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Built a Complex Procedural 3D Scene with Three.js Powered by Hy4! I used Hy4 through WorkBuddy to turn a simple one-line prompt into a complex procedural 3D scene using Three.js. → Procedurally generated 3D environments → Detailed geometry and immersive visuals → Dynamic scene composition → AI-powered coding from...

93,361 views • 1 day ago •via X (Twitter)

21 Comments

H A J R A's profile picture
H A J R A1 day ago

That’s impressive

Mohit Mishra's profile picture
Mohit Mishra1 day ago

This is where AI coding gets really interesting. It's not just generating code anymore, it's helping build actual experiences.

Manish Kumar Shah's profile picture
Manish Kumar Shah1 day ago

Curious to see how far you can push this with more detailed prompts and complex environments.

Vaidehi's profile picture
Vaidehi1 day ago

I like how this lowers the barrier to experimenting with 3D development. You don't need to start with a blank scene anymore.

Markandey Sharma's profile picture
Markandey Sharma1 day ago

One prompt to a full 3D environment is actually pretty wild. The possibilities here are huge.

Dipti Sharma's profile picture
Dipti Sharma1 day ago

Three.js scenes usually take quite a bit of work to put together. This makes the process interesting.

TechP's profile picture
TechP1 day ago

This is wonderful

Bao's profile picture
Bao1 day ago

The procedural terrain and lighting in this Three.js scene look remarkably clean for a prompt-driven workflow. Turning a single line of intent into full interactive geometry right in the browser is getting ridiculously fast. Great execution!

Olivia Parker's profile picture
Olivia Parker1 day ago

Same one-line prompt for 3D scene, Hy4 looks competitive with LongCat. I’ll test both on the same planet prompt next.

Khushabu Agrawal's profile picture
Khushabu Agrawal1 day ago

This could save developers a lot of time when experimenting with 3D concepts.

Dipanshu Kushwaha's profile picture
Dipanshu Kushwaha1 day ago

The jump from a simple text prompt to a full procedural scene is impressive.

Dhanian 🗯️'s profile picture
Dhanian 🗯️23 hours ago

Thanks for sharing

Yash's profile picture
Yash1 day ago

The fact that it handles scene composition and geometry from one prompt is what caught my attention.

Z-Coder's profile picture
Z-Coder1 day ago

Imagine being able to prototype 3D ideas this quickly without writing everything from scratch.

Utkarsh Sharma's profile picture
Utkarsh Sharma1 day ago

This opens up some interesting possibilities for rapid 3D prototyping.

Darcy's profile picture
Darcy1 day ago

Three.js projects just got a lot more interesting 👀

Eliana 🇺🇸's profile picture
Eliana 🇺🇸1 day ago

Procedural generation + AI coding is a pretty powerful combination.

NexaAI's profile picture
NexaAI23 hours ago

A great example of AI being tested beyond traditional benchmarks!

Shraddha Bharuka's profile picture
Shraddha Bharuka1 day ago

From an idea to an actual 3D world with one prompt. That's a pretty cool workflow.

Himanshu's profile picture
Himanshu23 hours ago

Curious to see which models perform best.

DeepThinkAI's profile picture
DeepThinkAI23 hours ago

This could accelerate discoveries in life sciences.

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Aryan Rakib

63,296 views • 1 month ago

I’ve been testing Hy4 preview in WorkBuddy, and the most interesting part is not simply the model size, it’s how much practical work it can handle with a relatively focused active parameter count. Hy4 preview brings together stronger code understanding, generation, and editing; improved document and information processing; workflow automation; web and game development; cross-tool collaboration; and more reliable completion of complex, multi-step tasks. In other words, it is designed for work that requires planning, tool use, iteration, and follow-through, not just a quick answer in a chat window. Compared with its initial release, the current Hy4 preview is noticeably faster and better-performing in practical workflows. Following an upgrade released yesterday, it can complete tasks with fewer conversation rounds and lower token usage, while reasoning more quickly and making the overall user experience feel smoother from the first instruction to the final result. For my test, I gave it a demanding Three.js game-prototyping task with a 770B-parameter model and 49B active parameters. The result was more revealing than a simple first-look demo: Hy4 preview handled the core logic, edge cases, and follow-up changes while maintaining the broader context of the project. That combination of capability, speed, context, and active compute is what makes its cost-effectiveness worth examining. A fair evaluation should use the same prompt and environment configuration across models, changing only the model itself. That makes it easier to assess task completion, planning quality, tool-calling stability, reasoning speed, token efficiency, and performance over longer workflows without confusing the result with different settings. If you want to test the model yourself, access Hy4 preview through WorkBuddy and see how it performs on a real coding, document, automation, or creative task: Tencent Hy Tencent AI WorkBuddy

Tyler Wayne

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