Cyberpunk Alley in Three.js: Claude Fable 5 vs Claude Opus 4.8 vs GPT-5.5 Pro
We asked three frontier AI models to write a complete Three.js scene from scratch — a neon-lit cyberpunk alley at night in the rain, with a locked-down camera path so the renders are directly comparable. One prompt, one shot, no edits. Every scene below is the model’s own code running in real time.
Create a complete single-file index.html using Three.js that renders a neon-lit cyberpunk alley at night in light rain — neon signs, wet reflective ground, rain particles, volumetric fog, and a fixed 10-second camera dolly down the alley so every model’s render is comparable.
The renders
Each scene is the model’s unedited code, recorded in a headless browser with software WebGL. Same prompt, same camera path, same 10 seconds. Which one nails the brief? Your call.
Claude Fable 5
Anthropic’s flagship, launched June 2026 as the successor to the Claude 4 line. Built for long-horizon agentic work, with creative coding as a headline strength.
Claude Opus 4.8
The top tier of Anthropic’s Claude 4 family, and the company’s flagship coding model until Fable 5 arrived. The Opus line is the one most big AI coding tools default to.
GPT-5.5 Pro
OpenAI’s deep-reasoning tier — it deliberates for minutes before writing a line, trading speed for thoroughness. The descendant of the o-series reasoning models.
All of them, stacked
Every render playing in parallel — same prompt, same camera, same clock.
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Split-screen comparison assets, ready to post. Credit appreciated, not required.
How we ran it
Every model received the identical prompt in a single turn: a complete single-file Three.js scene with no external assets, plus an exact camera specification (eye-level start, constant-speed 10-second dolly down the alley centerline with a ±4° sinusoidal yaw sway) so the renders line up frame for frame. No tools, no retries, no human edits — the first complete HTML file returned is what you see, recorded in headless Chromium with software WebGL (SwiftShader). Latency is wall-clock for the full API response, including any reasoning. GPT-5.5 Pro required its reasoning effort set to medium — at default effort it spent its entire 100k-token output budget reasoning and returned no code.
Run your own showdowns
PromptFrenzy benchmarks the big AI models on real prompts — images, styles, and now code. Browse the full library or compare models head to head.