⚡ Overview
We tested three frontier AI models on a brutal coding challenge: generate a complete, movie-quality Three.js solar system simulator in a single HTML file — all procedural textures, custom shaders, bloom post-processing, and interactive controls, zero external assets.
Same prompt, three models, head-to-head. The prompt specified 15+ celestial bodies with exact shader requirements (multi-layer FBM noise, vortex noise, cellular noise), 3 glow layers on the sun, Jupiter's Great Red Spot with spiral edges, Saturn's Cassini division, Earth's city lights on the dark side, and more. No shortcuts allowed.
🤖 Models Tested
| Model | Tool | Task 1: Solar System | Task 2: City Renderer |
|---|---|---|---|
| GPT-5.6 Sol | Codex | 11 min | 11 + 33 min (2 rounds) |
| Kimi K3 | Kimi Code | 45 min | 3+ hours, round 2 abandoned |
| Qwen3.8Max | Direct | — | <10 min (2 rounds) |
This is not a formal benchmark — it's a real-world stress test by GitHub user OBdangshang07. Same prompt, same expectations, measured wall-clock time from tool invocation to complete output. Quality judged by visual fidelity and code completeness.
🌌 Task 1: Solar System Simulator
The prompt demanded a cinematic-grade solar system with 15+ celestial bodies, each requiring custom ShaderMaterial with multi-layer noise. Key requirements:
- Sun: Dynamic plasma texture with 3 glow layers, sunspots, solar wind particles
- Jupiter: Multi-layer stretched noise bands, Great Red Spot with spiral edges, 3+ smaller vortices
- Saturn: Multi-layer translucent rings with Cassini division, particle scatter via shader
discard - Earth: Ocean specular highlights, city lights on dark side, Fresnel atmosphere shell
- Moons: 4 Galilean moons + 4 Saturnian moons, each with unique procedural textures
Results
| Aspect | GPT-5.6 Sol (11 min) | Kimi K3 (45 min) |
|---|---|---|
| Visual fidelity | ⭐⭐⭐⭐⭐ Excellent shaders, Jupiter bands look organic | ⭐⭐⭐⭐ Good but some bodies use simpler noise |
| Code completeness | All 15+ bodies, all moons included | All bodies present, some moons simplified |
| Interactivity | Smooth orbit controls, info panels, time warp | Similar controls, slightly less polished UI |
| Post-processing | UnrealBloomPass well-tuned | Bloom present but less refined |
| Stability | Stable at 60fps | Occasional frame drops on lower GPUs |
🏙️ Task 2: City Renderer
A harder challenge: generate a real-time metropolitan renderer with 50+ adjustable parameters, procedural infinite city, dynamic day/night cycle, atmospheric scattering, and dense 3D building clusters with unique textures.
Results
| Model | Round 1 | Round 2 (Refinement) | Building Density | Texture Quality |
|---|---|---|---|---|
| Qwen3.8Max | <10 min | <10 min | ⭐⭐⭐⭐⭐ Dense, varied | ⭐⭐⭐⭐ Good procedural |
| GPT-5.6 Sol | 11 min | 33 min | ⭐⭐⭐⭐ Dense | ⭐⭐⭐⭐⭐ Excellent detail |
| Kimi K3 | 3+ hours | ❌ Abandoned | ⭐⭐⭐ Moderate | ⭐⭐⭐ Decent |
Kimi K3 took over 3 hours for the first round and couldn't complete the second. The city renderer task exposed K3's weakness in generating complex, performance-sensitive 3D code with many interdependent systems (roads, traffic, lighting, building generation).
📊 Key Findings
🏎️ Speed
Qwen3.8Max is the speed king — both rounds under 10 minutes total. GPT-5.6 Sol is consistent (~11 min per task). Kimi K3 is 3-4x slower on complex tasks.
🎨 Quality
GPT-5.6 Sol produces the best visual quality — its shaders are more refined, noise layers more organic, and post-processing better tuned. Qwen3.8Max trades some visual polish for raw speed. Kimi K3's output is functional but less cinematic.
🔧 Reliability
GPT-5.6 Sol is the most reliable — it completed both tasks fully. Qwen3.8Max is fast but may need a refinement round. Kimi K3 can timeout on complex multi-system tasks.
🎮 Live Demos — Try Them Yourself
Below are the actual outputs from each model. Open them in your browser and compare the visual quality, interactivity, and performance:
☀️ Solar System Simulator
| Model | Generation Time | Demo |
|---|---|---|
| GPT-5.6 Sol | 11 min | 🚀 Launch Demo → |
| Kimi K3 | 45 min | 🚀 Launch Demo → |
🌃 City Renderer
| Model | Generation Time | Demo |
|---|---|---|
| GPT-5.6 Sol | 11 + 33 min | 🚀 Launch Demo → |
| Kimi K3 | 3+ hours | 🚀 Launch Demo → |
| Qwen3.8Max | <10 min × 2 | 🚀 Launch Demo → |
🎯 What This Means for Developers
- Need the best visual quality? → GPT-5.6 Sol (Codex). Best shaders, most polished output.
- Need speed? → Qwen3.8Max. Blazing fast, good enough quality for prototyping.
- Complex multi-system 3D? → Avoid Kimi K3 for now. It excels at simpler tasks but struggles with interconnected systems.
- Cost-sensitive? → Qwen3.8Max delivers the best time-to-quality ratio.
The gap between models is not just speed — it's about the complexity ceiling. GPT-5.6 Sol can handle prompts with 15+ interdependent shader systems. Qwen3.8Max is fast but may need refinement passes. Kimi K3 has a lower ceiling on complex 3D tasks.
For single-file HTML generation — the emerging "vibe coding" benchmark — GPT-5.6 Sol currently leads in quality, while Qwen3.8Max leads in throughput. Choose based on your priority.
📎 Source
All code, prompts, and test results are open source: github.com/OBdangshang07/AI_project
Test conducted by GitHub user OBdangshang07. Demos reproduced with original HTML output files.