diff --git a/pina/equation/equation.py b/pina/equation/equation.py
index 677b0e54a..057c6bcf5 100644
--- a/pina/equation/equation.py
+++ b/pina/equation/equation.py
@@ -1,7 +1,6 @@
 """Module for the Equation."""
 
 import inspect
-import torch
 from .equation_interface import EquationInterface
 
 
@@ -61,33 +60,3 @@ def residual(self, input_, output_, params_=None):
             f"Unexpected number of arguments in equation: {self.__len_sig}. "
             "Expected either 2 (direct problem) or 3 (inverse problem)."
         )
-
-    def to(self, device):
-        """
-        Move all tensor attributes of the Equation to the specified device.
-
-        :param torch.device device: The target device to move the tensors to.
-        :return: The Equation instance moved to the specified device.
-        :rtype: Equation
-        """
-        # Iterate over all attributes of the Equation
-        for key, val in self.__dict__.items():
-
-            # Move tensors in dictionaries to the specified device
-            if isinstance(val, dict):
-                self.__dict__[key] = {
-                    k: v.to(device) if torch.is_tensor(v) else v
-                    for k, v in val.items()
-                }
-
-            # Move tensors in lists to the specified device
-            elif isinstance(val, list):
-                self.__dict__[key] = [
-                    v.to(device) if torch.is_tensor(v) else v for v in val
-                ]
-
-            # Move tensor attributes to the specified device
-            elif torch.is_tensor(val):
-                self.__dict__[key] = val.to(device)
-
-        return self
diff --git a/pina/equation/equation_interface.py b/pina/equation/equation_interface.py
index f1cc74754..82b86dbd0 100644
--- a/pina/equation/equation_interface.py
+++ b/pina/equation/equation_interface.py
@@ -1,6 +1,7 @@
 """Module for the Equation Interface."""
 
 from abc import ABCMeta, abstractmethod
+import torch
 
 
 class EquationInterface(metaclass=ABCMeta):
@@ -33,3 +34,33 @@ def residual(self, input_, output_, params_):
         :return: The computed residual of the equation.
         :rtype: LabelTensor
         """
+
+    def to(self, device):
+        """
+        Move all tensor attributes to the specified device.
+
+        :param torch.device device: The target device to move the tensors to.
+        :return: The instance moved to the specified device.
+        :rtype: EquationInterface
+        """
+        # Iterate over all attributes of the Equation
+        for key, val in self.__dict__.items():
+
+            # Move tensors in dictionaries to the specified device
+            if isinstance(val, dict):
+                self.__dict__[key] = {
+                    k: v.to(device) if torch.is_tensor(v) else v
+                    for k, v in val.items()
+                }
+
+            # Move tensors in lists to the specified device
+            elif isinstance(val, list):
+                self.__dict__[key] = [
+                    v.to(device) if torch.is_tensor(v) else v for v in val
+                ]
+
+            # Move tensor attributes to the specified device
+            elif torch.is_tensor(val):
+                self.__dict__[key] = val.to(device)
+
+        return self
diff --git a/pina/equation/system_equation.py b/pina/equation/system_equation.py
index 21cb27160..3e8550d9b 100644
--- a/pina/equation/system_equation.py
+++ b/pina/equation/system_equation.py
@@ -101,6 +101,10 @@ def residual(self, input_, output_, params_=None):
         :return: The aggregated residuals of the system of equations.
         :rtype: LabelTensor
         """
+        # Move the equation to the input_ device
+        self.to(input_.device)
+
+        # Compute the residual for each equation
         residual = torch.hstack(
             [
                 equation.residual(input_, output_, params_)
@@ -108,6 +112,7 @@ def residual(self, input_, output_, params_=None):
             ]
         )
 
+        # Skip reduction if not specified
         if self.reduction is None:
             return residual