LocalClaw/TTS/TADA
Local TTS model

TADA

LLM-based TTS built on Llama with a fully integrated audio tokenizer and decoder. Available in 1B (English) and 3B multilingual variants. Open-source weights on HuggingFace. Developed by Hume AI, specialists in expressive, emotion-aware voice.

Apple Silicon ready text-to-speech generation 8 languages Apache 2.0
Compare TTS models Open source page
Quality
9.1/10
Speed
7.5/10
Model size
2 GB
Voices
Multiple + expressive control

Can TADA run locally?

TADA can generate speech locally for private voice workflows. Start with pip install hume.

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

pip install hume Upstream source
multilingualemotionstreaming

Audio profile

Quality
9.1
Speed
7.5
Local
8.6

Best fit

TADA is best for multilingual local speech generation.

Hardware: gpuapple

Model details

Type
Local TTS model
Family
tada
Latency
low
Formats
pytorchsafetensors
Languages
en, fr, de, es, it, pt, zh, ja
Context
Llama architecture, audio tokenizer + decoder

Install locally

01
Check runtimeConfirm the backend supports pytorch, safetensors 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 hume

Good for

  • text-to-speech generation
  • Apple Silicon ready local workflows
  • multilingual, emotion, streaming

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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