Skip to main content
ShippedNo vapor

The AI that actually shipped

VerdictQwen (Qwen)

Editor's first pass (AI-assisted)

Scored by an AI research pass from the linked sources; a human editor will re-score it. How we score →

Real4.5Weights for several checkpoints are on Hugging Face under Apache 2.0, with vLLM-Omni support noted.
Useful4.0Cloning, preset voices and voice design cover most TTS tasks in ten languages.
Notable4.5Several checkpoints, a tokenizer and vLLM-Omni support make it a ready-to-use family.
Novel3.0Dual-track streaming and a family layout are tidy, but the idea is incremental.
Hype gap▼ −0.5 under
Shipped

Readers

Upvotes count the readers who want this seen. Ratings are 1 to 5 scores on the four dimensions; the rating count is the number of readers who rated it. The editor’s score is shown on its own and is the headline figure. Once readers sign in, their ratings will pull a score toward the readers’ view only as more of them rate, and a reader mean from fewer than 5 ratings is too few to print. How ranking works →

Qwen releases Qwen3-TTS, Apache 2.0 voice cloning in 10 languages

Qwen3-TTS is a family of open TTS models, 0.6B and 1.7B, with 3-second voice cloning, voice design and streaming, under Apache 2.0.

Alibaba's Qwen team released Qwen3-TTS, a family of open text-to-speech checkpoints. The card for the 1.7B Base model lists Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish and Italian. The Base model clones a voice from "a 3-second rapid voice clone" of reference audio, plus an optional transcript. Sibling checkpoints cover a 1.7B VoiceDesign model, 1.7B and 0.6B CustomVoice models with nine preset timbres, a 0.6B Base model and a tokenizer.

The card cites end-to-end synthesis latency "as low as 97ms" for the series' dual-track streaming design. It does not say that figure applies to this particular checkpoint. On the Seed-TTS test set the card reports a word error rate of 0.77 for Chinese and 1.24 for English, and it lists CosyVoice 3 ahead on Chinese at 0.71.

The licence is Apache 2.0. The card does not give a release date; the date here, 22 January 2026, is the date of the linked technical report on the card. The Hugging Face repo was created a day earlier.

It does what the card says. The latency figure comes with a caveat the headline omits.

Sources

Editor's first pass (AI-assisted)

Primary evidence

Comments