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How to Run Qwen3-TTS-12Hz-1.7B-CustomVoice

How to Run Qwen3-TTS-12Hz-1.7B-CustomVoice

The fastest tactical way to launch this model locally is via a Docker image.

Follow the straightforward walkthrough provided below.

No manual effort needed; the setup auto-ingests the large data.

The engine benchmarks your hardware to apply the most effective operational mode.

📦 Hash-sum → 884c14dd17a43f6c291e52b3df59a382 | 📌 Updated on 2026-06-26



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: at least 32 GB in dual-channel mode for bandwidth
  • Disk Space:70 GB free space for full FP16 weights storage
  • Graphics: CUDA Compute Capability 8.0+ required for flash-attention

Qwen3-TTS-12Hz-1.7B-CustomVoice is a cutting‑edge text‑to‑speech model that delivers high‑fidelity voice synthesis at a 12 Hz frame rate. It supports custom voice cloning, allowing users to train on just a few samples and generate personalized speech that retains the speaker’s unique characteristics. Its 1.7 B parameter architecture balances performance with a low memory footprint, making it suitable for deployment on consumer‑grade hardware. Inference latency stays under 50 ms per utterance, enabling real‑time applications such as interactive assistants and live dubbing. The model has been optimized for multiple languages and prosodic styles, producing natural‑sounding output across a wide range of domains.

Spec Value
Parameter Count 1.7 B
Sample Rate 12 Hz (frame)
Training Data 200 h multi‑speaker speech
Latency <50 ms
Supported Languages 20+
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