HELM Audio - Speech Robust Bench: leaderboard

The "Speech Robust Bench" 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: WER. Source: crfm.stanford.edu. Saturation forecast: Estimated already saturated. 17 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro (Preview 05-06)3.88#148
2Gemini 2.0 Flash Lite4.92#453
3Gemini 2.5 Flash (Preview 05-20)7.66#214
4Qwen2.5-Omni-7B10.35#632
5Gemini 2.0 Flash (Preview)17.13#366
6Gemini 2.0 Flash17.75#344
7Gemini 1.5 Pro (002)20.7#350
8Gemini 1.5 Pro (001)21.25#446
9Gemini 1.5 Flash (002)21.41#585
10Qwen2-Audio-7B-Instruct39.94#888
11Gemini 1.5 Flash (001)49.85#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-speech-robust-bench · How It Works · Data refreshed daily, snapshot 2026-10-23.