A standalone PowerShell module provides the fastest route to local installation.
Follow the straightforward walkthrough provided below.
The script takes care of fetching the multi-gigabyte model weights.
During setup, the script automatically determines and applies the best settings.
🗂 Hash: 54252948eb404328309ed1ce49631bbb • Last Updated: 2026-07-02
- Processor: high single-core performance needed for token latency
- RAM: high-speed DDR5 memory preferred for CPU offloading
- Disk: 150+ GB for high-context vector database storage
- GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference
|
The Qwen3-TTS-12Hz-1.7B-Base model is a lightweight text‑to‑speech system designed for real‑time voice synthesis at a 12 Hz update rate. It leverages a compact 1.7 B parameter transformer architecture that balances expressive prosody with low computational overhead. The model incorporates multi‑speaker conditioning and a refined acoustic tokenizer to produce natural‑sounding speech across diverse linguistic styles. In benchmark evaluations, it achieves state‑of‑the‑art Mean Opinion Scores while maintaining a modest memory footprint suitable for edge devices. A comparative
showcases its performance against similar models, highlighting superior latency and quality metrics.
| Metric |
Value |
| Parameters |
1.7B |
| Update Rate |
12 Hz |
| MOS |
4.6 |
| Latency |
< 100 ms |
| Memory |
≈ 800 MB |
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