AI Model Benchmarks Face a Credibility Crisis as Gaming and Data Contamination Undermine Evaluations

AI labs have built their competitive advantage on a fundamentally broken evaluation system. As data contamination, strategic gaming, and benchmark saturation render traditional benchmarking increasingly unreliable, the industry is scrambling to rebuild trust in how it measures progress.