Four models, one prompt, and a real manual playtest of three of the four (Opus 5 was added later and scored from a code read only). Part of our ongoing /design benchmark series in Command Code.
The prompt
Create a complete single HTML file for a fun top-down car racing game using HTML5 Canvas with a 700x700 canvas size... Implement realistic car physics including acceleration, deceleration, braking, turning with momentum and slight drifting when turning at high speed... Increase difficulty by adding more enemies and higher speed as the score rises... Use requestAnimationFrame for smooth 60fps gameplay, add simple Web Audio API sound effects for engine, coin collect, and crash.
(Full prompt in the repo.)
Seen on X
The three-model round that this benchmark's manual playtest is based on was posted with the actual clip:
GPT-5.6 Sol vs Fable 5 vs Grok 4.5 Built a car racing game with a UX-over-UI focus, using /design command....
Scorecard
| Model | Spec fidelity | Physics/feel | Collision | Architecture | Polish/UI | Offline-safe | Mean | Cost | Quality/$ |
|---|---|---|---|---|---|---|---|---|---|
| Grok 4.5 | 5 | 5 | 4 | 4.5 | 4.5 | 5 | 4.67 | $0.40 | ~11.7 |
| Opus 5 | 5 | 4.5 | 4 | 4.5 | 4.5 | 5 | 4.58 | $0.247 | ~18.5 |
| Fable 5 | 5 | 4 | 4 | 4 | 4 | 5 | 4.33 | $0.65 | ~6.7 |
| GPT-5.6 Sol | 4 | 2 | 2.5 | 3.5 | 5 | 5 | 3.67 | $0.50 | ~7.3 |
Manual playtest (Grok 4.5, Fable 5, GPT-5.6 Sol only): Grok 4.5 (9/10) > Fable 5 (8/10) > GPT-5.6 Sol (6/10). Opus 5 was added afterward and was not hand-played; its Physics/feel score above is a code-read estimate, not a played impression.
Which model should you reach for
If you're prototyping a driving or arcade-physics game with AI and gameplay feel is what matters most, this round says start with Grok 4.5 or Opus 5, not the model with the flashiest UI. GPT-5.6 Sol proves the two aren't the same thing: the best-looking dashboard in the set shipped with physics that fought its own prompt. If your project needs a polished HUD more than tight driving feel, that tradeoff flips.
This is the recurring reason teams run the same prompt across models before picking one, instead of committing to a single provider up front. Command Code makes that comparison a one-line change - /model grok-4.5 today, /model opus-5 tomorrow, same session, same taste profile, same cost dashboard - so you're choosing based on how a model actually performs on your brief, not on a vendor's benchmark slide.
Verdict
On gameplay feel, the manual playtest is decisive for the original three: Grok 4.5 wins on progressive steering and crash response, Fable 5 is a close second, and GPT-5.6 Sol has the best UI in the set paired with physics that directly contradict its own prompt.
Opus 5 wasn't put through that same playtest, so it isn't ranked into the 9/8/6 ordering, but on a static read it looks architecturally closer to Grok's momentum-based approach than to GPT's over-corrected one. On quality-per-dollar it's the standout: a ~$0.247 floor roughly 60% cheaper than Grok's ~$0.40 for a mean score within 0.09 of it. Whether it actually feels as good as Grok in the hand is the one open question this round doesn't answer.
Try this yourself
1npm i -g command-code1/model grok-4.5
2/design Create a complete single HTML file for a fun top-down car racing game using HTML5 Canvas with a 700x700 canvas size, realistic car physics with momentum and drifting, enemy cars, coins, power-ups, a speedometer, and lives system.Full command reference: commandcode.ai/docs/slash-commands/design. More one-shot comparisons: CommandCodeAI/slash-design-showcase.
