MOSS-TTS-Nano (0.1B)

MOSS-TTS-Nano is an open-source multilingual tiny speech generation model from MOSI.AI and the OpenMOSS team. With only 0.1B parameters, it is designed for realtime speech generation, can run directly on CPU without a GPU, and delivers native 48 kHz stereo audio.

Introduction

MOSS-TTS-Nano focuses on the part of TTS deployment that matters most in practice: small footprint, low latency, good enough quality for realtime products, and simple local setup. It uses a pure autoregressive Audio Tokenizer + LLM pipeline.

Installation

pip install transformers==4.57.5 torch torchaudio soundfile

Quick Inference (Hugging Face AutoModel)

Load the model once, then choose your preferred generation mode:

import torch
from transformers import AutoModel

# Load model directly from Hugging Face
model_id = "maanka2/MOSS-TTS-Nano-100M"
model = AutoModel.from_pretrained(model_id, trust_remote_code=True)
model.eval()

1. Zero-Shot Voice Clone

Clone any target voice using a short 3–10 second reference audio clip:

output = model.inference(
    text="Welcome to MOSS-TTS-Nano. Fast, real-time speech generation on CPU.",
    output_audio_path="voice_clone_output.wav",
    mode="voice_clone",
    prompt_audio_path="assets/audio/zh_1.wav",  # Reference speaker audio (3-10s)
)

print(f"Cloned audio generated at: {output['audio_path']}")

2. Real-Time Streaming Inference

Stream audio chunks iteratively with ultra-low latency while the model is still generating (ideal for chatbots and voice assistants):

for event in model.inference_stream(
    text="Streaming generation enables instantaneous playback before synthesis finishes.",
    output_audio_path="stream_output.wav",
    mode="voice_clone",
    prompt_audio_path="assets/audio/zh_1.wav"  # Reference speaker audio (3-10s)
):
    if event["type"] == "audio":
        audio_chunk = event["waveform"]  # torch.Tensor [channels, samples]
        sample_rate = event["sample_rate"]
        # Stream audio_chunk to speakers, WebRTC, or WebSocket
    elif event["type"] == "result":
        print(f"Streaming complete. Full audio saved to: {event['audio_path']}")

MOSS-Audio-Tokenizer-Nano

Model Specs

Citation

@misc{openmoss2026mossttsnano,
  title={MOSS-TTS-Nano},
  author={OpenMOSS Team},
  year={2026},
  howpublished={GitHub repository},
  url={https://github.com/OpenMOSS/MOSS-TTS-Nano}
}