Local TTS model

OmniVoice

Catalogue summary: Massively multilingual zero-shot TTS model built on a diffusion language-model style architecture. It supports voice cloning from a short reference clip, prompt-based voice design and local CUDA, Apple Silicon MPS and Intel XPU inference through the official Python package.

Repository editorial metadata; verify comparative claims in the linked upstream material.

GPU recommendedtext-to-speech generation600 languagesCC-BY-NC pretrained model / Apache 2.0 code
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Catalogue quality
9.1/10
Catalogue speed
9/10
Model size
Qwen3-0.6B base plus 2.45GB model and 806MB audio tokenizer safetensors
Voices
Zero-shot voice cloning, saved clone prompts and text-described voice design

Can OmniVoice run locally?

OmniVoice can generate speech locally for private voice workflows. Use the verified setup options on this page; no terminal command is required to choose the right path.

CC-BY-NC pretrained model / Apache 2.0 code license. Review upstream restrictions before commercial use.

cloningmultilingualcontrollablerealtime

Audio profile

Cat. quality
9.1
Cat. speed
9
Audio
9.1

Best fit

OmniVoice is best for local voice cloning and expressive speech generation.

Hardware: gpuapple

Model details

Type
Local TTS model
Family
omnivoice
Latency
low
Formats
pytorchsafetensors
Languages
multilingual
Context
600+ languages, RTF as low as 0.025, local web UI via omnivoice-demo, pretrained weights are CC-BY-NC

Install locally

01
Check runtimeConfirm the backend supports pytorch, safetensors on your machine.
02
Open recommended setupUse the app and model links above. LocalClaw does not expose a terminal command.
03
Test locallyRun a short private audio prompt before moving into production workflows.

Good for

  • text-to-speech generation
  • GPU recommended local workflows
  • cloning, multilingual, controllable

Watch before shipping

  • Validate pronunciation, latency and artifacts with your own voice samples.
  • Review the upstream license and acceptable-use notes.
  • Benchmark on your target CPU, Apple Silicon or GPU setup.

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