RenormCFG - ComfyUI Built-in Node Documentation

The RenormCFG node modifies the classifier-free guidance (CFG) process in diffusion models by applying conditional scaling and normalization. It adjusts the denoising process based on specified timestep thresholds and renormalization factors to control the influence of conditional versus unconditional predictions during image generation.

Inputs

Parameter	Description	Data Type	Required	Range
`model`	The diffusion model to apply renormalized CFG to	MODEL	Yes	-
`cfg_trunc`	Timestep threshold for applying CFG scaling. When the current timestep is below this value, CFG scaling is applied; otherwise, only the conditional prediction is used (default: 100.0)	FLOAT	No	0.0 - 100.0
`renorm_cfg`	Renormalization factor that limits the maximum norm of the CFG-scaled prediction relative to the original conditional prediction. A value of 0.0 disables renormalization (default: 1.0)	FLOAT	No	0.0 - 100.0

Outputs

Output Name	Description	Data Type
`model`	The modified model with renormalized CFG function applied	MODEL

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