Qwen3.5-27B performs almost on par with 397B and GPT-5 mini in the Game Agent Coding League

Hi LocalLlama.

Here are the results from the March run of the GACL. A few observations from my side:

• GPT-5.4 clearly leads among the major models at the moment.
• Qwen3.5-27B performed better than every other Qwen model except 397B, trailing it by only 0.04 points. In my opinion, it’s an outstanding model.
• Kimi2.5 is currently the top open-weight model, ranking #6 globally, while GLM-5 comes next at #7 globally.
• Significant difference between Opus and Sonnet, more than I expected.
• GPT models dominate the Battleship game. However, Tic-Tac-Toe didn’t work well as a benchmark since nearly all models performed similarly. I’m planning to replace it with another game next month. Suggestions are welcome.

For context, GACL is a league where models generate agent code to play seven different games. Each model produces two agents, and each agent competes against every other agent except its paired “friendly” agent from the same model. In other words, the models themselves don’t play the games but they generate the agents that do. Only the top-performing agent from each model is considered when creating the leaderboards.

All game logs, scoreboards, and generated agent codes are available on the league page.

Github Link

League Link