diff --git a/backends/mediatek/partitioner.py b/backends/mediatek/partitioner.py
index 056336d606..b9e342e937 100644
--- a/backends/mediatek/partitioner.py
+++ b/backends/mediatek/partitioner.py
@@ -44,6 +44,11 @@ def is_node_supported(self, _, node: torch.fx.Node) -> bool:
             return False
 
         op_type = node.target.__name__
+
+        # Skip until we can handle the dimension order representation
+        if op_type == "aten._to_copy.default":
+            return False
+
         if op_type in self._op_types_to_skip or node.name in self._op_names_to_skip:
             print(
                 f"[Neuropilot Backend] The {op_type} operator with name '{node.name}' is skipped."
diff --git a/backends/mediatek/preprocess.py b/backends/mediatek/preprocess.py
index 92a1e196ad..3ec8c87e08 100644
--- a/backends/mediatek/preprocess.py
+++ b/backends/mediatek/preprocess.py
@@ -22,6 +22,23 @@
 SKIP_COMPILE_SPEC_KEYS = {"ImportForever"}
 
 
+def assert_default_dim_order(edge_graph_module: torch.fx.GraphModule) -> None:
+    for node in edge_graph_module.graph.nodes:
+        if node.op != "placeholder":
+            continue
+
+        # We expect the default dim order for all tensor-like inputs i.e. inputs, buffers, and params
+        t = node.meta.get("val", None)
+        if t is not None and getattr(t, "dim_order", None) is not None:
+            default_dim_order = tuple(range(t.dim()))
+            if t.dim_order() != default_dim_order:
+                raise RuntimeError(
+                    f"Neuropilot backend only supports contiguous memory format for inputs."
+                    f"Expecting dim_order: {default_dim_order}, but got "
+                    f"{node.meta['val'].dim_order()} for a placeholder node {node}."
+                )
+
+
 @final
 class NeuropilotBackend(BackendDetails):
 
@@ -30,6 +47,9 @@ def preprocess(
         cls, edge_program: ExportedProgram, module_compile_spec: List[CompileSpec]
     ) -> PreprocessResult:
 
+        # Make sure all inputs are contiguous_format or NCHW or default dim order
+        assert_default_dim_order(edge_program.graph_module)
+
         name_to_node_mappings = {node.name: node for node in edge_program.graph.nodes}
         input_names = edge_program.graph_signature.user_inputs
         output_names = edge_program.graph_signature.user_outputs
diff --git a/backends/mediatek/runtime/NeuronBackend.cpp b/backends/mediatek/runtime/NeuronBackend.cpp
index 342534474d..fa3d0d9dc6 100644
--- a/backends/mediatek/runtime/NeuronBackend.cpp
+++ b/backends/mediatek/runtime/NeuronBackend.cpp
@@ -13,6 +13,7 @@
 #include "api/NeuronAdapter.h"
 
 #include "executorch/runtime/core/error.h"
+#include "executorch/runtime/core/exec_aten/util/dim_order_util.h"
 
 #include <algorithm>
 #include <memory>
@@ -111,6 +112,14 @@ Error NeuronExecuTorchDelegate::execute(
   size_t inputCount = mInputSizes.size(), outputCount = mOutputSizes.size();
 
   for (int i = 0; i < inputCount; i++) {
+    auto tensor_in = args[i]->toTensor();
+    ET_CHECK_OR_RETURN_ERROR(
+        runtime::is_contiguous_dim_order(
+            tensor_in.dim_order().data(), tensor_in.dim()),
+        Internal,
+        "Expecting default dim_order but got a non default dim_order tensor for external input %u",
+        i);
+
     auto data_ptr = args[i]->toTensor().data_ptr();
     auto data_size = args[i]->toTensor().nbytes();
     if (IsCached</*isInput=*/true>(i, data_ptr)) {