MuLA-Bench - Arabic: leaderboard

Metric: Accuracy (%; the 313 Arabic-language questions over both evidence tracks; open-ended questions over in-the-wild long-form recordings (median 36.8 minutes, capped at three hours) in the source language, answered from the full recording without transcripts, audio clipped only to a local model's native input limit; each answer judged correct or not by GPT-5.6 Sol on a route-specific binary rubric with programmatic structural and 3-second timing checks; missing or invalid answers scored wrong). Source: arxiv.org. Saturation forecast: Around December 2026. 8 models tracked.

Top models

#ModelScore
1Gemini 3.7 Flash72.5
2Gemini 3.8 Flash71.2
3Gemini 3.1 Pro (Preview)63.9
4Qwen 3.5 Omni Plus59.4
5Qwen3.5 Omni Flash41.9
6Muse Spark 1.231.6

Interactive version: theaggregate.ai/benchmark?slug=mula-bench-arabic · How It Works · Data refreshed daily, snapshot 2026-09-26.