Zonos — Multilingual TTS with Voice Cloning

What it is

Zonos is an open-weight text-to-speech model by Zyphra, trained on more than 200,000 hours of multilingual speech data. It generates natural-sounding speech from text with zero-shot voice cloning from brief audio samples. Zonos supports English, Japanese, Chinese, French, and German, with controls for speaking rate, pitch, emotion, and audio quality.

Zonos targets developers building multilingual voice applications, accessibility tools, and content creation pipelines. It runs locally on GPUs with 6GB+ VRAM and includes both a Python API and a Gradio web interface.

How it saves time or tokens

Zonos enables voice cloning from a single audio sample without fine-tuning, eliminating the hours of recording and training that traditional TTS customization requires. The model achieves approximately 2x real-time factor on an RTX 4090, meaning it generates speech faster than playback speed. The Gradio interface provides a visual way to adjust emotion, pitch, and rate without writing code.

How to use

1. Install Zonos: pip install -e . in the cloned repository (requires a GPU with 6GB+ VRAM).
2. Load the model and generate speech using the Python API with Zonos.from_pretrained.
3. Alternatively, launch the Gradio web interface with uv run gradio_interface.py for interactive control.

Example

from zonos.model import Zonos
import torchaudio

# Load model
model = Zonos.from_pretrained('Zyphra/Zonos-v0.1-transformer')

# Load a speaker reference audio for voice cloning
ref_audio, sr = torchaudio.load('reference_speaker.wav')

# Generate speech with cloned voice
output = model.generate(
    text='Hello, this is a voice cloning demonstration.',
    speaker_audio=ref_audio,
    language='en'
)

torchaudio.save('output.wav', output, 24000)

Related on TokRepo

• AI Tools for Voice -- explore voice synthesis and processing tools for AI applications
• AI Tools for Content -- discover content creation workflows including audio generation

Common pitfalls

• Zonos requires a CUDA-compatible GPU with at least 6GB VRAM; CPU inference is not practical for real-time use.
• Voice cloning quality depends heavily on the reference audio; use clean, noise-free samples of at least 5 seconds for best results.
• The model weights are large (several GB); ensure sufficient disk space and bandwidth for the initial download from Hugging Face.