HELM Audio - Meld Audio: leaderboard

The "Meld Audio" 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: PEM. Source: crfm.stanford.edu. Saturation forecast: Estimated already saturated. 17 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 1.5 Pro (002)51.6#350
2Qwen2.5-Omni-7B49.1#632
3Gemini 2.5 Pro (Preview 05-06)47.3#148
4Gemini 1.5 Flash (001)47.1#580
5Gemini 1.5 Pro (001)46.9#446
6Gemini 2.0 Flash (Preview)44.3#366
7Gemini 1.5 Flash (002)42.5#585
8Gemini 2.0 Flash42.3#344
9Gemini 2.0 Flash Lite36.8#453
10Gemini 2.5 Flash (Preview 05-20)34#214
11Qwen2-Audio-7B-Instruct26#888

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-meld-audio · How It Works · Data refreshed daily, snapshot 2026-10-23.