diff --git a/models/demos/resnet/tt/metalResnetBlock50.py b/models/demos/resnet/tt/metalResnetBlock50.py
index e5c21983e44..fa5a11b8c82 100644
--- a/models/demos/resnet/tt/metalResnetBlock50.py
+++ b/models/demos/resnet/tt/metalResnetBlock50.py
@@ -1465,7 +1465,7 @@ def __init__(
                 {
                     tt_lib.tensor.CoreRange(
                         tt_lib.tensor.CoreCoord(0, 0),
-                        tt_lib.tensor.CoreCoord(11, 7),
+                        tt_lib.tensor.CoreCoord(10, 7),
                     ),
                     tt_lib.tensor.CoreRange(
                         tt_lib.tensor.CoreCoord(0, 8),
@@ -1473,6 +1473,7 @@ def __init__(
                     ),
                 }
             )
+            self.n_fold_cores = 92
 
             self.shard_grid = tt_lib.tensor.CoreRangeSet(
                 {
@@ -2060,7 +2061,7 @@ def preprocessing_with_fold(self, x: torch.Tensor) -> tt_lib.tensor:
         NHW_even = _nearest_y(NHW // stride_h, self.first_conv_num_cores_nhw * 32)
 
         shard_spec = tt_lib.tensor.ShardSpec(
-            self.fold_grid, [NHW // 100, x.shape[3]], tt_lib.tensor.ShardOrientation.ROW_MAJOR, False
+            self.fold_grid, [NHW // self.n_fold_cores, x.shape[3]], tt_lib.tensor.ShardOrientation.ROW_MAJOR, False
         )
         x = torch2tt_tensor(
             x,
@@ -2076,25 +2077,25 @@ def preprocessing_with_fold(self, x: torch.Tensor) -> tt_lib.tensor:
         # fold for unity stride on device
         x = tt_lib.tensor.fold(x, stride_h=stride_h, stride_w=1)
 
-        # non-optimal resharding via the interleaved round trip, because
-        # direct resharding from 100 to 98 cores breaks the reshard op
-        x = tt_lib.tensor.sharded_to_interleaved(
+        shard_shape = [
+            NHW_even // self.first_conv_num_cores_nhw,
+            x.get_legacy_shape()[3],
+        ]
+
+        x = tt_lib.tensor.reshard(
             x,
-            output_mem_config=tt_lib.tensor.MemoryConfig(
-                tt_lib.tensor.TensorMemoryLayout.INTERLEAVED, tt_lib.tensor.BufferType.L1
+            tt_lib.tensor.MemoryConfig(
+                tt_lib.tensor.TensorMemoryLayout.HEIGHT_SHARDED,
+                tt_lib.tensor.BufferType.L1,
+                tt_lib.tensor.ShardSpec(
+                    self.shard_grid,
+                    shard_shape,
+                    tt_lib.tensor.ShardOrientation.ROW_MAJOR,
+                    False,
+                ),
             ),
         )
 
-        x = tt_lib.tensor.interleaved_to_sharded(
-            x,
-            self.shard_grid,
-            [
-                NHW_even // self.first_conv_num_cores_nhw,
-                x.get_legacy_shape()[3],
-            ],
-            tt_lib.tensor.TensorMemoryLayout.HEIGHT_SHARDED,
-            tt_lib.tensor.ShardOrientation.ROW_MAJOR,
-        )
         return x
 
     def forward(self, x: tt_lib.tensor) -> tt_lib.tensor: