New #1 open source AI model is here! Kimi K3
Connecting agentic models like Kimi K3 directly to 3D suites via MCP opens up automated scene assembly and script-driven pre-visualization.
What this lesson covers
This video reviews Moonshot AI's open-source Kimi K3 model, demonstrating its advanced multi-step agentic capabilities. The creator showcases using Kimi Code integrated with a Blender MCP server to programmatically build, light, and animate a complex V8 engine inside Blender.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 01:31 ↗
Kimi Code operates inside VS Code as an agentic harness capable of managing multi-file local project directories.
- 03:06 ↗
Kimi K3 executes self-verification by running browser tests and capturing screenshots to troubleshoot code iteratively.
- 05:38 ↗
Kimi K3 can control Blender via a local MCP server to programmatically assemble, texture, and animate complex multi-part 3D models.
Workflow outlined in the video
- Install the Kimi Code extension in VS Code to configure an agentic harness.
- Enable a local Blender MCP server to expose 3D control functions to AI coding agents.
- Prompt Kimi K3 with multi-component scene specifications to automate complex 3D asset generation.
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.
Put the lesson in context
When to use Blender previsualization for AI video →How to interpret the numbers
332,889 views captured 23 October 2026. ReelStack recommendation score: 56/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
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