LocalClaw/TTS/Audar-ASR-V1-Turbo
Local ASR model

Audar-ASR-V1-Turbo

Catalogue summary: Arabic-first multilingual generative ASR model for dialect-aware local transcription. The official release ships full BF16 safetensors plus GGUF and vLLM builds, with benchmark-parity PyTorch/qwen-asr usage, llama.cpp support and real-time streaming notes.

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

Edge readyspeech-to-text transcription30 languagesAudarAI Community License v1.0
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Open model filesRecommended verified starting pointOpen in UnslothLaunches Unsloth Desktop on this modelOpen Python packageVerified package page without exposing a commandOpen on Hugging FaceFiles, licence and model cardCheck my machineOptional: verify the fit with your saved hardware

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Catalogue quality
9.4/10
Catalogue speed
8.6/10
Model size
2.35B params; 4.7 GB BF16 or 1.28 GB Q4 GGUF
Voices
N/A (ASR: Arabic-first transcription)

Can Audar-ASR-V1-Turbo run locally?

Audar-ASR-V1-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.

AudarAI Community License v1.0 license. Review upstream restrictions before commercial use.

Upstream source
streamingrealtimemultilinguallow-latency

Audio profile

Cat. quality
9.4
Cat. speed
8.6
Audio
9.1

Best fit

Audar-ASR-V1-Turbo is best for offline transcription, speech indexing and local voice pipelines.

Hardware: gpucpuedge

Model details

Type
Local ASR model
Family
audar
Latency
low
Formats
pytorchsafetensorsggufvllm
Languages
ar, en, multilingual
Context
2.35B BF16 Qwen3-ASR adaptation, 30 s 16 kHz audio window, Arabic MSA/dialects plus English and 28 more languages; vLLM W4A16 fits 12 GB GPUs

Install locally

01
Check runtimeConfirm the backend supports pytorch, safetensors, gguf, vllm 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
  • Edge 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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