Skip to main content
ShippedNo vapor

The AI that actually shipped

VerdictOpenMOSS Team (OpenMOSS-Team)

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 →

Real4.0Apache 2.0 weights, though the card needs trust_remote_code and pinned torch.
Useful4.0Long-form output, duration control and cloning cover narration and dubbing work.
Notable3.5A broad family with dialogue, sound effects and realtime siblings.
Novel3.5Token-level duration control is uncommon, the rest is familiar.
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 →

OpenMOSS Team releases MOSS-TTS, an 8B Apache 2.0 voice cloning and long-form TTS

MOSS-TTS is an 8B (and 1.7B) open TTS family with cloning, up to an hour of long-form audio and duration control.

OpenMOSS Team released MOSS-TTS, a family led by an 8B flagship (MossTTSDelay, recommended for production) and a 1.7B MossTTSLocal (recommended for research). The card lists 20 languages but its table shows 19. Features include zero-shot voice cloning from reference audio, long-form generation described as up to one hour in a single run, token-level duration control (about 12.5 audio tokens per second), Pinyin and IPA pronunciation input, and code-switching within one utterance. Siblings include MOSS-TTSD for dialogue, MOSS-VoiceGenerator for voice design, MOSS-SoundEffect and MOSS-TTS-Realtime, which reports 180 ms time to first byte.

Self-reported Seed-TTS-eval: MossTTSDelay scores 1.84 English word error rate and 1.37 Chinese character error rate. The card calls these state of the art, but its own table shows Qwen3-TTS at 1.5 on English and GLM-TTS-RL at 0.89 on Chinese, both better.

The licence is Apache-2.0. Practical notes: it needs trust_remote_code, the README recommends Transformers 5.0.0, and only one reference audio is supported. The card gives no release date; the date used is the Hugging Face repo creation date, and the linked report is listed as published 18 March.

Useful family. The card's own table keeps the claims honest.

Sources

Editor's first pass (AI-assisted)

Primary evidence

Comments