diff --git a/tests/ttnn/unit_tests/operations/test_new_conv2d.py b/tests/ttnn/unit_tests/operations/test_new_conv2d.py
index 05d477aae6f1..5e20f2bf371b 100644
--- a/tests/ttnn/unit_tests/operations/test_new_conv2d.py
+++ b/tests/ttnn/unit_tests/operations/test_new_conv2d.py
@@ -789,7 +789,7 @@ def test_conv_for_segformer_512x512(
 )
 @pytest.mark.parametrize(
     "weights_dtype",
-    [ttnn.bfloat16, ttnn.bfloat8_b],
+    [ttnn.bfloat16],
 )
 @pytest.mark.parametrize(
     "activations_dtype",
@@ -1220,7 +1220,7 @@ def test_resnet50_conv_wh_fp32(
 )
 @pytest.mark.parametrize(
     "weights_dtype",
-    [ttnn.bfloat8_b],
+    [ttnn.bfloat16],
 )
 @pytest.mark.parametrize(
     "activations_dtype",
@@ -1503,7 +1503,7 @@ def test_sd_conv_wh(
 )
 @pytest.mark.parametrize(
     "weights_dtype",
-    [ttnn.bfloat8_b],
+    [ttnn.bfloat16],
 )
 @pytest.mark.parametrize(
     "activations_dtype",
@@ -1958,6 +1958,7 @@ def test_unet_conv_groups_8_wh(
     )
 
 
+@skip_for_grayskull()
 @pytest.mark.parametrize("device_params", [{"l1_small_size": 16384}], indirect=True)
 @pytest.mark.parametrize(
     "batch_size, output_channels, input_channels, input_height, input_width, filter_height, filter_width, stride_h, stride_w, pad_h, pad_w, config_override",
@@ -2019,6 +2020,7 @@ def test_halo_reshard_conv(
     )
 
 
+@skip_for_grayskull()
 @pytest.mark.skip("New API needs to be tested")
 @pytest.mark.parametrize("device_params", [{"l1_small_size": 16384}], indirect=True)
 @pytest.mark.parametrize(
@@ -2380,6 +2382,7 @@ def test_yolov4_conv_groups_larger_than_one(
     )
 
 
+@skip_for_grayskull()
 @pytest.mark.parametrize("device_params", [{"l1_small_size": 16384}], indirect=True)
 @pytest.mark.parametrize(
     " output_channels, input_channels, input_height, input_width, filter_height, filter_width, stride_h, stride_w, pad_h, pad_w, shard_layout, config_override, use_shallow_conv_variant, groups",
@@ -2630,7 +2633,7 @@ def test_conv_for_vanilla_unet(
 )
 @pytest.mark.parametrize(
     "weights_dtype",
-    [ttnn.bfloat8_b, ttnn.bfloat16],
+    [ttnn.bfloat16],
 )
 @pytest.mark.parametrize(
     "activations_dtype",
@@ -2870,6 +2873,7 @@ def test_shallow_conv_with_tiled_input(device):
 
 # Tests running conv2d which maps to matmul w/o sharding the input tensor.
 # Output tensor is in DRAM.
+@skip_for_grayskull()
 @pytest.mark.parametrize("device_params", [{"l1_small_size": 16384}], indirect=True)
 @pytest.mark.parametrize("tiled_input", [True, False])
 @pytest.mark.parametrize("input_on_device", [True, False])