Run Qwen3-TTS-12Hz-1.7B-CustomVoice with Native FP4 No-Code Guide

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

Just follow the guidelines provided below.

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

During setup, the script automatically determines and applies the best settings tailored to your machine.

💾 File hash: cb9f82b0d7cff51199a45cb824f7d903 (Update date: 2026-06-23)
  • CPU: 8-core / 16-thread recommended for orchestration
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space: 100 GB for multi-modal model vision components
  • GPU: high memory bandwidth GPU for next-gen local AI pipeline

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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