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LeeAeron/VibeVoice-Large-Q8
VibeVoice-Large-Q8 is a text-to-audio model from LeeAeron. Use it for the text-to-audio task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
Downloads · 30 days
5
5% of all-time downloads
All-time downloads
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.safetensors11.6 GB · 100%
How the weights are stored.
I87.1B · 76%
From the Hugging Face model README
The first 8-bit VibeVoice model that actually works
</div>If you've tried other 8-bit quantized VibeVoice models, you probably got nothing but static noise. This one actually works.
The secret? Selective quantization: I only quantized the language model (the most robust part), while keeping audio-critical components (diffusion head, VAE, connectors) at full precision.
Most 8-bit models you'll find online quantize everything aggressively: Result: Audio components get quantized → numerical errors propagate → audio = pure noise.
I only quantized what can be safely quantized without losing quality.
Result: 52% of parameters quantized, 48% at full precision = perfect audio quality.
| Model | Size | Audio Quality | Status |
|---|---|---|---|
| Original VibeVoice | 18.7 GB | ⭐⭐⭐⭐⭐ | Full precision |
| Other 8-bit models | 10.6 GB | 💥 NOISE | ❌ Don't work |
| This model | 11.6 GB | ⭐⭐⭐⭐⭐ | ✅ Perfect |
+1.0 GB vs other 8-bit models = perfect audio instead of noise. Worth it.
from transformers import AutoModelForCausalLM, AutoProcessor
import torch
import scipy.io.wavfile as wavfile
# Load model
model = AutoModelForCausalLM.from_pretrained(
"FabioSarracino/VibeVoice-Large-Q8",
device_map="auto",
trust_remote_code=True,
torch_dtype=torch.bfloat16,
)
processor = AutoProcessor.from_pretrained(
"FabioSarracino/VibeVoice-Large-Q8",
trust_remote_code=True
)
# Generate audio
text = "Hello, this is VibeVoice speaking."
inputs = processor(text, return_tensors="pt").to(model.device)
output = model.generate(**inputs, max_new_tokens=None)
# Save
audio = output.speech_outputs[0].cpu().numpy()
wavfile.write("output.wav", 24000, audio)
Install the custom node:
cd ComfyUI/custom_nodes
git clone https://github.com/Enemyx-net/VibeVoice-ComfyUI
Download this model to ComfyUI/models/vibevoice/
Restart ComfyUI and use it normally!
⚠️ Not supported: CPU, Apple Silicon (MPS), AMD GPUs
transformers>=4.51.3bitsandbytes>=0.43.0device_map="auto"pip install bitsandbytes>=0.43.0
This shouldn't happen! If it does:
pip install --upgrade transformerstorch.cuda.is_available() should return True@misc{vibevoice-q8-2025,
title={VibeVoice-Large-Q8: Selective 8-bit Quantization for Audio Quality},
author={Fabio Sarracino},
year={2025},
url={https://huggingface.co/FabioSarracino/VibeVoice-Large-Q8}
}
@misc{vibevoice2024,
title={VibeVoice: High-Quality Text-to-Speech with Large Language Models},
author={Microsoft Research},
year={2024},
url={https://github.com/microsoft/VibeVoice}
}
MIT License.
If this model helped you, leave a ⭐ on GitHub!
Created by Fabio Sarracino
The first 8-bit VibeVoice model that actually works
</div>