The fastest way to get this model running locally is via Docker.
Simply follow the directions outlined below.
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The client handles the setup, pulling gigabytes of data automatically.
The deployment tool scans your environment and automatically chooses the ideal parameters for your OS.
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🔗 SHA sum: 23be6f5e2b947913aa623a81aee261e7 | Updated: 2026-06-24
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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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