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Whisper Small

Measured on 8 of 8 datasets in the Superwhisper speech benchmark.

Available as a model choice inside Superwhisper.

Results

Whisper Small accuracy and speed

Whisper Small is a fast local model for short dictation on modest hardware. On conversational audio the error rate climbs quickly, and the numbers below show how quickly.

61

Blended score

15.6%

Word error rate

0.33 s

Wait for the text

Macro average over 8 datasets on Apple M4

On Apple M4

DatasetScore WER Speed Recall F-score Response
AMI Meetingssw-app-local-sw-app-whisper-small-esb-ami-202608065518.2%36×0.33 s
Common Voice, Australian Englishsw-app-local-sw-app-whisper-small-common-voice-24-en-au-20260806817.4%21×0.33 s
Common Voice, spontaneous Englishsw-app-local-sw-app-whisper-small-common-voice-spontaneous-4-en-202608065518.0%32×0.33 s
Earnings 22sw-app-local-sw-app-whisper-small-esb-earnings22-202608066414.3%44×0.33 s
Earnings 22 (with vocabulary)sw-app-local-sw-app-whisper-small-contextual-earnings22-202608062538.6%34×58.5%72.6%0.33 s
LibriSpeech Othersw-app-local-sw-app-whisper-small-esb-librispeech-other-20260806827.3%37×0.33 s
Loquacioussw-app-local-sw-app-whisper-small-loquacious-test-202608067410.3%28×0.33 s
Phonetic vocabularysw-app-local-sw-app-whisper-small-phonetic-vocab-202608067310.8%12×71.4%76.9%0.33 s

Updated August 27, 2026 from bench commit 5344cab. The second line of each row is the run that produced it.

Method

How this was measured

Local results come from driving the real Superwhisper app over each clip, so they reflect the engine and decode settings that ship in the product rather than a separate implementation.

Word error rate counts insertions, deletions and substitutions against a human transcript, so lower is better. Speed is a multiple of real time, so higher is better. The full method and every other model is on the benchmarks page.

Compare

Other models in the benchmark

Same audio, same machines, same method.

Support

Frequently asked questions

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