ReferenceMultiLatent - ComfyUI Built-in Node Documentation

This node encodes one or more reference images and appends their latents to the conditioning that an edit model consumes.

This node encodes one or more reference images and appends their latents to the conditioning that an edit model consumes. It is the multi-image counterpart of Set Reference Latent: you connect a VAE plus a set of reference images, and the node attaches every encoded latent to the positive conditioning and, when one is connected, to the negative conditioning as well. Use it when a model expects several reference images at once instead of a single latent.

Inputs

Common Inputs

Parameter	Description	Data Type	Required	Range
positive	The positive conditioning to modify with the reference latents.	CONDITIONING	Yes	-
negative	Optional negative conditioning that receives the same reference latents. Leave it unconnected to reuse the modified positive conditioning on the negative output.	CONDITIONING	No	-
vae	The VAE used to encode the connected reference images. Required whenever at least one image is connected, otherwise the node raises an error.	VAE	No	-
resolution	How each reference image is prepared before encoding. "keep resolution" encodes it at its incoming size; "resize" scales it to a target megapixel count while preserving the aspect ratio, which reveals megapixels. (default: “keep resolution”)	DYNAMIC_COMBO	Yes	"keep resolution" "resize"
images	Growable slot: connect one or more reference images (image_1, image_2, …) to use as references. Images are encoded in slot order and appended to the conditioning in that order.	IMAGE	No	1 to 100

Resize Inputs

These options appear when resolution is set to "resize".

Parameter	Description	Data Type	Required	Range
megapixels	Target size of each reference image, preserving aspect ratio. 1.0 is about 1024 x 1024 pixels. (default: 1.0)	FLOAT	Yes	0.01 to 16.0

Outputs

Output Name	Description	Data Type
positive	The positive conditioning with the encoded reference latents appended.	CONDITIONING
negative	The negative conditioning with the same reference latents appended. Returns the positive output when no negative conditioning is connected.	CONDITIONING
empty_latent	The first reference latent multiplied by 0.0, ready to seed a sampler. Empty when no reference image is connected.	LATENT

Notes

• The latents are appended rather than replaced, so chaining several Set Reference Multi Latent nodes accumulates references.
• Each connected image is encoded on its own, so the reference images do not have to share a size.
• Without any connected image, positive and negative are returned unchanged and empty_latent is empty.

This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHub

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