Can Google's New Omni 1.2 Video Model Beat Seedance 2.5?
Adrian breaks down the real-world performance differences between Google's Omni 1.2 Flash and Seedance 2.5, evaluating motion physics, audio fidelity, and generation pricing to help creators optimize video quality versus cost.
What this lesson covers
Adrian evaluates Google's Omni 1.2 Flash video generation model by comparing its output against Seedance 2.5 across photorealistic and animated test cases. The comparison examines motion physics, audio quality, pricing structures, and resolution capabilities.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:33 ↗
Omni 1.2 Flash API pricing runs around 10 cents per second, whereas Google Flow Studio offers lower generation costs around 1 cent per second.
- 00:44 ↗
Omni 1.2 Flash supports output resolutions up to 4K.
- 01:54 ↗
In side-by-side dialogue tests, Omni 1.2 offers slightly clearer spoken audio, while Seedance 2.5 provides more realistic environmental reverberation.
- 03:08 ↗
In action-heavy animation prompts, Omni 1.2 Flash exhibits physics artifacts, whereas Seedance 2.5 delivers cleaner motion and character consistency.
Workflow outlined in the video
- Generate source images using tools that avoid OpenAI blurriness before running image-to-video generation.
- Run identical image-to-video prompts across models at matching aspect ratios and resolutions to benchmark baseline movement.
- Compare dialogue clarity and room acoustic reverberation between generated videos to select the best audio output.
- Test high-action movement prompts to evaluate physics and motion artifact resistance in each model.
- Utilize Google Flow Studio rather than standard API pricing when generating high volumes of draft video on a budget.
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
17,310 views captured 9 November 2026. ReelStack recommendation score: 75/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 65% performance: 4.92× current views vs the channel's recent median; same-age history is not yet available. View-evidence factor 95% (views / (views + 1,000))
- 25% freshness: 85/100 with a 14-day half-life
- Momentum pending: collecting daily snapshots; its 20% weight goes to observed performance, not free points
- 10% engagement: 27/100; likes + 4× comments, smoothed with a 500-view neutral prior