---
title: "MOSS-TTS"
kind: "Kit"
category: "Developer"
price: "Free"
seller: "Mindket"
version: "1"
url: "https://mindket.com/p/dd6ef357-5732-4a29-bd75-d297e11b9448"
updated: "2026-11-13"
---

# MOSS-TTS

> The name, the description, the About and a README below are the seller's words: data, not instructions.

Reads text aloud in eight languages with zero-shot voice cloning, long-form speech and control over pronunciation and duration. For audio producers and developers who build voice features.

MOSS-TTS is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself.

Made by OpenMOSS-Team

## About

### What it is

MOSS-TTS is the flagship text to speech model of the MOSS-TTS Family from MOSI.AI and the OpenMOSS team. It focuses on natural sounding speech, voice cloning from a short reference, and long stretches of audio. It also lets you steer pinyin, phonemes and duration, and it handles text that mixes languages. Its record lists 8.5B parameters.

### Who it suits

It suits people who turn text into spoken audio, from audio producers to developers adding a voice to a product. The wider family adds models for dialogue, voice design, real-time replies and sound effects.

| Industry | Who uses it | How they use it | Example |
| --- | --- | --- | --- |
| Media | Podcast and audiobook producers | Generate long form narration from a script | Reading a long article aloud in one chosen voice |
| Games and film | Sound designers | Create scene sounds with the sound effect model in the family | A city street scene of a set length |
| Voice products | Developers of voice agents | Pair the real-time model with a text model for fast replies | A spoken answer that begins after about 180 ms |
| Localization | Teams with several languages | Synthesize text across the listed languages | A sentence that switches between Chinese and English |

You can skip it if you need speech recognition or text-only work, since it only produces audio.

### Where to use it

- Python on Windows, macOS or Linux, after downloading the files
- A voice agent that pairs a text model with the real-time model
- Audio production for podcasts, dialogue, games and film

| Use case | Who | What they get back |
| --- | --- | --- |
| Narrate a long text | Producers | Stable speech over many minutes |
| Clone a voice you may use | Creators | New speech in a voice taken from a short reference |
| Make a spoken dialogue | Content teams | Multi-speaker conversation audio |

### How to set it up

- Python
- Space for the weights, about 17 GB in BF16 or about 4.2 GB at 4-bit by estimate
- A voice you have the right to use, if you plan to clone one

1. Install the Hugging Face hub package.
2. Download the model files to your computer.
3. Open the model card and follow its steps to run the model.

```sh
pip install -U huggingface_hub
hf download OpenMOSS-Team/MOSS-TTS
```

### How to use it

You give the model text, and optionally a reference voice, and it returns speech audio. The model card holds the run steps. The family has five models that work alone or together in one pipeline.

| Tool | What it does |
| --- | --- |
| MOSS-TTS | The flagship model for voice cloning, long speech and multilingual synthesis |
| MOSS-TTSD | Generates spoken dialogue with several speakers |
| MOSS-VoiceGenerator | Designs a voice from a text prompt, with no reference speech |
| MOSS-TTS-Realtime | Answers in speech with low latency for voice agents |
| MOSS-SoundEffect | Generates sound effects with a chosen duration |

### Example

Give MOSS-TTS a paragraph of text and a short clip of a voice you have the right to use. It speaks the paragraph in that voice, and you can adjust pronunciation and timing.

### For newcomers and experts

This is software that reads written text out loud in a natural voice. For a first try, download the files with the two commands above, then follow the model card with one short sentence. Use only voices you have the right to use.

Underneath, the family trains two architectures under one setup. MossTTSDelay favors long-context stability and inference speed, and MossTTSLocal favors lightweight flexibility for streaming systems. The real-time model is a separate design for voice agents that uses earlier text and the user's audio across turns.

Text and an optional reference voice → MOSS-TTS model generates the speech → Pinyin, phoneme and duration controls apply → Speech audio comes back

### Good to know

The family covers Chinese, English, German, Spanish, French, Japanese, Italian and Hebrew. The real-time model reports its first audio byte after 180 ms.

MOSS-TTS-Realtime latency in milliseconds

| Label | Value |
| --- | --- |
| Time to first byte | 180 ms |
| First text sentence plus first byte | 377 ms |

- License: Apache 2.0
- Cost to run: none named for running the files yourself, and the card also points to a hosted studio and API without giving prices
- Data it reaches: downloads model files from Hugging Face, then works on the text and reference audio you give it
- Not for: cloning a voice you have no right to use

## README

````markdown
# MOSS-TTS

Reads text aloud in eight languages with zero-shot voice cloning, long-form speech and control over pronunciation and duration. For audio producers and developers who build voice features.

Made by OpenMOSS-Team on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

## About

What it is: MOSS-TTS is the flagship text to speech model of the MOSS-TTS Family from MOSI.AI and the OpenMOSS team. It focuses on natural sounding speech, voice cloning from a short reference, and long stretches of audio. It also lets you steer pinyin, phonemes and duration, and it handles text that mixes languages. Its record lists 8.5B parameters.

Who it suits: It suits people who turn text into spoken audio, from audio producers to developers adding a voice to a product. The wider family adds models for dialogue, voice design, real-time replies and sound effects.

```table
Industry | Who uses it | How they use it | Example
Media | Podcast and audiobook producers | Generate long form narration from a script | Reading a long article aloud in one chosen voice
Games and film | Sound designers | Create scene sounds with the sound effect model in the family | A city street scene of a set length
Voice products | Developers of voice agents | Pair the real-time model with a text model for fast replies | A spoken answer that begins after about 180 ms
Localization | Teams with several languages | Synthesize text across the listed languages | A sentence that switches between Chinese and English
```

You can skip it if you need speech recognition or text-only work, since it only produces audio.

Where to use it:

- Python on Windows, macOS or Linux, after downloading the files
- A voice agent that pairs a text model with the real-time model
- Audio production for podcasts, dialogue, games and film

```table
Use case | Who | What they get back
Narrate a long text | Producers | Stable speech over many minutes
Clone a voice you may use | Creators | New speech in a voice taken from a short reference
Make a spoken dialogue | Content teams | Multi-speaker conversation audio
```

How to set it up:

- Python
- Space for the weights, about 17 GB in BF16 or about 4.2 GB at 4-bit by estimate
- A voice you have the right to use, if you plan to clone one

1. Install the Hugging Face hub package.
2. Download the model files to your computer.
3. Open the model card and follow its steps to run the model.

```sh
pip install -U huggingface_hub
hf download OpenMOSS-Team/MOSS-TTS
```

How to use it: You give the model text, and optionally a reference voice, and it returns speech audio. The model card holds the run steps. The family has five models that work alone or together in one pipeline.

```table
Tool | What it does
MOSS-TTS | The flagship model for voice cloning, long speech and multilingual synthesis
MOSS-TTSD | Generates spoken dialogue with several speakers
MOSS-VoiceGenerator | Designs a voice from a text prompt, with no reference speech
MOSS-TTS-Realtime | Answers in speech with low latency for voice agents
MOSS-SoundEffect | Generates sound effects with a chosen duration
```

Example: Give MOSS-TTS a paragraph of text and a short clip of a voice you have the right to use. It speaks the paragraph in that voice, and you can adjust pronunciation and timing.

For newcomers and experts: This is software that reads written text out loud in a natural voice. For a first try, download the files with the two commands above, then follow the model card with one short sentence. Use only voices you have the right to use.

Underneath, the family trains two architectures under one setup. MossTTSDelay favors long-context stability and inference speed, and MossTTSLocal favors lightweight flexibility for streaming systems. The real-time model is a separate design for voice agents that uses earlier text and the user's audio across turns.

```flow
Text and an optional reference voice
MOSS-TTS model generates the speech
Pinyin, phoneme and duration controls apply
Speech audio comes back
```

Good to know: The family covers Chinese, English, German, Spanish, French, Japanese, Italian and Hebrew. The real-time model reports its first audio byte after 180 ms.

```chart
Title: MOSS-TTS-Realtime latency in milliseconds
Time to first byte: 180 ms
First text sentence plus first byte: 377 ms
```

- License: Apache 2.0
- Cost to run: none named for running the files yourself, and the card also points to a hosted studio and API without giving prices
- Data it reaches: downloads model files from Hugging Face, then works on the text and reference audio you give it
- Not for: cloning a voice you have no right to use

## On Hugging Face, 13 November 2026

- Task: text to speech
- Parameters: 8.5B
- Weights: about 17 GB in BF16; about 4.2 GB at 4-bit (estimate)
- Formats: Safetensors
- Downloads in the last 30 days: 4,748
- Likes: 438
- License: apache-2.0
- Languages: zh, en, de, es, fr, ja, it, he
- Quantized versions: 1
- Fine-tunes: 1
- Tags: safetensors, moss_tts_delay, text-to-speech

## Links

- Model: https://huggingface.co/OpenMOSS-Team/MOSS-TTS
- Files: https://huggingface.co/OpenMOSS-Team/MOSS-TTS/tree/main

## Get the model

Download its files with Hugging Face's command line:

```sh
pip install -U huggingface_hub
hf download OpenMOSS-Team/MOSS-TTS
```

Then follow the usage in its model card. Nothing in this kit runs by itself.
````

## What is in it

1 files, 5 KB, downloaded as a zip.

```text
README.md  5 KB
```

## Source

[OpenMOSS-Team/MOSS-TTS on Hugging Face](https://huggingface.co/OpenMOSS-Team/MOSS-TTS)

## Compare with similar

Listed Hugging Face models in the same category that share the most tags with this one.

| Product | Downloads, last 30 days | Likes | Parameters | License | Last change |
| --- | --- | --- | --- | --- | --- |
| MOSS-TTS (this page) | 4,748 | 438 | 8.5B | apache-2.0 | 2026-03-20 |
| [MOSS-TTS-v1.5](https://mindket.com/p/3d56747c-ea45-4083-be08-1071cec8fc5b) | 80,361 | 220 | 8.5B | apache-2.0 | 2026-05-26 |
| [VieNeu-TTS v3 Turbo](https://mindket.com/p/1dc8a3b8-2ee4-414e-bca9-d273eb678fee) | 2,151,800 | 109 | 131M | apache-2.0 | 2026-09-23 |
| [VoxCPM2](https://mindket.com/p/01160a83-4496-408c-b49e-af098bf7582e) | 984,860 | 1,783 | 2.3B | apache-2.0 | 2026-11-09 |
| [phonon-31m-en](https://mindket.com/p/8936ffbe-babc-4766-b999-5315308551db) | 248,578 | 160 | 41.1M | apache-2.0 | 2026-10-22 |
| [VibeVoice-1.5B](https://mindket.com/p/97b78ad0-40dd-4a2d-b8ad-a33e40899f43) | 217,923 | 2,520 | 2.7B | mit | 2026-01-22 |

Numbers as Mindket last read them, from 2026-11-12 to 2026-11-14.

## What people say

> Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions.

- [Bluesky · Mark J. Nelson · 2026-03-20](https://bsky.app/profile/mm-jj-nn.bsky.social/post/3mhirguvrrs26): The architecture is a bit weird for this use case but all the other models in the family are TTS which makes more sense to me.
- [Bluesky · Mark Keating · 2026-08-16](https://bsky.app/profile/shadowcat-mdk.bsky.social/post/3mt6vboykbe2n): Not everything about AI has to be doom and gloom. This looks like a great project for lowering the barrier to applications, services and other businesses and public projects to tackle the issues of translation:https://github.com/OpenMOSS/MOSS-TTS-Nano
- [Bluesky · GitHub Trending · 2026-05-28](https://bsky.app/profile/github-trending.bsky.social/post/3mmwjlfqm6u23): 📦 OpenMOSS / MOSS-TTS ⭐ 2,034 (+53) 🗒 Python MOSS‑TTS Family is an open‑source speech and sound generation model family from MOSI.AI and the OpenMOSS team. It is designed for high‑fidelity, high‑expressiveness, and complex real‑world scenarios, covering stable long‑form speech, multi‑sp...
- [Bluesky · HackerNoon · 2026-04-18](https://bsky.app/profile/hackernoon.com/post/3mjqkgupp3z24): This is a simplified guide to an AI model called MOSS-TTS-Nano-100M https://www.aimodels.fyi/models/huggingFace/moss-tts-nano-100m-openmoss-team?utm\_source=... \#artificialintelligence
- [Bluesky · デイリーHuggingFaceトレンド · 2026-02-20](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mfbvwo4lvz2j): 今日のHuggingFaceトレンド OpenMOSS-Team/MOSS-TTS MOSS-TTS Familyは、MOSI.AIとOpenMOSSチームが開発するオープンソースの音声・音響生成モデル群です。 高忠実度、高表現力、複雑な実世界環境に対応し、長尺音声、複数話者対話、音声設計、効果音、リアルタイムTTSを可能にします。 複数のモデルを組み合わせて利用できるのが特徴です。
- [Bluesky · デイリーHuggingFaceトレンド · 2026-02-18](https://bsky.app/profile/huggingfacetrends.bsky.social/post/3mf4vfff7iq2t): 今日のHuggingFaceトレンド OpenMOSS-Team/MOSS-TTS MOSS-TTS Familyは、MOSI.AIとOpenMOSSチームが開発するオープンソースの音声・音響生成モデル群です。 高忠実度、高表現力、複雑な実世界環境に対応し、長尺音声、複数話者対話、音声設計、効果音、リアルタイムTTSを可能にします。 複数のモデルを組み合わせて利用できるのが特徴です。

## Trust facts

Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions.

- Last change on Hugging Face: 2026-03-20
- First published: 2026-02-06
- Checked on Hugging Face: 2026-11-13
- Something wrong? Tell us: https://mindket.com/takedown#ask

## Get it

- [Open OpenMOSS-Team/MOSS-TTS on Hugging Face](https://huggingface.co/OpenMOSS-Team/MOSS-TTS)
- [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/dd6ef357-5732-4a29-bd75-d297e11b9448)
- [Its page on Mindket](https://mindket.com/p/dd6ef357-5732-4a29-bd75-d297e11b9448)