diff --git a/__init__.py b/__init__.py
index f47c110..bd82a69 100644
--- a/__init__.py
+++ b/__init__.py
@@ -45,6 +45,7 @@ NODE_CONFIG = {
     "GetImageRangeFromBatch": {"class": GetImageRangeFromBatch, "name": "Get Image Range From Batch"},
     "GetImageSizeAndCount": {"class": GetImageSizeAndCount, "name": "Get Image Size & Count"},
     "ImageAndMaskPreview": {"class": ImageAndMaskPreview},
+    "ImageAddMulti": {"class": ImageAddMulti, "name": "Image Add Multi"},
     "ImageBatchMulti": {"class": ImageBatchMulti, "name": "Image Batch Multi"},
     "ImageBatchRepeatInterleaving": {"class": ImageBatchRepeatInterleaving},
     "ImageBatchTestPattern": {"class": ImageBatchTestPattern, "name": "Image Batch Test Pattern"},
diff --git a/nodes/image_nodes.py b/nodes/image_nodes.py
index 2a089e1..ddc51d5 100644
--- a/nodes/image_nodes.py
+++ b/nodes/image_nodes.py
@@ -1134,6 +1134,50 @@ with the **inputcount** and clicking update.
         for c in range(1, inputcount):
             new_image = kwargs[f"image_{c + 1}"]
             image, = image_batch_node.batch(image, new_image)
+        return (image,)
+
+class ImageAddMulti:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "inputcount": ("INT", {"default": 2, "min": 2, "max": 1000, "step": 1}),
+                "image_1": ("IMAGE", ),
+                "image_2": ("IMAGE", ),
+                "blending": (
+                [   'add',
+                    'subtract',
+                    'multiply',
+                    'difference',
+                ],
+                {
+                "default": 'add'
+                }),
+            },
+    }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("images",)
+    FUNCTION = "add"
+    CATEGORY = "KJNodes/image"
+    DESCRIPTION = """
+Add blends multiple images together.    
+You can set how many inputs the node has,  
+with the **inputcount** and clicking update.
+"""
+
+    def add(self, inputcount, blending, **kwargs):
+        image = kwargs["image_1"]
+        for c in range(1, inputcount):
+            new_image = kwargs[f"image_{c + 1}"]
+            if blending == "add":
+                image = torch.add(image * 0.5, new_image * 0.5)
+            elif blending == "subtract":
+                image = torch.sub(image * 0.5, new_image * 0.5)
+            elif blending == "multiply":
+                image = torch.mul(image * 0.5, new_image * 0.5)
+            elif blending == "difference":
+                image = torch.sub(image, new_image)
         return (image,)    
 
 class PreviewAnimation:
diff --git a/web/js/jsnodes.js b/web/js/jsnodes.js
index b805706..c8fe533 100644
--- a/web/js/jsnodes.js
+++ b/web/js/jsnodes.js
@@ -30,6 +30,7 @@ app.registerExtension({
 				}
 				break;
 			case "ImageBatchMulti":
+			case "ImageAddMulti":
 				nodeType.prototype.onNodeCreated = function () {
 				this._type = "IMAGE"
 				this.inputs_offset = nodeData.name.includes("selective")?1:0