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.
pip install outetts
Upstream source
realtimelow-latencycloning
Audio profile
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.
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