HyperTile - ComfyUI Built-in Node Documentation

The HyperTile node applies a tiling technique to the attention mechanism in diffusion models to optimize memory usage during image generation. It divides the latent space into smaller tiles and processes them separately, then reassembles the results. This allows for working with larger image sizes without running out of memory.

Inputs

Parameter	Description	Data Type	Required	Range
`model`	The diffusion model to apply the HyperTile optimization to	MODEL	Yes	-
`tile_size`	The target tile size for processing (default: 256). The effective tile size is rounded down to a multiple of 8, with a minimum of 32.	INT	No	1 - 2048
`swap_size`	Controls how the tiles are rearranged during processing to improve efficiency (default: 2)	INT	No	1 - 128
`max_depth`	The maximum depth level (resolution scale) to apply tiling. A value of 0 applies tiling only at the highest resolution (default: 0)	INT	No	0 - 10
`scale_depth`	When enabled, the tile size is scaled proportionally at deeper depth levels. This can help maintain quality at lower resolutions (default: False)	BOOLEAN	No	True / False

Outputs

Output Name	Description	Data Type
`model`	The modified model with HyperTile optimization applied	MODEL

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Inputs

Outputs