Using Docker is the absolute quickest way to install this model on your local machine.
Just follow the guidelines provided below.
1-click setup: the app automatically fetches the large weight files.
You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.
🧾 Hash-sum — bcb655b638bae04bc4e627fffa799dfd • 🗓 Updated on: 2026-06-25
Processor: Intel i7 / Ryzen 7 for heavy Quantized models
RAM: fast 5600MHz+ required to avoid memory bottlenecks
Disk Space: 100 GB for multi-modal model vision components
Graphics: CUDA Compute Capability 8.0+ required for flash-attention
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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