MuLA-Bench - Narrative Domain: leaderboard

The narrative domain of the semantic track of MuLA-Bench (Yang et al., 2026), a benchmark of open-ended questions over long in-the-wild recordings, answered from the audio alone: 480 questions about spoken content in narrative and storytelling recordings, 30 in each of 16 languages. Each answer is judged correct or wrong by GPT-5.6 Sol against the reference with rubric and timing checks; accuracy in percent, higher is better.

Metric: Accuracy (%; the 480 semantic-track questions from narrative recordings, 30 in each of the 16 languages; 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 February 2027. 8 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.8 Flash78.1#36
2Gemini 3.7 Flash76.5#32
3Gemini 3.1 Pro (Preview)68.5#91
4Qwen 3.5 Omni Plus63.3#237
5Qwen3.5 Omni Flash48.7#548
6Muse Spark 1.228.1#97

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=mula-bench-narrative-domain · How It Works · Data refreshed daily, snapshot 2026-11-12.