ModelMergeWAN2_1 - ComfyUI Built-in Node Documentation

Complete documentation for the ModelMergeWAN2_1 node in ComfyUI. Learn its inputs, outputs, parameters and usage.

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The ModelMergeWAN2_1 node merges two models by blending their components using weighted averages. It supports different model sizes including 1.3B models with 30 blocks and 14B models with 40 blocks, with special handling for image to video models that include an extra image embedding component. Each component of the models can be individually weighted to control the blending ratio between the two input models.

Inputs

Parameter	Data Type	Required	Range	Description
model1	MODEL	Yes	-	First model to merge
model2	MODEL	Yes	-	Second model to merge
patch_embedding.	FLOAT	Yes	0.0 - 1.0	Weight for patch embedding component (default: 1.0)
time_embedding.	FLOAT	Yes	0.0 - 1.0	Weight for time embedding component (default: 1.0)
time_projection.	FLOAT	Yes	0.0 - 1.0	Weight for time projection component (default: 1.0)
text_embedding.	FLOAT	Yes	0.0 - 1.0	Weight for text embedding component (default: 1.0)
img_emb.	FLOAT	Yes	0.0 - 1.0	Weight for image embedding component, used in image to video models (default: 1.0)
blocks.0.	FLOAT	Yes	0.0 - 1.0	Weight for block 0 (default: 1.0)
blocks.1.	FLOAT	Yes	0.0 - 1.0	Weight for block 1 (default: 1.0)
blocks.2.	FLOAT	Yes	0.0 - 1.0	Weight for block 2 (default: 1.0)
blocks.3.	FLOAT	Yes	0.0 - 1.0	Weight for block 3 (default: 1.0)
blocks.4.	FLOAT	Yes	0.0 - 1.0	Weight for block 4 (default: 1.0)
blocks.5.	FLOAT	Yes	0.0 - 1.0	Weight for block 5 (default: 1.0)
blocks.6.	FLOAT	Yes	0.0 - 1.0	Weight for block 6 (default: 1.0)
blocks.7.	FLOAT	Yes	0.0 - 1.0	Weight for block 7 (default: 1.0)
blocks.8.	FLOAT	Yes	0.0 - 1.0	Weight for block 8 (default: 1.0)
blocks.9.	FLOAT	Yes	0.0 - 1.0	Weight for block 9 (default: 1.0)
blocks.10.	FLOAT	Yes	0.0 - 1.0	Weight for block 10 (default: 1.0)
blocks.11.	FLOAT	Yes	0.0 - 1.0	Weight for block 11 (default: 1.0)
blocks.12.	FLOAT	Yes	0.0 - 1.0	Weight for block 12 (default: 1.0)
blocks.13.	FLOAT	Yes	0.0 - 1.0	Weight for block 13 (default: 1.0)
blocks.14.	FLOAT	Yes	0.0 - 1.0	Weight for block 14 (default: 1.0)
blocks.15.	FLOAT	Yes	0.0 - 1.0	Weight for block 15 (default: 1.0)
blocks.16.	FLOAT	Yes	0.0 - 1.0	Weight for block 16 (default: 1.0)
blocks.17.	FLOAT	Yes	0.0 - 1.0	Weight for block 17 (default: 1.0)
blocks.18.	FLOAT	Yes	0.0 - 1.0	Weight for block 18 (default: 1.0)
blocks.19.	FLOAT	Yes	0.0 - 1.0	Weight for block 19 (default: 1.0)
blocks.20.	FLOAT	Yes	0.0 - 1.0	Weight for block 20 (default: 1.0)
blocks.21.	FLOAT	Yes	0.0 - 1.0	Weight for block 21 (default: 1.0)
blocks.22.	FLOAT	Yes	0.0 - 1.0	Weight for block 22 (default: 1.0)
blocks.23.	FLOAT	Yes	0.0 - 1.0	Weight for block 23 (default: 1.0)
blocks.24.	FLOAT	Yes	0.0 - 1.0	Weight for block 24 (default: 1.0)
blocks.25.	FLOAT	Yes	0.0 - 1.0	Weight for block 25 (default: 1.0)
blocks.26.	FLOAT	Yes	0.0 - 1.0	Weight for block 26 (default: 1.0)
blocks.27.	FLOAT	Yes	0.0 - 1.0	Weight for block 27 (default: 1.0)
blocks.28.	FLOAT	Yes	0.0 - 1.0	Weight for block 28 (default: 1.0)
blocks.29.	FLOAT	Yes	0.0 - 1.0	Weight for block 29 (default: 1.0)
blocks.30.	FLOAT	Yes	0.0 - 1.0	Weight for block 30 (default: 1.0)
blocks.31.	FLOAT	Yes	0.0 - 1.0	Weight for block 31 (default: 1.0)
blocks.32.	FLOAT	Yes	0.0 - 1.0	Weight for block 32 (default: 1.0)
blocks.33.	FLOAT	Yes	0.0 - 1.0	Weight for block 33 (default: 1.0)
blocks.34.	FLOAT	Yes	0.0 - 1.0	Weight for block 34 (default: 1.0)
blocks.35.	FLOAT	Yes	0.0 - 1.0	Weight for block 35 (default: 1.0)
blocks.36.	FLOAT	Yes	0.0 - 1.0	Weight for block 36 (default: 1.0)
blocks.37.	FLOAT	Yes	0.0 - 1.0	Weight for block 37 (default: 1.0)
blocks.38.	FLOAT	Yes	0.0 - 1.0	Weight for block 38 (default: 1.0)
blocks.39.	FLOAT	Yes	0.0 - 1.0	Weight for block 39 (default: 1.0)
head.	FLOAT	Yes	0.0 - 1.0	Weight for head component (default: 1.0)

Note: All weight parameters use a range from 0.0 to 1.0 with 0.01 step increments. The node supports up to 40 blocks to accommodate different model sizes, where 1.3B models use 30 blocks and 14B models use 40 blocks. The img_emb. parameter is specifically for image to video models.

Outputs

Output Name	Data Type	Description
model	MODEL	The merged model combining components from both input models according to the specified weights