AA ASR WER: Artificial Analysis ASR WER
About
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.Compare model scores alongside pricing, API availability, and release date — high benchmark score alone doesn't make a model the right pick.
How to read this benchmark
This benchmark uses a scoring system where lower is better. Scores are useful for directional filtering and model shortlisting, not for universal quality ranking.
Interpretation checklist: prefer benchmarks that are closest to your workload style, then validate against the linked model pages for pricing, context window, and provider availability.
Trust when:
- There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
- Model list covers the same version family you can actually deploy today.
- Top candidates overlap with your required routing and feature requirements.
Don't trust when:
- There is only one benchmark snapshot or the dataset appears stale.
- Benchmark metric direction is opposite of your decision objective.
- The score difference between options is narrow and likely within implementation variance.
Current modeled score band for tracked entries is roughly 3.6 – 2.4.
Window
Feb 5 to Jun 2
last 3 snapshots
Mean delta
-1.20
score points
Coverage
1
models in latest snapshot
Leaderboard preview (top 5)
- 1. Voxtral Mini Transcribe 23.6
- 2. MAI-Transcribe-12.6
- 3. MAI-Transcribe-1.52.4