MuLA-Bench - Acoustic Evidence: leaderboard
Metric: Accuracy (%; the 1,198 acoustic-track questions about naturally occurring non-speech or paralinguistic events such as laughter, applause and music; 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 June 2027. 10 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Gemini 3.8 Flash | 55.26 |
| 2 | Gemini 3.7 Flash | 54.34 |
| 3 | Qwen 3.5 Omni Plus | 42.07 |
| 4 | Qwen3.5 Omni Flash | 27.63 |
| 5 | Gemini 3.1 Pro (Preview) | 26.63 |
| 6 | Muse Spark 1.2 | 24.71 |
| 7 | Qwen3 Omni 30B A3B Instruct | 11.6 |
Interactive version: theaggregate.ai/benchmark?slug=mula-bench-acoustic-evidence · How It Works · Data refreshed daily, snapshot 2026-09-26.