The QIMMA leaderboard evaluates Arabic LLMs using human-centric quality metrics rather than automated benchmarks. It ranks models based on linguistic nuance and cultural accuracy across diverse dialects. This shift forces developers to prioritize high-quality curated data over raw volume. Practitioners can now identify models that actually handle complex Arabic syntax without hallucinating.