Gemini Omni: Google’s Multimodal AI Video Model From I/O 2026

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.

How Gemini Omni Differs From Veo

Before Omni, Google’s primary generative video system was Veo, a model dedicated to video creation.

The key difference is architectural scope.

Veo

• Specialized generative video model
• Part of a separate media‑generation stack

Gemini Omni

• Unified multimodal model
• Accepts text, image, audio, and video inputs simultaneously
• Integrates Gemini reasoning with generative media systems

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.

What Gemini Omni Flash Can Do

Gemini Omni Flash is the first production model in the Omni family.

It supports multimodal inputs in one prompt, including:

• Text
  n- Images
• Audio
• Video

From those inputs, the system generates realistic video outputs and supports conversational editing of the results.

Example workflows demonstrated by Google include:

• Creating video scenes from text and reference images
• Editing uploaded video footage through natural‑language instructions
• Combining voice instructions with visual assets to modify scenes

The model is designed to understand how objects move and interact, which helps produce more physically consistent video simulations compared with earlier generation models.

Where Gemini Omni Flash Is Available

Google began rolling out Gemini Omni Flash on May 19, 2026, the day of the I/O keynote.

Initial availability includes:

• Gemini app
• Google Flow (AI creative studio)
• YouTube Shorts and YouTube Create for creators

In the Gemini ecosystem, access is tied to Google’s AI subscription tiers.

Supported tiers include:

• Google AI Plus
• Google AI Pro
• Google AI Ultra

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.

SynthID: Watermarking and AI Content Detection

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:

• Images
• Video
• Audio
• Text

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:

1. Detection inside Google products

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.

2. Cross‑industry adoption

Google also announced that several companies are adopting SynthID watermarking in their own AI systems, including:

• OpenAI
• Kakao
• ElevenLabs
• Nvidia

The goal is to create a broader industry standard for identifying AI‑generated media across the web.

3. Verification tools

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.

Why Gemini Omni Matters

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.