Local TTS model

OuteTTS

Pure language model approach to TTS - no separate audio encoder. Runs via llama.cpp for fully local GGUF inference. Excellent for CPU-only setups.

Edge ready text-to-speech generation 4 languages MIT
Quality
8.7/10
Speed
8.5/10
Model size
0.9 GB
Voices
Built-in + reference cloning

Can OuteTTS run locally?

OuteTTS can generate speech locally for private voice workflows. Start with pip install outetts.

MIT license. Still verify upstream usage notes before shipping.

realtimelow-latencycloning

Audio profile

Quality
8.7
Speed
8.5
Local
8.8

Best fit

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

Hardware: cpugpuappleedge

Model details

Type
Local TTS model
Family
outetts
Latency
low
Formats
ggufpytorch
Languages
en, ja, ko, zh
Context
llama.cpp compatible

Install locally

01
Check runtimeConfirm the backend supports gguf, pytorch on your machine.
02
Install modelUse the upstream command or repository instructions.
03
Test locallyRun a short private audio prompt before moving into production workflows.
pip install outetts

Good for

  • text-to-speech generation
  • Edge ready local workflows
  • realtime, low-latency, cloning

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.

Related TTS and speech models

CompareBrowse all TTS models Local AIBrowse LLM models macOS appGet LocalClaw