Setup Qwen3-ASR-1.7B on AMD/Nvidia GPU

Using Docker is the absolute quickest way to install this model on your local machine.

Make sure to follow the instructions below.

The loader auto-caches the model archive (several GBs included).

To guarantee smooth performance, the installation process auto-selects the best possible options for your PC.

🔐 Hash sum: 19ea5558a7306f62d7d588a42502f76d | 📅 Last update: 2026-06-22



  • Processor: next-gen chip for heavy context processing
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: free: 80 GB on system drive for scratch space
  • Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

The Qwen3-ASR-1.7B model delivers high‑accuracy automatic speech recognition across a wide range of languages and accents. Built on an efficient transformer architecture, it balances performance with a modest 1.7 B parameter count, making it suitable for both research and production environments. Its training leverages large‑scale multilingual corpora, enabling real‑time transcription with low latency on consumer hardware. The model incorporates advanced noise‑robustness techniques, ensuring reliable output even in challenging acoustic settings. Below is a quick overview of its core specifications:

Model Name Qwen3-ASR-1.7B
Parameters 1.7 B
Language Support Multilingual ASR
Key Feature Real‑time speech transcription
  • Automated file verification bypass for loading modified save data blocks
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دسته‌بندی‌ها: EXL2