I personally want to test spatial, temporal, and causal coherence in an interactive 3D world. Does the model understand where things are, world stays consistent over time and do the consequences make sense? There is a million people generating random games here and there on yt, but I want something that I can reproduce every time a model comes out and gets scored.
For this first run, 9 models received the same three roughly 30-line game prompt. I just added Kimi k3 to the results.
They all ran in high-thinking mode through the same open source harness, with the same sub-agent setup and access to Three.js, Rapier, and Playwright. There is currently one run per model per brief, producing 27 browser-playable games.
Because the qualities I’m interested in are difficult to score automatically, the main evaluation happens through blind pairwise comparisons. You play two games built from the same brief without seeing the model names, then compare their game feel, world design, presentation, completeness, and overall quality.
I’m also publishing the prompts, generated artifacts, generation time, estimated cost, and code size.
Fable produced some of the strongest games from what I could see, but its three runs cost about $756. GPT-5.6 Sol cost about $108, while GLM-5.2 and Grok 4.5 each cost around $19. Opus also felt closer to Fable than I expected, considering the large cost difference. Kimi somehow ended up roughly at the cost of GPT, but performed somewhat similar to Opus (thats just my subjective opinion there)
This first run is small, and as stated above, human preference is subjective. But I plan on running more and hope to evolve the methodology. As long as I can afford all these tokens. Fable is ridiculously expensive.
If you look at it, I'd really appreciate criticism of the task methodology, design, blind evaluation, etc. What would make this rigorous enough to be truly useful.