AudioProcessBench - All-Error Identification: 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 is the PRMScore on a 0 to 100 scale for judging every step, which rewards both catching wrong steps and keeping correct ones; higher is better.

Metric: PRMScore (0-100) of the binary correctness judgment on every step (balancing detection of erroneous and correct steps); 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; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 11 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash74.8#164
2Gemma 3n E4B55#3301
3Gemma 4 E4B54#2214
4Gemma 3n E2B49.2#6091
5Gemma 4 E2B44.2#3892
6Phi-4 Multimodal Instruct43.5#3882
7Qwen2.5-Omni-7B40.8#1789

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

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