Qwen Image Layered INT8 ConvRot for ComfyUI
This repository contains a stock-ComfyUI-native INT8 TensorWise + ConvRot
conversion of the official
qwen_image_layered_bf16.safetensors
checkpoint. It loads directly in ComfyUI 0.27.0 or newer; no quantization
custom node is required.
File
| File | Size | SHA-256 |
|---|---|---|
qwen_image_layered_int8convrot.safetensors |
20,555,647,784 bytes | 34e45a22c895cd15877838909f8f6b98a8ee1a6258d7967f584b860a7b8c7c27 |
The checkpoint contains 839 INT8 weights, 839 FP32 per-output-channel scales, 839 ConvRot metadata tensors, and 1,095 retained BF16 tensors. Every selected weight was rotated with regular-Hadamard groups of 256 before quantization.
Requirements
- ComfyUI >= 0.27.0
comfy-kitchen>= 0.2.15- NVIDIA GPU with compute capability 7.5 or newer for the optimized TensorWise INT8 kernels
Install this file in ComfyUI/models/diffusion_models/. The standard
Qwen Image Layered workflow also needs:
Select qwen_image_layered_int8convrot.safetensors in the workflow's Load
Diffusion Model node.
Conversion provenance
- Base model:
Qwen/Qwen-Image-Layered, revision8f0ca708dfff6ba1dd5f2d85d78f8c108a040bcf - ComfyUI source checkpoint:
Comfy-Org/Qwen-Image-Layered_ComfyUI, revision5d93d59c0e34488b94dee03ad33337f7ee997f97 - Converter:
Comfy-Org/comfy-quants, revision1e0d481f24847c4914578f5468917902ad53ea46 - Recipe:
qwen_image_layered_int8_tensorwise.yaml
comfy-quants export-model-int8-tensorwise \
--config configs/qwen_image_layered_int8_tensorwise.yaml \
--source qwen_image_layered_bf16.safetensors \
--out qwen_image_layered_int8convrot.safetensors \
--device cuda:0 \
--convrot \
--convrot-groupsize 256 \
--hash-output
Validation
The safetensors contract and checksum were verified after export. The checkpoint
was then loaded by stock ComfyUI, which detected all 839 INT8 weights, and the
official image_qwen_image_layered workflow completed with a local 640-pixel
input on an RTX A5000. The smoke test produced three non-empty 640x608 RGBA
layers.
This conversion retains the upstream Apache-2.0 license.