AudioProcessBench - Majority Voting Selection: leaderboard

AudioProcessBench (2026) tests audio and omni-modal models as critics of audio-grounded reasoning: given an audio question and a model-written reasoning chain split into steps, the critic marks each step correct or wrong; 3,872 annotated chains from MMAR, MMSU and MMAU-Pro questions. This board sums the chain scores of the critic for each candidate answer and reports the accuracy of the chosen answer in percent; higher is better.

Metric: Final-answer accuracy (%) when the critic's chain scores are summed per candidate answer; 3,872 reasoning traces (23,497 steps, 41% erroneous) from six audio and omni models on MMAR, MMSU and MMAU-Pro questions, steps labelled by two LLM annotators with human review; few-shot critic prompt with three annotated example chains, temperature 0.7; random 40.6; higher is better. Source: arxiv.org. Saturation forecast: Around 2030. 11 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash61.5#164
2Gemma 3n E4B54#3301
3Phi-4 Multimodal Instruct53.7#3882
4Gemma 4 E2B53.2#3892
5Qwen2.5-Omni-7B53.1#1789
6Gemma 3n E2B52.5#6091
7Gemma 4 E4B52.2#2214

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

Interactive version: theaggregate.ai/benchmark?slug=audioprocessbench-majority-voting-selection · How It Works · Data refreshed daily, snapshot 2026-11-13.