SamplerSASolver - ComfyUI Built-in Node Documentation

The SamplerSASolver node implements a custom sampling algorithm for diffusion models. It uses a predictor-corrector approach with configurable order settings and stochastic differential equation (SDE) parameters to generate samples from the input model.

Inputs

Parameter	Description	Data Type	Required	Range
`model`	The diffusion model to use for sampling	MODEL	Yes	-
`eta`	Controls the step size scaling factor (default: 1.0)	FLOAT	No	0.0 - 10.0
`sde_start_percent`	The starting percentage for SDE sampling (default: 0.2)	FLOAT	No	0.0 - 1.0
`sde_end_percent`	The ending percentage for SDE sampling (default: 0.8)	FLOAT	No	0.0 - 1.0
`s_noise`	Controls the amount of noise added during sampling (default: 1.0)	FLOAT	No	0.0 - 100.0
`predictor_order`	The order of the predictor component in the solver (default: 3)	INT	No	1 - 6
`corrector_order`	The order of the corrector component in the solver (default: 4)	INT	No	0 - 6
`use_pece`	Enables or disables the PECE (Predict-Evaluate-Correct-Evaluate) method	BOOLEAN	No	-
`simple_order_2`	Enables or disables simplified second-order calculations	BOOLEAN	No	-

Outputs

Output Name	Description	Data Type
`sampler`	A configured sampler object that can be used with diffusion models	SAMPLER

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Inputs

Outputs