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---
language:
- en
license: cc-by-4.0
pipeline_tag: text-to-speech
tags:
- voxtream
- text-to-speech
---
# Model Card for VoXtream
VoXtream, a fully autoregressive, zero-shot streaming text-to-speech system for real-time use that begins speaking from the first word.
### Key features
- **Streaming**: Support a full-stream scenario, where the full sentence is not known in advance. The model takes the text stream coming word-by-word as input and outputs an audio stream in 80ms chunks.
- **Speed**: Works **5x** times faster than real-time and achieves **102 ms** first packet latency on GPU.
- **Quality and efficiency**: With only 9k hours of training data, it matches or surpasses the quality and intelligibility of larger models or models trained on large datasets.
### Model Sources
- **Repository:** [repo](https://github.com/herimor/voxtream)
- **Paper:** [paper](https://arxiv.org/pdf/2509.15969)
- **Demo:** [demo](https://herimor.github.io/voxtream)
## Get started
### Installation
```bash
pip install voxtream
```
### Usage
#### Output streaming
```bash
voxtream \
--prompt-audio assets/audio/male.wav \
--prompt-text "The liquor was first created as 'Brandy Milk', produced with milk, brandy and vanilla." \
--text "In general, however, some method is then needed to evaluate each approximation." \
--output "output_stream.wav"
```
* Note: Initial run may take some time to download model weights.
#### Full streaming
```bash
voxtream \
--prompt-audio assets/audio/female.wav \
--prompt-text "Betty Cooper helps Archie with cleaning a store room, when Reggie attacks her." \
--text "Staff do not always do enough to prevent violence." \
--output "full_stream.wav" \
--full-stream
```
### Out-of-Scope Use
Any organization or individual is prohibited from using any technology mentioned in this paper to generate someone's speech without his/her consent, including but not limited to government leaders, political figures, and celebrities. If you do not comply with this item, you could be in violation of copyright laws.
## Training Data
The model was trained on a 9k-hour subset from [Emilia](https://huggingface.co/datasets/amphion/Emilia-Dataset) and [HiFiTTS2](https://huggingface.co/datasets/nvidia/hifitts-2) datasets. You can download it [here](https://huggingface.co/datasets/herimor/voxtream-train-9k). For more details, please check our paper.
## Citation
```
@article{torgashov2025voxtream,
author = {Torgashov, Nikita and Henter, Gustav Eje and Skantze, Gabriel},
title = {Vo{X}tream: Full-Stream Text-to-Speech with Extremely Low Latency},
journal = {arXiv:2509.15969},
year = {2025}
}
``` |