X (atomic.chat) comparison: LongCat 2.0 vs GPT-5.5 in the same agentic game-development task (Duck Hunt)

One-sentence takeaway

In Kilo Code CLI, LongCat 2.0 (open weights, running locally/free) and GPT-5.5 (paid cloud) performed the same task: three agent iterations turned game.html into a retro Duck Hunt game with duck waves, ammunition, and physics. Both outputs were "smooth, with no clipping issues, and synchronized graphics/physics/game logic"; the only difference was the bill: $0 for LongCat versus $0.65 for GPT-5.5.

Raw data (key points)

• Method: Both models ran in agent mode in Kilo Code CLI under the same task (build Duck Hunt in a single game.html file, with three agent iterations, duck waves, ammunition, and physics).

• Usage and cost:

  • LongCat 2.0: 70.3K tokens, $0.00 (open weights, running locally)

  • GPT-5.5: 64.9K tokens, $0.65

• Quality conclusion (the author's own words): "LongCat stayed in sync across the graphics, physics, and game logic. Ducks fly and fall when hit, the dog goes to retrieve them, ammo counts down, and waves keep coming. Both run smoothly, with no clipping issues. The only difference is the bill — GPT costs $0.65, while LongCat running locally costs just $0."

Verification and applicable limits

• The author is a local AI application vendor (atomic.chat), and this comparison supports a commercial narrative of "local/free is better than paid cloud." There is a conflict of interest, but the method (same task, same framework, same number of iterations, with token and cost figures) is transparent and can be checked; the demo output link is attached to the post.

• The sample is a single task (single-file game development), so the conclusion is limited to "lightweight front-end game generation" and does not represent repository-scale engineering or long-horizon agent tasks.

• Together with the five official single-prompt projects (prompt directory 07) and the r/opencodeCLI Ubuntu case (prompt directory 08), this forms an evidence group for "creative/front-end coding tasks": LongCat 2.0 approaches the quality of leading closed models on this class of task, with a substantial cost advantage.

• Note: "GPT-5.5" here refers to the cloud model from 2026, and the $0.65 cost uses that platform's billing convention; prices from different periods and channels cannot be extrapolated directly.