MTEB is a benchmark for comparing text embedding models used in search and RAG systems, but its per-language leaderboard is misleading because each language is evaluated on different tasks with varying difficulty and frequency, making direct score comparisons invalid—for example, a model scoring 32 points higher on Malayalam than English does not mean it performs better in Malayalam.