ModelSamplingFlux now takes a resolution and adjusts the shift with it.

If you want to sample Flux dev exactly how the reference code does use
the same resolution as your image in this node.

comfy_extras/nodes_model_advanced.py

@@ -2,6 +2,7 @@
 import comfy.sd
 import comfy.model_sampling
 import comfy.latent_formats
+import nodes
 import torch
 
 class LCM(comfy.model_sampling.EPS):
@@ -174,17 +175,26 @@ class ModelSamplingFlux:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": { "model": ("MODEL",),
-                              "shift": ("FLOAT", {"default": 1.15, "min": 0.0, "max": 100.0, "step":0.01}),
+                              "max_shift": ("FLOAT", {"default": 1.15, "min": 0.0, "max": 100.0, "step":0.01}),
+                              "base_shift": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 100.0, "step":0.01}),
+                              "width": ("INT", {"default": 1024, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 8}),
+                              "height": ("INT", {"default": 1024, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 8}),
                               }}
 
     RETURN_TYPES = ("MODEL",)
     FUNCTION = "patch"
 
     CATEGORY = "advanced/model"
 
-    def patch(self, model, shift):
+    def patch(self, model, max_shift, base_shift, width, height):
         m = model.clone()
 
+        x1 = 256
+        x2 = 4096
+        mm = (max_shift - base_shift) / (x2 - x1)
+        b = base_shift - mm * x1
+        shift = (width * height / (8 * 8 * 2 * 2)) * mm + b
+
         sampling_base = comfy.model_sampling.ModelSamplingFlux
         sampling_type = comfy.model_sampling.CONST