I Made the Same Animation in Every AI Video Generator - FULL Comparison
Rigorous multi-model comparisons help AI filmmakers identify the strengths and weaknesses of different video generators without needing multiple disjointed subscriptions.
What this lesson covers
This video provides a head-to-head comparison of major text-to-video and image-to-video generators using a standardized workflow built in Weavy AI. It tests models like Google V3, Seedance, Kling, and MiniMax across complex space and action prompts.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:26 ↗
Weavy AI allows creators to build advanced visual workflows that link a single prompt or file across multiple video generation platforms simultaneously.
- 02:01 ↗
Google V3 demonstrates strong motion physics and object integration, such as maintaining floating physics and handling audio generation in space prompts.
- 04:48 ↗
MiniMax struggles with consistent text-to-video alien newspaper generation, often introducing glitchy visual artifacts.
- 07:54 ↗
Kling 2.1 handles complex action and object interaction well, such as drinking water realistically, though prompt adherence varies by complexity.
Workflow outlined in the video
- Access the comparative workflow template on Weavy AI via the creator's link to test prompts across multiple video models.
- Run text-to-video tests focusing on physics (like zero gravity) to evaluate spatial consistency across models.
- Test complex multi-step actions (such as punching, drinking water, and using a towel) to identify model breaking points.
- Evaluate generation pricing and output reliability across different platforms before committing to a single pipeline.
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
488,134 views captured 23 October 2026. ReelStack recommendation score: 53/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 4.79× views vs 5 other channel videos observed at a similar age. View-evidence factor 100% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 37 views/day vs 10 channel baseline (4 comparable uploads), with the same view-evidence factor
- 10% engagement: 2/100; likes + 4× comments, smoothed with a 500-view neutral prior