echo-tts-gguf

Echo-TTS GGUF + ONNX

Converted model files for the Echo-TTS C++ inference engine.

This repo contains:

• echo-dit.gguf - EchoDiT diffusion transformer weights (F16 GGUF, best quality)
• echo-dit-q8.gguf - EchoDiT diffusion transformer weights (Q8_0 GGUF, near-lossless, lower VRAM)
• onnx/ - S1-DAC autoencoder (ONNX format) for audio encoding/decoding

Converted from Echo-TTS by Jordan Darefsky.

Download

# F16 GGUF model (5.6 GB) — best quality
huggingface-cli download tmdarkbr/echo-tts-gguf echo-dit.gguf --local-dir .

# Q8_0 GGUF model (3.3 GB) — near-lossless, lower VRAM
huggingface-cli download tmdarkbr/echo-tts-gguf echo-dit-q8.gguf --local-dir .

# ONNX DAC models
huggingface-cli download tmdarkbr/echo-tts-gguf onnx/ --local-dir onnx_models

Usage

echo-tts \
  --model echo-dit.gguf \
  --speaker speaker.wav \
  --dac-encoder onnx_models/dac_encoder.onnx \
  --dac-decoder onnx_models/dac_decoder.onnx \
  --text "[S1] Hello world." \
  --output output.wav

Use echo-dit-q8.gguf instead of echo-dit.gguf for lower VRAM usage with near-lossless quality.

Files

License

• Model weights: CC-BY-NC-SA-4.0 (same as original Echo-TTS)
• Audio outputs: CC-BY-NC-SA-4.0 (due to Fish Speech S1-DAC dependency)

Citation

@misc{darefsky2025echo,
    author = {Darefsky, Jordan},
    title = {Echo-TTS},
    year = {2025},
    url = {https://jordandarefsky.com/blog/2025/echo/}
}