SamplerSASolver - ComfyUI Built-in Node Documentation

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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	Data Type	Required	Range	Description
`model`	MODEL	Yes	-	The diffusion model to use for sampling
`eta`	FLOAT	Yes	0.0 - 10.0	Controls the step size scaling factor (default: 1.0)
`sde_start_percent`	FLOAT	Yes	0.0 - 1.0	The starting percentage for SDE sampling (default: 0.2)
`sde_end_percent`	FLOAT	Yes	0.0 - 1.0	The ending percentage for SDE sampling (default: 0.8)
`s_noise`	FLOAT	Yes	0.0 - 100.0	Controls the amount of noise added during sampling (default: 1.0)
`predictor_order`	INT	Yes	1 - 6	The order of the predictor component in the solver (default: 3)
`corrector_order`	INT	Yes	0 - 6	The order of the corrector component in the solver (default: 4)
`use_pece`	BOOLEAN	Yes	-	Enables or disables the PECE (Predict-Evaluate-Correct-Evaluate) method
`simple_order_2`	BOOLEAN	Yes	-	Enables or disables simplified second-order calculations

Outputs

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

SamplerLMS - ComfyUI Built-in Node Documentation

SamplerSEEDS2 - ComfyUI Built-in Node Documentation

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Inputs

Outputs