Google introduced Gemini Omni at I/O 2026 as a new multimodal AI that can generate high‑quality video from text, images, audio, and video inputs, starting with the first model in the family—Gemini Omni Flash—rolling o... Unlike the earlier Veo video model, Gemini Omni unifies video generation with Gemini’s reasoning...

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Google I/O 2026 introduced Gemini Omni, a new generation of multimodal AI designed to generate and edit media from multiple input types. The model combines Gemini’s reasoning capabilities with generative media systems to produce video from mixed inputs such as text, images, audio, and existing video. The first version—Gemini Omni Flash—began rolling out the same day across Google’s AI ecosystem.
Below is a clear breakdown of what Gemini Omni is, how it differs from Google’s earlier video model Veo, what Omni Flash can do, where it’s available, and how Google is expanding its SynthID detection system alongside it.
Gemini Omni is a multimodal generative model family designed to create media from nearly any combination of inputs. Google describes it as a system where Gemini’s reasoning meets generative creativity.
At launch, the model focuses on video generation:
Google says the model aims to improve realism in areas such as motion, physics, and object interactions, helping generated video look more coherent and believable.
While the first release focuses on video outputs, Google has indicated that future versions of Omni will expand to generate other modalities like images and text directly from multimodal inputs.
Before Omni, Google’s primary generative video system was Veo, a model dedicated to video creation.
The key difference is architectural scope.
Veo
Gemini Omni
In practice, this means Omni is designed as a single foundation model that merges capabilities previously spread across different tools, including Veo and other media models.
The goal is a system that understands context across modalities—allowing users to mix prompts like dialogue, reference footage, and images when generating or editing video.
Gemini Omni Flash is the first production model in the Omni family.
It supports multimodal inputs in one prompt, including:
From those inputs, the system generates realistic video outputs and supports conversational editing of the results.
Example workflows demonstrated by Google include:
The model is designed to understand how objects move and interact, which helps produce more physically consistent video simulations compared with earlier generation models.
Google began rolling out Gemini Omni Flash on May 19, 2026, the day of the I/O keynote.
Initial availability includes:
In the Gemini ecosystem, access is tied to Google’s AI subscription tiers.
Supported tiers include:
Omni features are included in Gemini experiences under these plans, with higher tiers offering larger usage limits and advanced capabilities.
Google also introduced a $100 per month AI Ultra plan at I/O 2026 aimed at developers and advanced creators who need higher compute limits in the Gemini ecosystem.
Alongside new generative tools, Google emphasized content transparency safeguards built around its SynthID system.
SynthID is an invisible watermarking technology that embeds identifiable signals in AI‑generated content, including:
These watermarks are designed to be imperceptible to humans but detectable by software, enabling verification tools to identify AI‑generated media.
At I/O 2026, Google expanded SynthID in several ways:
New verification capabilities are being integrated into Google Search and the Chrome browser, allowing users to identify whether images online were generated or edited using AI.
Google also announced that several companies are adopting SynthID watermarking in their own AI systems, including:
The goal is to create a broader industry standard for identifying AI‑generated media across the web.
Google’s SynthID Detector portal allows users to upload media and check for embedded watermarks across multiple formats, helping journalists and researchers verify content provenance.
Gemini Omni signals a shift in how AI media models are built.
Instead of separate tools for text, images, and video, Google is moving toward unified multimodal systems that can interpret and generate across formats in a single workflow.
The first step is video generation from mixed inputs, but the broader goal is a model capable of creating any output modality from any input—a direction Google executives describe as a major advance in AI world modeling and media generation.
At the same time, the company is pairing those capabilities with watermarking and detection systems like SynthID to address concerns about AI‑generated media and deepfakes.
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Google introduced Gemini Omni at I/O 2026 as a new multimodal AI that can generate high‑quality video from text, images, audio, and video inputs, starting with the first model in the family—Gemini Omni Flash—rolling o...
Google introduced Gemini Omni at I/O 2026 as a new multimodal AI that can generate high‑quality video from text, images, audio, and video inputs, starting with the first model in the family—Gemini Omni Flash—rolling o... Unlike the earlier Veo video model, Gemini Omni unifies video generation with Gemini’s reasoning and multimodal inputs in a single foundation model designed to create and edit media conversationally.[20][23]
Google is pairing the launch with broader transparency tools: SynthID watermarking in AI outputs and new detection features in products like Search and Chrome, with partners including OpenAI, Kakao, ElevenLabs, and Nv...