HELM Audio - Auditory Perception: leaderboard

The "Auditory Perception" subtask of HELM Audio. Stanford HELM's audio project (AHELM): audio-language models are given speech and sound clips and scored on transcription, spoken-question answering, reasoning over audio, speaker and emotion attributes, safety and fairness.

Metric: Mean win rate. Source: crfm.stanford.edu. Saturation forecast: Estimated already saturated. 17 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro (Preview 05-06)93.75#148
2Qwen2.5-Omni-7B73.44#632
3Gemini 2.0 Flash68.75#344
4Gemini 2.0 Flash (Preview)65.62#366
5Gemini 2.5 Flash (Preview 05-20)64.06#214
6Gemini 1.5 Pro (002)51.56#350
7Qwen2-Audio-7B-Instruct46.88#888
8Gemini 2.0 Flash Lite45.31#453
9Gemini 1.5 Flash (002)35.94#585
10Gemini 1.5 Pro (001)26.56#446
11Gemini 1.5 Flash (001)14.06#580

No result here: #4 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=helm-audio-auditory-perception · How It Works · Data refreshed daily, snapshot 2026-10-23.