Local ASR model

Whisper v3 Turbo

Catalogue summary: OpenAI's optimized Whisper v3 with 4 decoder layers instead of 32. 8× faster than Whisper Large v3 with only minor accuracy trade-off. 99 languages supported. New gold standard for fast local transcription.

Repository editorial metadata; verify comparative claims in the linked upstream material.

Apple Silicon readyspeech-to-text transcription99 languagesMIT
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Catalogue quality
9.1/10
Catalogue speed
9.5/10
Model size
1.6 GB
Voices
N/A (ASR: outputs text)

Can Whisper v3 Turbo run locally?

Whisper v3 Turbo can run locally for offline speech-to-text. Use the verified setup options on this page; no terminal command is required to choose the right path.

MIT license. Still verify upstream usage notes before shipping.

streamingrealtimemultilinguallow-latency

Audio profile

Cat. quality
9.1
Cat. speed
9.5
Audio
9.2

Best fit

Whisper v3 Turbo is best for offline transcription, speech indexing and local voice pipelines.

Hardware: cpugpuapple

Model details

Type
Local ASR model
Family
whisper
Latency
ultra-low
Formats
pytorchsafetensorsgguf
Languages
multilingual
Context
809M params, 4 decoder layers, 99 languages

Install locally

01
Check runtimeConfirm the backend supports pytorch, safetensors, gguf on your machine.
02
Open recommended setupUse the app and model links above. LocalClaw does not expose a terminal command.
03
Test locallyRun a short private audio prompt before moving into production workflows.

Good for

  • speech-to-text transcription
  • Apple Silicon ready local workflows
  • streaming, realtime, multilingual

Watch before shipping

  • Validate pronunciation, latency and artifacts with your own voice samples.
  • Review the upstream license and acceptable-use notes.
  • Benchmark on your target CPU, Apple Silicon or GPU setup.

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