One thing I've learned is that benchmark rankings rarely tell the whole story. A model that tops a reasoning benchmark can still underperform in production if it struggles with long-running workflows, tool usage, codebase context, or cost efficiency. The real evaluation starts when you measure success against actual business tasks not just leaderboard scores. Curious whether your analysis found any models that consistently delivered the best balance of quality, latency, and cost in real-world environments.