LocalClaw/TTS/OuteTTS
Local TTS model

OuteTTS

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

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

Edge readytext-to-speech generation4 languagesMIT
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Open model filesRecommended verified starting pointOpen in UnslothLaunches Unsloth Desktop on this modelOpen Python packageVerified package page without exposing a commandOpen on Hugging FaceFiles, licence and model cardCheck my machineOptional: verify the fit with your saved hardware

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Catalogue quality
8.7/10
Catalogue 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. Use the verified setup options on this page; no terminal command is required to choose the right path.

MIT license. Still verify upstream usage notes before shipping.

Upstream source
realtimelow-latencycloning

Audio profile

Cat. quality
8.7
Cat. speed
8.5
Audio
8.6

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
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
  • 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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