HELM Audio - Librispeech: leaderboard

The "Librispeech" 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)3.87#148
2Gemini 2.0 Flash4.34#344
3Gemini 2.0 Flash (Preview)4.39#366
4Gemini 2.0 Flash Lite4.9#453
5Gemini 1.5 Pro (002)5.23#350
6Gemini 1.5 Flash (002)6.22#585
7Gemini 1.5 Pro (001)7.1#446
8Gemini 2.5 Flash (Preview 05-20)7.66#214
9Qwen2.5-Omni-7B10.35#632
10Qwen2-Audio-7B-Instruct11.33#888
11Gemini 1.5 Flash (001)34.24#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-librispeech · How It Works · Data refreshed daily, snapshot 2026-10-23.