diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py
index 2bdf7a55c6..f4bb1a4aff 100644
--- a/invokeai/app/invocations/denoise_latents.py
+++ b/invokeai/app/invocations/denoise_latents.py
@@ -663,27 +663,27 @@ class DenoiseLatentsInvocation(BaseInvocation):
     def prepare_noise_and_latents(
         context: InvocationContext, noise_field: LatentsField | None, latents_field: LatentsField | None
     ) -> Tuple[float, torch.Tensor | None, torch.Tensor]:
-        seed = None
         noise = None
-
         if noise_field is not None:
             noise = context.tensors.load(noise_field.latents_name)
-            seed = noise_field.seed
 
         if latents_field is not None:
             latents = context.tensors.load(latents_field.latents_name)
-            if seed is None:
-                seed = latents_field.seed
-
-            if noise is not None and noise.shape[1:] != latents.shape[1:]:
-                raise Exception(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}")
-
         elif noise is not None:
             latents = torch.zeros_like(noise)
         else:
-            raise Exception("'latents' or 'noise' must be provided!")
+            raise ValueError("'latents' or 'noise' must be provided!")
 
-        if seed is None:
+        if noise is not None and noise.shape[1:] != latents.shape[1:]:
+            raise ValueError(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}")
+
+        # The seed comes from (in order of priority): the noise field, the latents field, or 0.
+        seed = 0
+        if noise_field is not None and noise_field.seed is not None:
+            seed = noise_field.seed
+        elif latents_field is not None and latents_field.seed is not None:
+            seed = latents_field.seed
+        else:
             seed = 0
 
         return seed, noise, latents