Shall We Play a Game?

With the rapid pace of change in the field of artificial intelligence (AI), it is very hard to keep up with what is happening from one day to the next. If you want to use the best performing coding LLM for your latest project, for instance, how do you know which model is currently in the top spot? Sure, everyone has a personal opinion, but what if you want hard data, not just anecdotes? In cases such as these, most people turn to standardized benchmarks.

Unfortunately, benchmarks are not all they are cracked up to be. Very large frontier models have the potential to simply memorize a tremendous amount of information, which may make them look like they have reasoning capabilities on a benchmark when all they are really doing is regurgitating data. Worse yet, benchmarks can be (and are!) gamed by model developers. In some very public incidents, major players in the field have been caught submitting alternative versions of their models for benchmarking which have been fine-tuned to score highly, but that do not actually perform well in real-world applications.

Make your move

Google believes that the best way to prevent gaming AI benchmarks is through… gaming. They have just announced the release of the Kaggle Game Arena, which allows for head-to-head comparisons between frontier systems by assessing their performance in playing strategic games. By pitting the models against each other in games, there is a clear definition for winning, and their reasoning abilities can be better assessed than with traditional benchmarks.

The Kaggle Game Arena, developed in partnership with Google DeepMind, provides a dynamic, open, and scalable platform for testing AI models using competitive games like chess, Go, and poker. These games are ideal for evaluating AI because they require complex reasoning, long-term planning, adaptation, and, in some cases, even the ability to model an opponent's thoughts. Success in these arenas is not about memorization. It is about strategic thinking and problem-solving in real time.

Game Arena’s infrastructure is fully open-sourced, including the game environments, harnesses (which dictate what each model sees and enforce the rules), and visualizers. These components make the benchmarking process transparent and reproducible. Kaggle will maintain leaderboards on its platform going forward, updating them regularly as new games and models are added.

To kick off the new platform, Game Arena is hosting a three-day chess exhibition featuring eight of the world’s leading frontier models, including Gemini 2.5 Pro, Claude Opus 4, Grok 4, and others. The matches will be live-streamed and analyzed by top chess players. The tournament format for the exhibition is single-elimination, but the final rankings will be determined using a robust all-play-all system, where each model competes in over a hundred games against every other model to ensure statistical validity.

By assessing which model makes the best moves, we can learn a lot about its real-world performance. But when the day comes that a model tells us “the only winning move is not to play,” we might be in trouble.