How to Run OmniVoice Locally: The Easy Way and the Manual Way (2026)

OmniVoice is the model people reach for when one cloned voice has to speak many languages. From a few seconds of reference audio it copies a voice and carries it into any of more than 600 languages, keeping the speaker's accent as it goes. It also builds brand-new voices from structured attributes like age, pitch, and accent, and it is one of the fastest cloning models available.

Most people looking to run it locally want one thing: OmniVoice running on their own machine, with a proper interface, without a weekend of debugging. This guide starts with that route, then covers the problems that make manual installs fail, and finally outlines the do-it-yourself path for anyone who wants it.

Three ways to run OmniVoice

	Install it yourself	Voice Creator Pro desktop app	Voice Creator Pro Cloud
What you set up	Python, PyTorch, GPU libraries, and the model, in versions you work out yourself	Install the app; it packages everything OmniVoice needs	Nothing; it runs in your browser
When something breaks	You fix it yourself	All dependencies included and tested; support helps if anything breaks	Nothing on your computer to break; support helps if needed
Hardware	NVIDIA GPU only (~4 GB)	NVIDIA, AMD, Intel Arc, or Apple Silicon; CPU-only works too	Any browser
Interface	Command line and Python scripts	Desktop app	Browser app
Numbers and dates	Often misread (no text normalization in the base model)	Read correctly	Read correctly
Voice design	In code	Menus for age, pitch, accent, and more	Menus for age, pitch, accent, and more
Long documents	You split and feed the text yourself	Import an EPUB, PDF, Word doc, or text file	Import an EPUB, PDF, Word doc, or text file
Runs offline	Yes, once set up	Yes	No
Cost	Free model; you supply the hardware (check the license)	One-time purchase, unlimited generations (see prices)	Free to generate and listen; downloads from $5 a month

The easy way: OmniVoice in the Voice Creator Pro desktop app

Voice Creator Pro is a desktop app for Windows and Apple Silicon Macs that ships OmniVoice ready to use. OmniVoice still runs on Python, PyTorch, and the GPU libraries for your graphics card, but the app packages all of them for you. You never have to work out which versions you need, where to download them, or why they won't talk to each other.

It runs on NVIDIA, AMD, or Intel Arc graphics cards (8 GB of video memory recommended), on Apple Silicon Macs, or on the CPU alone, more slowly.

1. Install the app. Download it from the Microsoft Store (which has a free trial) or the Mac App Store, and open it.
2. Pick OmniVoice from the model list.
3. Generate or clone. Type or paste your text and pick a voice, or drop in a clean 3 to 10 second clip to clone a voice, choose the output language, and click generate.

The desktop app runs OmniVoice locally and offline, so reference clips and scripts never leave your computer, and generations are unlimited. It is a one-time purchase (see current prices), with no subscription.

It also covers what the base model leaves out:

• Numbers read correctly. The open-source OmniVoice has no text normalization and tends to mangle prices, dates, and figures. Voice Creator Pro rewrites them into words before they reach the model, so you never spell out numbers by hand.
• Voice design with a form, not code. Set age, gender, pitch, accent, pace, and other attributes from menus. See the OmniVoice voice design guide for recipes.
• Long files. Drop in an EPUB, PDF, Word doc, or text file and it converts the whole thing, with no manual chunking.
• Dubbing, subtitles, and more. Video dubbing that clones each speaker automatically, subtitle generation, speech to text, and a voice changer sit in the same app.

No install at all: Voice Creator Pro Cloud

If you want to try OmniVoice before committing to anything, Voice Creator Pro Cloud runs it in your browser on server GPUs, so any laptop works, GPU or not. The free tier lets you generate and listen to audio with no card required. Downloading your audio for publishing starts at $5 a month. Your data is processed on servers to generate speech and is never used to train models.

Common problems when installing OmniVoice yourself

OmniVoice itself is not hard to use once it runs. Getting it to run is where people lose hours, and the failures follow a pattern.

PyTorch installs without GPU support. OmniVoice depends on PyTorch, and PyTorch comes in separate builds for CPU and for specific CUDA versions. A plain install frequently pulls the CPU-only build, so the model either refuses to use your graphics card or crawls. Nothing in the error message says "wrong build," so people blame the model.

CUDA and driver mismatches. The PyTorch build has to match a CUDA version your NVIDIA driver supports. An older driver, or a PyTorch build aimed at a newer CUDA release, produces cryptic CUDA errors at load time. Fixing it means updating drivers or reinstalling PyTorch against a different CUDA build, sometimes both.

Python and dependency conflicts. If you already run other AI tools (Stable Diffusion front ends, ComfyUI, other TTS models), they often want different versions of the same libraries. Installing OmniVoice into the same Python can quietly break one of them, which is why every manual guide tells you to create a separate virtual environment.

Non-NVIDIA hardware. The manual route is built around NVIDIA's CUDA. If you have an AMD graphics card on Windows, or an Apple Silicon Mac, the official instructions don't cover your setup, so you are on your own working out what to install instead.

Slow CPU fallback. When the GPU is not detected, or the card runs out of video memory, generation falls back to the processor. It still works, but a few seconds of speech can take minutes, which makes cloning experiments painful.

Poor clones from noisy reference audio. This one gets mistaken for an install problem. OmniVoice copies what it hears, including background noise and room echo, and its emotion comes from the reference clip, since it has no separate emotion control. A clean, short sample of 3 to 10 seconds works best. Longer clips do not produce a better clone.

Every one of these is fixable if you are comfortable in a terminal and willing to dig through error logs. In the desktop app you don't hit them at all, because the versions it ships already work together.

The manual route, in brief

If you want to run the open-source model yourself, you will be working out what to install, where to get it, and which versions fit your machine, then troubleshooting whatever breaks. Here is the outline. We point to the official source for the exact commands, since install steps and version requirements change with each release.

Hardware. A Windows or Linux PC with an NVIDIA GPU. OmniVoice is light for a cloning model: around 4 GB of video memory is enough to run it, and more memory means faster, smoother generation. Plan on 8 GB or more of system RAM and a few gigabytes of disk space for the model weights.

The general shape of the process:

1. Install Python and create a separate virtual environment for OmniVoice.
2. Install a GPU-enabled PyTorch build that matches your NVIDIA driver's CUDA version.
3. Install OmniVoice and let it download the model weights on first run.
4. Launch the included browser demo, or call the model from a Python script, then clone or design voices from there.

Where to get the exact steps: the official OmniVoice model page on Hugging Face, OmniVoice on Hugging Face, published by the k2-fsa team. Follow its instructions for current versions and commands, and check its license terms there before commercial use.

Who should run OmniVoice themselves

Running it yourself makes sense if you are comfortable with Python environments and the command line, and you want to script OmniVoice into your own pipeline or experiment with the raw model. The manual route needs an NVIDIA card.

The desktop app or Cloud is the better fit if you have a Mac, an AMD or Intel Arc card, or no graphics card at all, you want a graphical interface, you need numbers and dates read correctly, or you would rather spend the time producing audio than fixing CUDA errors.

If you need emotion you can dial in line by line rather than emotion copied from a reference clip, that is Qwen3-TTS, covered in How to Run Qwen3-TTS Locally. To see how the two compare on the same cloned voice, read Qwen3 vs OmniVoice vs Chatterbox, and for everything OmniVoice can do inside the app, see the OmniVoice model page.