Local TTS model

MOSS-TTS-Nano

Catalogue summary: Tiny 0.1B multilingual speech generation model for CPU-friendly real-time TTS. Supports voice cloning, streaming, ONNX CPU inference and MLX Audio on Apple Silicon.

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

Edge readytext-to-speech generation20 languagesApache 2.0
Choose an app

Start with Recommended. No terminal commands are shown.

Compare speech models

Desktop app links require the app to be installed. If nothing opens, LocalClaw will show app-download and model-file fallbacks.

Catalogue quality
8.5/10
Catalogue speed
9.7/10
Model size
0.1 GB
Voices
Voice cloning + long-text chunked generation

Can MOSS-TTS-Nano run locally?

MOSS-TTS-Nano 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.

Apache 2.0 license. Still verify upstream usage notes before shipping.

cloningstreamingrealtimemultilinguallow-latency

Audio profile

Cat. quality
8.5
Cat. speed
9.7
Audio
8.9

Best fit

MOSS-TTS-Nano is best for local voice cloning and expressive speech generation.

Hardware: cpugpuappleedge

Model details

Type
Local TTS model
Family
moss
Latency
ultra-low
Formats
pytorchonnxmlx
Languages
zh, en, de, es, fr, ja, it, hu, ko, ru, fa, ar, pl, pt, cs, da, sv, el, tr
Context
0.1B params, 20 languages, ONNX CPU version runs smoothly on MacBook Air M4

Install locally

01
Check runtimeConfirm the backend supports pytorch, onnx, mlx 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
  • cloning, streaming, realtime

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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