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Wildminder/VibeVoice-Quants
VibeVoice-Quants is a machine learning model from Wildminder. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
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.safetensors40.5 GB · 93%
From the Hugging Face model README

Quantized VibeVoice checkpoints for the ComfyUI-VibeVoice node pack.
<a href="https://github.com/wildminder/ComfyUI-VibeVoice">Node repository</a> · <a href="https://github.com/wildminder/ComfyUI-VibeVoice/blob/main/README.md">Documentation</a> · <a href="https://github.com/wildminder/ComfyUI-VibeVoice/issues">Report an issue</a>
</div><p id="files" align="center">◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆</p>[!NOTE] These files are optional. The node downloads the official full-precision models on first run; point
Load VibeVoice Modelat a file from this repo to run quantized weights instead. No sidecar configs are needed — the node ships its own for every family here.
| Format | Storage | Notes |
|---|---|---|
| bf16 | full precision | Reference quality; matches the official checkpoints. |
| fp8 | 8-bit float, per-block scales | ~1.9× smaller than bf16; weights stay packed in memory at run time. |
| int8 | 8-bit integer, rowwise/blockwise | The convrot variant stores rotated weights; simple-heur is blockwise. |
| GGUF | q8_0, llama.cpp-style | Single file; needs the gguf package (pip install gguf). |
Quantization metadata is embedded in each checkpoint, so the node detects the format and the architecture from the file itself — no manual setup.
<p id="usage" align="center">◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆◇◆</p>ComfyUI/models/diffusion_models/.Load VibeVoice Model → external_model on the TTS or ASR node —
connected, it overrides the standard model_name dropdown.config_name on Auto-detect.Full setup, node inputs and VRAM notes in the node documentation.
MIT, matching the base models. VibeVoice is Microsoft's.