• Introducing Community Benchmarks on Kaggle Jan 14, 2026 Today’s AI models require more than static accuracy scores. • Community Benchmarks, a new capability on Kaggle, enables the global AI community to design, run and share custom evaluations that better reflect real-world model behavior. • General summary Kaggle launched Community Benchmarks so you can design and share custom benchmarks for evaluating AI models. • You can build tasks to test model performance on specific problems. • Group those tasks into a benchmark to evaluate leading AI models and track their performance on a leaderboard. • Kaggle launched Community Benchmarks so you can design and share custom benchmarks for evaluating AI models.

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  • Introducing Community Benchmarks on Kaggle Today, Kaggle is launching Community Benchmarks, which lets the global AI community design, run and share their own custom benchmarks for evaluating AI models. This is the next step after we launched Kaggle Benchmarks last year, to provide trustworthy and transparent access to evaluations from top-tier research groups like Meta’s MultiLoKo and Google’s FACTS suite. Why community-driven evaluation matters AI capabilities have evolved so rapidly that it’s become difficult to evaluate model performance. Not long ago, a single accuracy score on a static d

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