Holllllyyyyyyyy @GeminiApp cooked 😳😳 🚨 Gemini Omni: New video model Here is the first output and see the text coherence , if this is not nano banana moment of video then what is ?? direct link for those who believes otherwise in comments
As a subsequent solution to Google's video generation technology, Gemini Omni expands input formats and output capabilities beyond Veo 3, supporting creation and editing through text, images, video clips, and audio. Generation duration and image quality have improved, targeting video needs in advertising, education, and content creation.
As a follow-up to Veo 3, Gemini Omni extends processing capabilities to video clips and audio materials while inheriting text and image prompt functionality. When parsing multimodal inputs, the model employs a unified feature extraction framework to ensure signals from different sources are coordinated during generation. Gemini Omni AI Mode Operational instances demonstrate that when users upload static images, the model shows enhanced ability to maintain frame composition, character design, and color relationships compared to previous generations.
Gemini Omni integrates multiple input signals into unified instructions, allowing users to complete full workflows from generation to editing within a single process.
The model simultaneously receives text, images, video clips, and audio as creative references, understanding them as interconnected instruction sets. Users describe concepts through text, establish style with images, suggest motion with video, and guide mood with audio. The model synthesizes these to generate video consistent with overall intent.
Users complete frame adjustments by describing modification needs in natural language without manual editing. For example, instructions such as "remove the logo from the frame" or "replace the food on the plates with creamy pumpkin soup, keep everything else unchanged" enable the model to execute local modifications while maintaining original camera movement and style.
Users can output new versions from existing video clips through text instructions without repeating creation from scratch. For example, combining seaside walking footage with product display, accompanied by style descriptions, generates fused footage with commercial advertising quality.
The model supports directional modification of specific objects or regions within a video without re-rendering the complete scene. Users can correct designated elements while maintaining original composition, motion, and visual tone.
Compared to Veo 3, Gemini Omni demonstrates improvements in input compatibility, generation specifications, frame stability, and control capabilities.
While Veo 3 primarily supports text and image prompts, Gemini Omni additionally supports video clips, audio, and templates as references. Users can combine multiple materials in a single task without splitting creative intent by format.
Veo 3 generates clips around 8 seconds, while Gemini Omni is expected to reach 15 to 30 seconds with smoother segment transitions. Output resolution has also improved, with richer image detail presentation.
The model shows improved ability to maintain character identity, scene details, and environmental elements compared to previous generations, with better persistence of dynamic objects and stability in multi-character scenes, providing better visual coherence for longer clips.
Users can exercise finer control over camera movement, framing, and pacing through text, and can achieve multi-angle switching within a single scene. Regarding audio generation, the model can output dialogue, ambient sound, and sound effects matched to visuals, with lip synchronization supported in specific scenarios.
This model applies to creative fields with dual demands for video output efficiency and image quality.
Suitable for advertising prototypes, storyboard pre-visualization, and commercial shorts. Creative teams can quickly generate visualized drafts through text, adjusting style and camera language across iterations to reduce early-stage shooting and setup costs.
Applicable to short-form video and series channel content production. The model supports maintaining character and style consistency across segments, helping establish recognizable content series, while generated audio can satisfy basic narrative needs.
Usable for product display, brand story, and other marketing videos. Through text descriptions, users can adjust product presentation, scene atmosphere, and visual tone, accelerating conversion from creative conception to final output.
Suitable for explanation and demonstration teaching content. The model's improved capability in maintaining blackboard text and formulas helps generate logically clear teaching footage, while multi-angle shots can display operational details step by step.
Read the latest user feedback and reviews of Gemini Omni AI Video Generator.
Holllllyyyyyyyy @GeminiApp cooked 😳😳 🚨 Gemini Omni: New video model Here is the first output and see the text coherence , if this is not nano banana moment of video then what is ?? direct link for those who believes otherwise in comments
Sample video and early feedback 👀 > I won’t lie, this is one of the best video models I have seen, maybe not *the* best, but a really strong performance. I was particularly impressed by the prompt adherence (except for the one shot with the missing centerpiece), the model
Google will showcase Omni at Google I/O 2026 (May 19–20). Excited to see how this next-generation multimodal model advances AI-driven video creation and editing workflows. video by AIDRIVING #geminiomni
GOOGLE 🔥: An upcoming Gemini Omni video model from Google is expected to be much more advanced in video editing, capable of completing tasks like removing watermarks, replacing objects in the video, and more. It is also likely that Google will release 2 versions of this model,
🫨Google is creating a new Omni model with good video editing. Veo4? The original is on the left. Edited right. The new model also does a good job of removing watermarks from videos.
