UNetTemporalAttentionMultiply - ComfyUI Built-in Node Documentation

Complete documentation for the UNetTemporalAttentionMultiply node in ComfyUI. Learn its inputs, outputs, parameters and usage.

The UNetTemporalAttentionMultiply node applies multiplication factors to different types of attention mechanisms in a temporal UNet model. It modifies the model by adjusting the weights of self-attention and cross-attention layers, distinguishing between structural and temporal components. This allows fine-tuning of how much influence each attention type has on the model’s output.

Inputs

Parameter	Description	Data Type	Required	Range
model	The input model to modify with attention multipliers	MODEL	Yes	-
self_structural	Multiplier for self-attention structural components (default: 1.0)	FLOAT	No	0.0 - 10.0
self_temporal	Multiplier for self-attention temporal components (default: 1.0)	FLOAT	No	0.0 - 10.0
cross_structural	Multiplier for cross-attention structural components (default: 1.0)	FLOAT	No	0.0 - 10.0
cross_temporal	Multiplier for cross-attention temporal components (default: 1.0)	FLOAT	No	0.0 - 10.0

Outputs

Output Name	Description	Data Type
model	The modified model with adjusted attention weights	MODEL

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