Run Qwen3-TTS-12Hz-1.7B-Base Locally via Ollama 2 Uncensored Edition No-Code Guide

Run Qwen3-TTS-12Hz-1.7B-Base Locally via Ollama 2 Uncensored Edition No-Code Guide

Deploying this model locally is quickest when done via Docker.

Simply follow the directions outlined below.

Next, run the Docker command to spin up the container.

🔐 Hash sum: 05c75ecc8b74a58568e94f7e9b4a14a9 | 📅 Last update: 2026-06-21



  • CPU: modern architecture (Zen 3 / Alder Lake minimum)
  • RAM: enough space for background apps and OS overhead
  • Disk Space: free: 80 GB on system drive for scratch space
  • 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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