AA ASR WER: Artificial Analysis ASR WER
Word Error Rate measured by Artificial Analysis using a consistent methodology across a proprietary multi-domain test suite. Provides independent, reproducible comparison across both open-source and commercial STT APIs. Lower is better.
Models ranked
4
tracked on this benchmark
Score band
2.4 – 3.6
best → lowest tracked
Snapshot trend
-0.00
Apr 2 → Aug 26 · 1 models
Leaderboard
Tracked models ranked by WER (%) (lower is better).
Notes: Recommended seed value: 2.6 WER (%; lower is better). Evaluator: Artificial Analysis. Harness/methodology: Google reports locally evaluating default competitor APIs; Artificial Analysis' AA-WER index spans diverse datasets and separately evaluates non-streaming and streaming modalities. This row is for gemini-3.5-transcribe only, not the Live endpoint.
How to read this benchmark
This benchmark scores models where lower 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