GEMINI OMNI NEW AI VIDEO MODEL | COMPLETE TUTORIAL
Shows how conversational AI can replace complex prompt engineering, giving filmmakers a faster, more iterative workflow.
What this lesson covers
Gemini Omni is Google’s new AI video model that lets creators edit and generate footage through simple conversation and multimodal references. The tutorial demonstrates physics tests, visual edits, audio generation, and a side‑by‑side comparison with Seedance.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:20 ↗
Gemini Omni enables conversational editing without complex prompts.
- 01:15 ↗
Physics simulation is tested with a marble obstacle course, showing mixed results.
- 03:04 ↗
Simple text prompts can dramatically alter character appearance while preserving scene consistency.
- 04:20 ↗
The model keeps camera motion and focus consistent when swapping objects.
- 06:12 ↗
Educational videos are auto‑narrated; you must explicitly disable narration if undesired.
Workflow outlined in the video
- Open FlashBoards and select Gemini Omni as the generation model.
- Upload up to seven reference images and optionally a reference audio voice.
- Describe the desired edit in natural language; let the model generate the new clip.
- Review the output for visual and audio consistency; use a follow‑up prompt to refine.
- If needed, compare the result with another model (e.g., Seedance) to choose the best quality.
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
29,156 views captured 24 October 2026. ReelStack recommendation score: 50/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 2.53× views vs 5 other channel videos observed at a similar age. View-evidence factor 97% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 16 views/day vs 9 channel baseline (3 comparable uploads), with the same view-evidence factor
- 10% engagement: 62/100; likes + 4× comments, smoothed with a 500-view neutral prior