The article introduces Qwen3‑TTS, a dual‑track multilingual text‑to‑speech model trained on over five million hours of speech, detailing its two tokenizers, 3‑second voice‑cloning capability, SOTA benchmark results, and step‑by‑step instructions for running the demo on HyperAI.
This guide walks through installing and running Alibaba's open‑source Qwen3‑TTS on Ubuntu, covering environment setup, GPU requirements, model selection, Python virtual‑environment creation, code examples for voice cloning and voice design, low‑latency streaming, Web UI launch, and common troubleshooting tips.
Qwen3‑TTS, an open‑source text‑to‑speech model from Alibaba, offers sub‑100 ms first‑packet latency, supports voice cloning, natural‑language voice design, and ten languages, can be deployed locally on a GPU with as little as 8 GB VRAM, and integrates with ComfyUI for visual workflow building.
This guide walks through installing the open‑source Qwen3‑TTS model on Ubuntu, covering environment setup, GPU requirements, package installation, model variants, and hands‑on Python scripts for ultra‑low‑latency voice cloning and text‑driven voice design.
