AudioProcessBench - First-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 finding the first wrong step of each chain; higher is better.

Metric: PRMScore (0-100) for locating the first erroneous step of each reasoning chain; 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 Flash63.5#164
2Gemma 4 E4B35.5#2214
3Gemma 3n E4B25.7#3301
4Gemma 4 E2B24.7#3892
5Qwen2.5-Omni-7B19.3#1789
6Gemma 3n E2B18.8#6091
7Phi-4 Multimodal Instruct18.5#3882

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

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