LocalClaw/TTS/ARK-ASR-0.6B
Local ASR model

ARK-ASR-0.6B

Catalogue summary: Efficient multilingual ASR checkpoint trained with teacher-data adaptation and online policy distillation. The official Apache 2.0 release ships safetensors, custom Transformers code, processor files and an AutoArk inference script for 19-language local transcription.

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

Apple Silicon readyspeech-to-text transcription19 languagesApache 2.0
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Catalogue quality
9/10
Catalogue speed
9.2/10
Model size
0.6B decoder plus audio encoder; single safetensors checkpoint
Voices
N/A (ASR: outputs text)

Can ARK-ASR-0.6B run locally?

ARK-ASR-0.6B 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.

Apache 2.0 license. Still verify upstream usage notes before shipping.

Upstream source
multilinguallow-latency

Audio profile

Cat. quality
9
Cat. speed
9.2
Audio
9.1

Best fit

ARK-ASR-0.6B is best for offline transcription, speech indexing and local voice pipelines.

Hardware: cpugpuapple

Model details

Type
Local ASR model
Family
ark-asr
Latency
low
Formats
transformerspytorchsafetensorsgguf
Languages
zh, en, de, ja, fr, ko, es, pl, it, ro, hu, cs, nl, fi, hr, sk, sl, et, lt
Context
Whisper-style 16 kHz audio encoder plus Qwen2 decoder with custom arkasr remote code; official inference uses scripts/infer/ark_asr_transformers.py, with third-party GGUF available for transcribe.cpp

Install locally

01
Check runtimeConfirm the backend supports transformers, 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
  • multilingual, low-latency

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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