Kimi K3 vs. MiniMax M3.1 Flash | WebGPU & 3D Koi Pond Simulation One technical challenge. Two AI models. Different approaches to interactive 3D development. Testing both models on a WebGPU-powered 3D koi pond, featuring realistic water ripples, swimming koi fish, dynamic reflections, and real-time rendering. MiniMax M3.1 Flash... stands out for its speed, coding capabilities, and potential to accelerate creative development workflows. The real benchmark? Turning complex ideas into functional, interactive experiences. #M31Flash #WebGPU #AIshow more

Great technical comparison and creative benchmark

Interactive 3D demos are a great way to benchmark coding models

Curious which model needed fewer iterations to get it working

Can both models maintain smooth performance with multiple animated fish?

Real-time rendering adds a whole new layer of complexity

curious. just use the prompt and not provided any 3d assets?

Those water reflections are where things get interesting 👀

WebGPU 3D koi pond with realistic ripples looks absolutely mesmerizing

Soft-body physics is a much more interesting test than a static 3D model

WebGPU is a great test of how far AI coding has come.

Great benchmark comparison interactive 3D rendering impressive technical demonstration work

Great benchmark M3.1 Flash looks impressively fast for 3D work

The water ripples and fish movements make this a great test.

MiniMax looks promising for rapid prototyping 🔥

Sounds like a fun experiment! It's always interesting to see how different AI models handle creative tasks like that.

This is a much more meaningful test than a simple coding prompt

The koi pond test is such a creative benchmark choice

Turning complex WebGPU ideas into a live interactive koi pond incredible demo of creative coding speed!

A koi pond is a sneaky good test, water ripples and fish motion expose sloppy shader code fast. Did either model get the WebGPU setup right first try?

Great benchmark showing AI models powering richer interactive experiences

Super interesting approach, how are you handling edge cases when scaling concurrent workloads?

Could you share the prompt and a runnable link for each version? I'd compare frame time on the same device and how many manual fixes each needed.

The difference in execution speed would be interesting to compare

Great benchmark. Real-world interactive builds reveal far more about a model’s coding abilities than scores alone.

A beautiful demo is one thing. Clean, maintainable code is another

Would love to see how both models handle WebGPU fallbacks

Speed matters, but working output matters more