Deploying this model locally is quickest when done via a simple curl command.

Follow the step-by-step instructions below.

The installer automatically pulls the model (could be multiple GBs).

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

📘 Build Hash: 55c4171893dbdc49ab15217d5d5bb12d • 🗓 2026-07-05 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: required: fast PCIe 4.0 drive for instant boots Graphics: stable 30+ tk/s at 4-bit quantization on medium setup

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:

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