How to Run Qwen3-TTS-12Hz-1.7B-CustomVoice No Python Required

The fastest way to get this model running locally is via Optional Features.

Review and follow the instructions below.

The script takes care of fetching the multi-gigabyte model weights.

The initial setup handles the heavy lifting, fine-tuning the environment for your device.

🛡️ Checksum: be4ed394072c8e0dffc7610a6453394b — ⏰ Updated on: 2026-07-04



  • Processor: 6-core 3.5 GHz minimum required
  • RAM: 32 GB highly recommended for 26B+ GGUF models
  • Disk: 150+ GB for high-context vector database storage
  • Graphics: 12 GB VRAM minimum required for basic quantization

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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