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Sponsored by
YouArt
ApacheOne / sdxl_text_encoders-NVFP4
Model's Last Updated: April 21 2026
Introduction of sdxl_text_encoders-NVFP4
Model Details of sdxl_text_encoders-NVFP4
working in ComfyUI with sdxl models:
Just need the two safetensors model1 and model2. clip_g and clip_l for the common name from sdxl
Needs my custom loader here to work: https://github.com/Apache0ne/ComfyUI-SDXLNVFP4
Workflow in images, also I am using taesd vae for both.
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Hybrid-Sensitivity-Weighted-Quantization (HSWQ)
High-fidelity FP8 quantization for diffusion models (SDXL). HSWQ uses sensitivity and importance analysis instead of naive uniform cast, and offers two modes: standard-compatible (V1) and high-performance scaled (V2).
Technical details: md/HSWQ_ Hybrid Sensitivity Weighted Quantization.md
How to quantize: md/HSWQ_ How to quantize SDXL.md
SDXL Benchmark Test Results: md/SDXL Benchmark Test Results.md
Credit & Special Acknowledgement
https://github.com/ussoewwin/Hybrid-Sensitivity-Weighted-Quantization
https://github.com/tritant/ComfyUI_Kitchen_nvfp4_Converter
https://github.com/NVIDIA/Model-Optimizer
We extend our deepest respect and gratitude to the Nunchaku Team for their groundbreaking work on SVDQ quantization and for sharing their models with the community. This collection relies heavily on their research and original implementation.
- Original Repository: nunchaku-tech/nunchaku-sdxl
Runs of ApacheOne sdxl_text_encoders-NVFP4 on huggingface.co
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More Information About sdxl_text_encoders-NVFP4 huggingface.co Model
Url of sdxl_text_encoders-NVFP4
sdxl_text_encoders-NVFP4 huggingface.co Url
Provider of sdxl_text_encoders-NVFP4 huggingface.co
Other API from ApacheOne
Updated:August 13 2026
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