diff --git a/tests/ttnn/unit_tests/operations/test_new_conv2d.py b/tests/ttnn/unit_tests/operations/test_new_conv2d.py
index aca2169ac22..6f8c395b421 100644
--- a/tests/ttnn/unit_tests/operations/test_new_conv2d.py
+++ b/tests/ttnn/unit_tests/operations/test_new_conv2d.py
@@ -322,7 +322,11 @@ def run_conv_with_split(
 @pytest.mark.parametrize("stride", [1])
 @pytest.mark.parametrize(
     "output_channels, input_channels, input_height, input_width, filter_height, filter_width, pad_h, pad_w, act_block_w_div",
-    ((64, 32, 130, 130, 3, 3, 0, 0, 1),),
+    (
+        (64, 32, 130, 130, 3, 3, 0, 0, 1),
+        (64, 32, 128, 128, 3, 3, 1, 1, 1),
+        (64, 32, 1024, 1024, 3, 3, 1, 1, 1),
+    ),
 )
 @pytest.mark.parametrize(
     "has_bias",
@@ -424,6 +428,7 @@ def test_conv_dram(
         reshard_if_not_optimal=True,
         act_block_w_div=act_block_w_div,
         output_height_in_l1=64,
+        act_block_h_override=64,
     )
     [tt_output_tensor_on_device, out_height, out_width, weights_device, bias_device] = ttnn.conv2d(
         input_tensor=tt_input_tensor,
diff --git a/ttnn/cpp/ttnn/operations/conv/conv2d/conv2d.cpp b/ttnn/cpp/ttnn/operations/conv/conv2d/conv2d.cpp
index e437354e1ed..9bffd08f23a 100644
--- a/ttnn/cpp/ttnn/operations/conv/conv2d/conv2d.cpp
+++ b/ttnn/cpp/ttnn/operations/conv/conv2d/conv2d.cpp
@@ -725,13 +725,13 @@ std::tuple<ttnn::Tensor, uint32_t, uint32_t, ttnn::Tensor, std::optional<ttnn::T
                             std::array<uint32_t, 4>{1, 1, 1, 1} //Step
                             );
                         log_debug(tt::LogOp, "Sliced input tensor shape: {}", sliced_input_tensor.get_shape());
-                        if(pad_top>0)
+                        if(pad_top>0 || pad_bottom > 0)
                         {
                             auto pad_top_tensor = ttnn::pad(
+                                DefaultQueueId,
                                 sliced_input_tensor,
-                                tt::tt_metal::Array4D({1, input_slice_height + pad_top, input_width, in_channels}),
-                                tt::tt_metal::Array4D({0, 0, 0, 0}),
-                                0);
+                                std::vector<std::pair<uint32_t, uint32_t>>{{0, 0}, {pad_top, pad_bottom}, {0, 0}, {0, 0}},
+                                0, true, std::nullopt);
                             sliced_input_tensor = pad_top_tensor;
                         }
                         log_debug(tt::LogOp, "Padded sliced input tensor shape: {}", sliced_input_tensor.get_shape());
@@ -745,7 +745,7 @@ std::tuple<ttnn::Tensor, uint32_t, uint32_t, ttnn::Tensor, std::optional<ttnn::T
                             device,
                             in_channels,
                             out_channels,
-                            1, input_slice_height + pad_top, input_width,
+                            1, input_slice_height + pad_top + pad_bottom, input_width,
                             kernel_size, stride, {0,padding[1]}, dilation,
                             groups,
                             first_run ?  bias_tensor : (std::optional<const ttnn::Tensor>)(bias_tensor_on_device),