Testing GPT-5.6 Generating 3D Webpages via Codex
APPSO · wechat · 2026-07-12
This article tests GPT-5.6's performance in generating complex 3D webpages within Codex/ChatGPT. The focus isn't just on whether it can write the code, but how it delivers via planning → task decomposition → parallel sub-agents → iterative refinement → outputting Diffs.
Key Observations
- For 3D scene generation, GPT-5.6's Ultra/Sol mode performs the best, creating relatively complete and detailed scenes on par with Fable5.
- However, the cost is significant: with the same prompt, the Codex version can take over 2 hours, whereas other models/web versions might output results in minutes.
- The article compares models like GPT-5.5, DeepSeek V4 Pro, Gemini 3.5 Thinking, GLM-5.2, and Hy3 on 3D prompts like Zhangjiajie stone forests, bears catching salmon, and space elevators, noting GPT-5.6's higher completion rate.
Author's Conclusion
- Evaluating complex 3D generation shouldn't just rely on "how good the final screenshot looks," but must also consider runnability, performance, rework iterations, delivery time, and resource consumption.
- When models start planning, dividing labor, reworking, and self-reviewing, a single generation increasingly resembles a temporary project team. Therefore, the question of the "strongest model" might soon require a work-hour/Token cost sheet" to be truly fair.
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