QIMMA قِمّة ⛰: A Quality-First Arabic LLM Leaderboard

QIMMA قِمّة ⛰: A Quality-First Arabic LLM Leaderboard QIMMA validates benchmarks before evaluating models, ensuring reported scores reflect genuine Arabic language capability in LLMs. 🏆 Leaderboard · 🔧 GitHub · 📄 Paper If you've been tracking Arabic LLM evaluation, you've probably noticed a growing tension: the number of benchmarks and leaderboards is expanding rapidly, but are we actually measuring what we think we're measuring? We built QIMMA قمّة (Arabic for "summit"), to answer that question systematically. Instead of aggregating existing Arabic benchmarks as-is and running models on them, we applied a rigorous quality validation pipeline before any evaluation took place. What we found was sobering: even widely-used, well-regarded Arabic benchmarks contain systematic quality issues that can quietly corrupt evaluation results. This post walks through what QIMMA is, how we built it, what problems we found, and what the model rankings…