HELM Audio - Audiocaps: leaderboard
The "Audiocaps" 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: GPT-4o Judge Critique. Source: crfm.stanford.edu. Saturation forecast: Estimated already saturated. 17 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Qwen2-Audio-7B-Instruct | 2.67 | #881 |
| 2 | Qwen2.5-Omni-7B | 2.65 | #634 |
| 3 | Gemini 2.5 Pro (Preview 05-06) | 2.27 | #149 |
| 4 | Gemini 2.0 Flash | 1.98 | #345 |
| 5 | Gemini 2.0 Flash (Preview) | 1.98 | #369 |
| 6 | Gemini 2.5 Flash (Preview 05-20) | 1.97 | #217 |
| 7 | Gemini 2.0 Flash Lite | 1.88 | #455 |
| 8 | Gemini 1.5 Flash (002) | 1.42 | #584 |
| 9 | Gemini 1.5 Pro (002) | 1.37 | #352 |
| 10 | Gemini 1.5 Flash (001) | 1.36 | #587 |
| 11 | Gemini 1.5 Pro (001) | 1.35 | #461 |
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-audiocaps · How It Works · Data refreshed daily, snapshot 2026-10-24.