diff --git a/tensordict/utils.py b/tensordict/utils.py
index ea8bba786..e43e4e8fd 100644
--- a/tensordict/utils.py
+++ b/tensordict/utils.py
@@ -1499,6 +1499,7 @@ def assert_close(
     equal_nan: bool = True,
     intersection: bool = False,
     msg: str = "",
+    prefix: NestedKey = (),
 ) -> bool:
     """Asserts that two tensordicts, `actual` and `expected`, are element-wise equal within a tolerance for all entries.
 
@@ -1516,6 +1517,7 @@ def assert_close(
         intersection (bool, optional): If True, only the intersection of the two tensordicts will be compared.
             Default is ``False``.
         msg (str, optional): An optional message to include in the assertion error if the check fails.
+        prefix (NestedKey, optional): a prefix to add to the key for error messages.
 
     Returns:
         bool: True if the tensors are close within the specified tolerances, raise an exception otherwise.
@@ -1547,6 +1549,7 @@ def assert_close(
                 msg=msg,
                 intersection=intersection,
                 equal_nan=equal_nan,
+                prefix=prefix,
             )
         return True
 
@@ -1581,22 +1584,31 @@ def assert_close(
                 msg=msg,
                 intersection=intersection,
                 equal_nan=equal_nan,
+                prefix=prefix + (key,),
             )
             continue
         elif not isinstance(input1, torch.Tensor):
             continue
-        if input1.is_nested:
-            input1v = input1.values()
-            input2v = input2.values()
-            mse = (input1v.to(torch.float) - input2v.to(torch.float)).pow(2).sum()
-            input1o = input1.offsets()
-            input2o = input2.offsets()
-            mse = mse + (input1o.to(torch.float) - input2o.to(torch.float)).pow(2).sum()
-        else:
-            mse = (input1.to(torch.float) - input2.to(torch.float)).pow(2).sum()
+        try:
+            if input1.is_nested:
+                input1v = input1.values()
+                input2v = input2.values()
+                mse = (input1v.to(torch.float) - input2v.to(torch.float)).pow(2).sum()
+                input1o = input1.offsets()
+                input2o = input2.offsets()
+                mse = (
+                    mse
+                    + (input1o.to(torch.float) - input2o.to(torch.float)).pow(2).sum()
+                )
+            else:
+                mse = (input1.to(torch.float) - input2.to(torch.float)).pow(2).sum()
+        except Exception as err:
+            raise RuntimeError(
+                f"Failed to compare key {prefix + (key,)}. Scroll up for more details."
+            ) from err
         mse = mse.div(input1.numel()).sqrt().item()
 
-        local_msg = f"key {key} does not match, got mse = {mse:4.4f}"
+        local_msg = f"key {prefix + (key,)} does not match, got mse = {mse:4.4f}"
         new_msg = ",\t".join([local_msg, msg]) if len(msg) else local_msg
         if input1.is_nested:
             torch.testing.assert_close(
@@ -1611,7 +1623,7 @@ def assert_close(
             torch.testing.assert_close(
                 input1, input2, rtol=rtol, atol=atol, equal_nan=equal_nan, msg=new_msg
             )
-        local_msg = f"key {key} matches"
+        local_msg = f"key {prefix + (key,)} matches"
         msg = "\t".join([local_msg, msg]) if len(msg) else local_msg
 
     return True