Google strikes back! Gemini Omni, AI glasses, new models
Understanding Google's latest multimodal video and agentic releases helps filmmakers evaluate new pipeline integration options against established industry standards.
What this lesson covers
Google announced major AI updates at its annual event, introducing multimodal video generation models and advanced agentic tools. The presentation highlighted new capabilities for complex workflows, though early testing suggests some models lag behind competitors in specific generative tasks.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 0:30 ↗
Gemini Omni is Google's new multimodal video generation model capable of taking text, image, video, and audio inputs.
- 1:33 ↗
The model supports background replacement, object removal, and camera angle adjustments while maintaining consistency.
- 3:44 ↗
Gemini 3.5 Flash is designed for agentic use, optimizing speed and scale for complex multi-step workflows.
Workflow outlined in the video
- Review Google AI Studio to test the availability and performance of Gemini 3.5 Flash.
- Experiment with multimodal inputs in Gemini Omni to evaluate asset consistency and generation quality.
- Compare Google's new video generation capabilities against existing tools like Kling and Seedance.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
How to interpret the numbers
72,491 views captured 23 October 2026. ReelStack recommendation score: 28/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 0.63× views vs 9 other channel videos observed at a similar age. View-evidence factor 99% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 1 views/day vs 10 channel baseline (4 comparable uploads), with the same view-evidence factor
- 10% engagement: 92/100; likes + 4× comments, smoothed with a 500-view neutral prior