Big Bench Audio
Speech reasoning benchmark testing whether a voice model understands and reasons over what is said, not just transcribes it. Covers 12 tasks including emotion recognition, spoken arithmetic, factual Q&A, and instruction following. Evaluated by Artificial Analysis on speech-to-speech models. Higher is better.
Models ranked
5
tracked on this benchmark
Score band
97.6 – 29.2
best → lowest tracked
Snapshot trend
-20.13
May 24 → Jun 7 · 4 models
Leaderboard
Tracked models ranked by Accuracy (%) (higher is better).
How to read this benchmark
This benchmark scores models where higher is better. Use scores for directional filtering and shortlisting, not universal quality ranking; then validate pricing, context window, provider availability, and fit for your workload.
Trust this score when
- There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
- The model list covers the same version family you can actually deploy today.
- Top candidates overlap with your required routing and feature requirements.
Be cautious when
- There is only one benchmark snapshot or the dataset appears stale.
- The benchmark metric direction is opposite of your decision objective.
- The score difference between options is narrow and likely within implementation variance.
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Last reviewed: Jun 7, 2026