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Whisper Large V3

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

Available as a model choice inside Superwhisper.

Results

Whisper Large V3 accuracy and speed

The full Whisper Large V3 weights, running locally through whisper.cpp. More accurate than the turbo distillation on hard audio, and considerably slower.

61

Blended score

13.0%

Word error rate

1.72 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-large-v3-esb-ami-202608065913.6%7.2×1.73 s
Common Voice, Australian Englishsw-app-local-sw-app-whisper-large-v3-common-voice-24-en-au-20260806805.2%3.7×1.73 s
Common Voice, spontaneous Englishsw-app-local-sw-app-whisper-large-v3-common-voice-spontaneous-4-en-202608063921.6%6.3×1.73 s
Earnings 22sw-app-local-sw-app-whisper-large-v3-esb-earnings22-202608065914.0%9.1×1.73 s
Earnings 22 (with vocabulary)sw-app-local-sw-app-whisper-large-v3-contextual-earnings22-202608062328.1%7.5×68.6%78.9%1.73 s
LibriSpeech Othersw-app-local-sw-app-whisper-large-v3-esb-librispeech-other-20260806863.0%7.9×1.73 s
Loquacioussw-app-local-sw-app-whisper-large-v3-loquacious-test-20260806719.0%5.4×1.73 s
Phonetic vocabularysw-app-local-sw-app-whisper-large-v3-phonetic-vocab-20260806699.7%2.1×74.3%76.5%1.73 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

Run Whisper Large V3 yourself

Free to download, and the on-device models cost nothing to run.

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