MuLA-Bench - Semantic Evidence: leaderboard

Metric: Accuracy (%; the 3,840 semantic-track questions about spoken facts and relations, 30 per language-domain cell; 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. 10 models tracked.

Top models

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