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

Simply follow the directions outlined below.

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The loader auto-caches the model archive (several GBs included).

You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.

📎 HASH: 91417207ad4d78f4c41bf8add371b75b | Updated: 2026-06-23 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: required: 16 GB absolute minimum for small models 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.

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