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NeuTTS Air ☁️

Created by Neuphonic - building faster, smaller, on-device voice AI

State-of-the-art Voice AI has been locked behind web APIs for too long. NeuTTS Air is the world’s first super-realistic, on-device, TTS speech language model with instant voice cloning. Built off a 0.5B LLM backbone, NeuTTS Air brings natural-sounding speech, real-time performance, built-in security and speaker cloning to your local device - unlocking a new category of embedded voice agents, assistants, toys, and compliance-safe apps.

Key Features

🗣Best-in-class realism for its size - produces natural, ultra-realistic voices that sound human
📱Optimised for on-device deployment - provided in GGML format, ready to run on phones, laptops, or even Raspberry Pis
👫Instant voice cloning - create your own speaker with as little as 3 seconds of audio
🚄Simple LM + codec architecture built off a 0.5B backbone - the sweet spot between speed, size, and quality for real-world applications

Websites like neutts.com are popping up and they're not affliated with Neuphonic, our github or this repo.

We are on neuphonic.com only. Please be careful out there! 🙏

Model Details

NeuTTS Air is built off Qwen 0.5B - a lightweight yet capable language model optimised for text understanding and generation - as well as a powerful combination of technologies designed for efficiency and quality:

Audio Codec: NeuCodec - our proprietary neural audio codec that achieves exceptional audio quality at low bitrates using a single codebook
Format: Available in GGML format for efficient on-device inference
Responsibility: Watermarked outputs
Inference Speed: Real-time generation on mid-range devices
Power Consumption: Optimised for mobile and embedded devices

Get Started with NeuTTS

Install System Dependencies (required): espeak-ng

With brew on macOS Ventura and later, apt in Ubuntu version 25 or Debian version 13, and choco/winget on Windows, install the latest version of espeak-ng with the commands below. If you have a different or older operating system, you may need to install from source: see the following link https://github.com/espeak-ng/espeak-ng/blob/master/docs/building.md

Please refer to the following link for instructions on how to install espeak-ng:

https://github.com/espeak-ng/espeak-ng/blob/master/docs/guide.md

# Mac OS
brew install espeak-ng

# Ubuntu/Debian
sudo apt install espeak-ng

# Windows install
# via chocolatey (https://community.chocolatey.org/packages?page=1&prerelease=False&moderatorQueue=False&tags=espeak)
choco install espeak-ng
# via winget
winget install -e --id eSpeak-NG.eSpeak-NG
# via msi (need to add to path or folow the "Windows users who installed via msi" below)
# find the msi at https://github.com/espeak-ng/espeak-ng/releases

Windows users who installed via msi / do not have their install on path need to run the following (see https://github.com/bootphon/phonemizer/issues/163)

$env:PHONEMIZER_ESPEAK_LIBRARY = "c:\Program Files\eSpeak NG\libespeak-ng.dll"
$env:PHONEMIZER_ESPEAK_PATH = "c:\Program Files\eSpeak NG"
setx PHONEMIZER_ESPEAK_LIBRARY "c:\Program Files\eSpeak NG\libespeak-ng.dll"
setx PHONEMIZER_ESPEAK_PATH "c:\Program Files\eSpeak NG"

Install NeuTTS
```
pip install neutts
```
Or for a local editable install, clone the neutts repository and run in the base folder:
```
pip install -e .
```
Alternatively to install all dependencies, including onnxruntime and llama-cpp-python (equivalent to steps 3 and 4 below):
```
pip install neutts[all]
```
or for an editable install:
```
pip install -e .[all]
```
(Optional) Install llama-cpp-python to use .gguf models.
```
pip install "neutts[llama]"
```
Note that this installs llama-cpp-python without GPU support. To install with GPU support (e.g., CUDA, MPS) please refer to: https://pypi.org/project/llama-cpp-python/
(Optional) Install onnxruntime to use the .onnx decoder.
```
pip install "neutts[onnx]"
```

Basic Example

Run the basic example script to synthesize speech:

python -m examples.basic_example \
  --input_text "My name is Dave, and um, I'm from London" \
  --ref_audio samples/dave.wav \
  --ref_text samples/dave.txt

To specify a particular model repo for the backbone or codec, add the --backbone argument. Available backbones are listed in NeuTTS-Air huggingface collection.

Several examples are available, including a Jupyter notebook in the examples folder.

Simple One-Code Block Usage

from neutts import NeuTTS
import soundfile as sf

tts = NeuTTS(backbone_repo="neuphonic/neutts-air-q4-gguf", backbone_device="cpu", codec_repo="neuphonic/neucodec", codec_device="cpu")
input_text = "My name is Dave, and um, I'm from London."

ref_text = "samples/dave.txt"
ref_audio_path = "samples/dave.wav"

ref_text = open(ref_text, "r").read().strip()
ref_codes = tts.encode_reference(ref_audio_path)

wav = tts.infer(input_text, ref_codes, ref_text)
sf.write("test.wav", wav, 24000)

Tips

NeuTTS Air requires two inputs:

A reference audio sample (.wav file)
A text string

The model then synthesises the text as speech in the style of the reference audio. This is what enables NeuTTS Air’s instant voice cloning capability.

Example Reference Files

You can find some ready-to-use samples in the examples folder:

samples/dave.wav
samples/jo.wav

Guidelines for Best Results

For optimal performance, reference audio samples should be:

Mono channel
16-44 kHz sample rate
3–15 seconds in length
Saved as a .wav file
Clean — minimal to no background noise
Natural, continuous speech — like a monologue or conversation, with few pauses, so the model can capture tone effectively