This is now the #1 open-source AI
Evaluating the capabilities of open-source reasoning models helps AI filmmakers understand emerging alternatives to proprietary frontier systems for local workflows.
What this lesson covers
This video provides a detailed review and walkthrough of the Kimi K2 Thinking open-source model. It tests the model's coding capabilities by generating interactive web tools and simulations directly from single 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.
- 00:00 ↗
Kimi K2 Thinking is introduced as a major open-source model competitive with top closed-source alternatives.
- 01:54 ↗
A single prompt successfully generates a complete drag-and-drop UI builder in an HTML file.
- 05:28 ↗
The model can create fluid dynamics simulations with interactive sliders and multiple color dyes.
- 36:28 ↗
Kimi K2 Thinking features lower token overhead for reasoning compared to other deep-thinking models.
Workflow outlined in the video
- Test Kimi K2 Thinking on kim.com for complex prompt-based code generation.
- Enable thinking mode in the interface for tasks requiring multi-step logical planning.
- Export generated HTML single-file apps to test functionality locally.
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.
Explore the tools
How to interpret the numbers
91,763 views captured 23 October 2026. ReelStack recommendation score: 30/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 0.78× views vs 11 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 16 channel baseline (6 comparable uploads), with the same view-evidence factor
- 10% engagement: 89/100; likes + 4× comments, smoothed with a 500-view neutral prior