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FartingBackwards/wan2.2-fun-vace-14B-int8-convrot
wan2.2-fun-vace-14B-int8-convrot is a machine learning model from FartingBackwards. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for wan2.2. The card lists the license as apache-2.0.
Converted from original BF16 weights (alibaba-pai/Wan2.2-VACE-Fun-A14B, via Comfy-Org repack) with silveroxides/converttoquant:
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Updated Jul 25, 2026
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From the Hugging Face model README
Converted from original BF16 weights (alibaba-pai/Wan2.2-VACE-Fun-A14B, via Comfy-Org repack) with silveroxides/convert_to_quant:
ctq -i <source>.safetensors -o <output>.safetensors \
--int8 --scaling_mode row --simple \
--convrot --convrot-group-size 256 \
--wan --exclude-layers "vace_blocks\.\d+\.(before|after)_proj" \
--comfy_quant --save-quant-metadata
VACE architecture adds 8 context blocks (vace_blocks.0–.7) that inject into the main transformer via before_proj (block 0 only) and after_proj (all 8 blocks). These are zero-initialized and only lightly adapter-tuned on a frozen base, so their weight magnitudes are much smaller than a normally-trained layer. Row-wise INT8 quantization at the same settings as the rest of the model risks burying that signal in quantization noise, silencing VACE conditioning while the base model still generates normally. These 9 tensors are excluded and kept at source precision; the rest of vace_blocks (attention/FFN/norms) is quantized the same as the base model.
Apache 2.0, inherited from the base weights (Alibaba PAI).