn natural language edits, preserves scene consistency, uses Gemini world knowledge for physics and meaning, includes SynthID watermarking and Content Credentials, and will support more output modalities later. Reddit source strength was strongest around an r/GeminiAI post with score 316 asking whether Omni is a new video model or a Veo rebrand, plus an r/ArtificialInteligence post with score 130 focused on text coherence. Official Google DeepMind X engagement exceeded the project X gate by likes alone.
- Generate videos from text, image, video, and audio references.
- Edit videos through natural language across multiple turns while preserving scene continuity.
- Create videos with a personal avatar through the Gemini app flow.
- Evaluate Google media generation against Veo, Seedance, Runway, Sora, and other AI video models.
- Prepare for Gemini Omni API adoption once developer access is officially documented.
Gemini Omni is the family name. Gemini Omni Flash is the first model Google is rolling out. Google says the broader Omni direction is any input to any output, but the launch starts with video output. In time, Google says it will support additional output modalities such as image and audio.
- Use Gemini Omni when discussing the model family or capability direction.
- Use Gemini Omni Flash when discussing the first available launch model.
- Do not assume public developer API access is live until Google documents the API rollout; Google says APIs are coming in the following weeks.
Gemini Omni Flash can create and edit video from combinations of text, image, video, and audio references. Google highlights step-by-step conversational editing, scene consistency across turns, object or character swaps, style and motion transfer, video editing from reference images, and videos grounded in Gemini's world knowledge.
Google says Gemini Omni Flash is rolling out globally to Google AI Plus, Pro, and Ultra subscribers through the Gemini app and Google Flow. Google also says it is rolling out at no cost to users on YouTube Shorts and the YouTube Create app starting the launch week, with developer and enterprise API access planned in the coming weeks. Features can vary by subscription tier and geography.
Google says videos created or edited with Omni include SynthID digital watermarking and Content Credentials. The launch materials also distinguish avatars from broader audio or speech editing: users can create videos with their own voice and likeness through Avatars, while Google says broader audio and speech editing remains under responsible testing.
Community questions focus on whether Omni is a distinct model or a rebranded Veo experience, whether text rendering and math-on-board demos are meaningfully better than previous video models, and how Omni compares with other video models such as Seedance. These are comparison and evaluation signals, not replacements for Google's official availability, safety, or API claims.
- Reddit signal: r/GeminiAI post score 316 asked whether Gemini Omni is a new video model or a Veo rebrand.
- Reddit signal: r/ArtificialInteligence post score 130 focused on text coherence and viral early demos.
- X signal: Google DeepMind's official Omni post passed the project X inclusion gate by likes alone.
Source confidence
Google DeepMind
Google Blog
Google Blog
X / Google DeepMind
X / Gemini app
Reddit / r/GeminiAI
Reddit / r/ArtificialInteligence
Gemini Omni FAQ
Page-level questions for Gemini Omni.
What is Gemini Omni?+
Gemini Omni is Google's multimodal generative model family for creating from many input types, starting with video. The first launch model is Gemini Omni Flash, which Google says can create and edit video from text, images, video, and audio references.
Is Gemini Omni the same as Gemini Omni Flash?+
No. Gemini Omni is the family or capability direction, while Gemini Omni Flash is the first available model in that family. Google says the launch starts with video output and that more output modalities will come over time.
Where can I use Gemini Omni Flash?+
Google says Gemini Omni Flash is rolling out through the Gemini app and Google Flow for Google AI Plus, Pro, and Ultra subscribers, and through YouTube Shorts and the YouTube Create app at no cost starting launch week. Developer and enterprise APIs are planned for the coming weeks.
Does Gemini Omni support API access now?+
Google says developer and enterprise API access will roll out in the coming weeks. Until Google publishes stable API documentation, treat app and Flow access as confirmed and API details such as model IDs, pricing, limits, and endpoints as pending.
How is Gemini Omni different from Veo?+
Google presents Gemini Omni as a Gemini model family that combines Gemini reasoning with generative media systems and supports conversational, multi-input video creation. Community users are actively asking whether it is a new video model or a Veo rebrand, so the practical comparison should focus on current official surfaces, supported inputs, edit consistency, API availability, safety metadata, and output quality rather than assuming the two are identical.