diff --git a/ngraph/frontend/onnx/frontend/src/op/com.microsoft/skip_layer_normalization.cpp b/ngraph/frontend/onnx/frontend/src/op/com.microsoft/skip_layer_normalization.cpp
new file mode 100644
index 00000000000..2b7641d242a
--- /dev/null
+++ b/ngraph/frontend/onnx/frontend/src/op/com.microsoft/skip_layer_normalization.cpp
@@ -0,0 +1,45 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "op/com.microsoft/skip_layer_normalization.hpp"
+
+#include "default_opset.hpp"
+
+namespace ngraph {
+namespace onnx_import {
+namespace op {
+namespace set_1 {
+OutputVector skip_layer_normalization(const Node& node) {
+    auto nodes = node.get_ng_inputs();
+    auto num_nodes = nodes.size();
+    NGRAPH_CHECK(num_nodes >= 3 && num_nodes <= 5,
+                 "SkipLayerNormalization takes 3, 4 or 5 inputs. Provided " + std::to_string(num_nodes));
+
+    // input + skip
+    std::shared_ptr<ngraph::Node> input = std::make_shared<default_opset::Add>(nodes[0], nodes[1]);
+    // add bias if available
+    if (num_nodes == 5) {
+        input = std::make_shared<default_opset::Add>(input, nodes[4]);
+    }
+    float eps = node.get_attribute_value<float>("epsilon");
+    // reduce over hidden_size
+    int hidden_size_dim = 2;
+    const auto reduction_axes = default_opset::Constant::create(element::i32, Shape{1}, {hidden_size_dim});
+    std::shared_ptr<ngraph::Node> result =
+        std::make_shared<default_opset::MVN>(input, reduction_axes, true, eps, ngraph::op::MVNEpsMode::INSIDE_SQRT);
+    // multiply by gamma
+    result = std::make_shared<default_opset::Multiply>(result, nodes[2]);
+    // add beta if available
+    if (num_nodes > 3) {
+        result = std::make_shared<default_opset::Add>(result, nodes[3]);
+    }
+    // spec mentions three outputs (output, mean, inv_std_var) while we support only first one, but:
+    // - onnxruntime also doesn't support the last two
+    // - we'd have to unroll MVN to have them
+    return result->outputs();
+}
+}  // namespace set_1
+}  // namespace op
+}  // namespace onnx_import
+}  // namespace ngraph
diff --git a/ngraph/frontend/onnx/frontend/src/op/com.microsoft/skip_layer_normalization.hpp b/ngraph/frontend/onnx/frontend/src/op/com.microsoft/skip_layer_normalization.hpp
new file mode 100644
index 00000000000..6c134ad7684
--- /dev/null
+++ b/ngraph/frontend/onnx/frontend/src/op/com.microsoft/skip_layer_normalization.hpp
@@ -0,0 +1,17 @@
+// Copyright (C) 2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "onnx_import/core/node.hpp"
+
+namespace ngraph {
+namespace onnx_import {
+namespace op {
+namespace set_1 {
+OutputVector skip_layer_normalization(const Node& node);
+}  // namespace set_1
+}  // namespace op
+}  // namespace onnx_import
+}  // namespace ngraph
diff --git a/ngraph/frontend/onnx/frontend/src/ops_bridge.cpp b/ngraph/frontend/onnx/frontend/src/ops_bridge.cpp
index 75a0c78e03d..20484c78953 100644
--- a/ngraph/frontend/onnx/frontend/src/ops_bridge.cpp
+++ b/ngraph/frontend/onnx/frontend/src/ops_bridge.cpp
@@ -30,6 +30,7 @@
 #include "op/ceil.hpp"
 #include "op/clip.hpp"
 #include "op/com.microsoft/bias_gelu.hpp"
+#include "op/com.microsoft/skip_layer_normalization.hpp"
 #include "op/compress.hpp"
 #include "op/concat.hpp"
 #include "op/constant.hpp"
@@ -479,6 +480,7 @@ OperatorsBridge::OperatorsBridge() {
     REGISTER_OPERATOR_WITH_DOMAIN(OPENVINO_ONNX_DOMAIN, "Swish", 1, swish);
 
     REGISTER_OPERATOR_WITH_DOMAIN(MICROSOFT_DOMAIN, "BiasGelu", 1, bias_gelu);
+    REGISTER_OPERATOR_WITH_DOMAIN(MICROSOFT_DOMAIN, "SkipLayerNormalization", 1, skip_layer_normalization);
 }
 
 #undef REGISTER_OPERATOR
diff --git a/ngraph/test/CMakeLists.txt b/ngraph/test/CMakeLists.txt
index 4b0a08076e3..a50ee6c8571 100644
--- a/ngraph/test/CMakeLists.txt
+++ b/ngraph/test/CMakeLists.txt
@@ -546,6 +546,7 @@ set(MULTI_TEST_SRC
 if (NGRAPH_ONNX_FRONTEND_ENABLE)
     list(APPEND MULTI_TEST_SRC
             onnx/onnx_import.in.cpp
+            onnx/onnx_import_com_microsoft.in.cpp
             onnx/onnx_import_controlflow.in.cpp
             onnx/onnx_import_const_folding.in.cpp
             onnx/onnx_import_convpool.in.cpp
diff --git a/ngraph/test/models/onnx/dynamic_shapes/skip_layer_normalization.prototxt b/ngraph/test/models/onnx/dynamic_shapes/skip_layer_normalization.prototxt
new file mode 100644
index 00000000000..dea7e08d9a6
--- /dev/null
+++ b/ngraph/test/models/onnx/dynamic_shapes/skip_layer_normalization.prototxt
@@ -0,0 +1,76 @@
+ir_version: 6
+producer_name: "nGraph"
+graph {
+  node {
+    input: "input"
+    input: "skip"
+    input: "gamma"
+    input: "beta"
+    input: "bias"
+    output: "out"
+    name: "SkipLayerNorm"
+    op_type: "SkipLayerNormalization"
+    attribute {
+      name: "epsilon"
+      f: 9.999999960041972e-13
+      type: FLOAT
+    }
+    domain: "com.microsoft"
+  }
+  name: "torch-jit-export"
+  input {
+    name: "input"
+    type {
+      tensor_type {
+        elem_type: 1
+      }
+    }
+  }
+  input {
+    name: "skip"
+    type {
+      tensor_type {
+        elem_type: 1
+      }
+    }
+  }
+  input {
+    name: "gamma"
+    type {
+      tensor_type {
+        elem_type: 1
+      }
+    }
+  }
+  input {
+    name: "beta"
+    type {
+      tensor_type {
+        elem_type: 1
+      }
+    }
+  }
+  input {
+    name: "bias"
+    type {
+      tensor_type {
+        elem_type: 1
+      }
+    }
+  }
+  output {
+    name: "out"
+    type {
+      tensor_type {
+        elem_type: 1
+      }
+    }
+  }
+}
+opset_import {
+  version: 11
+}
+opset_import {
+  domain: "com.microsoft"
+  version: 1
+}
diff --git a/ngraph/test/models/onnx/skip_layer_normalization_with_gamma.prototxt b/ngraph/test/models/onnx/skip_layer_normalization_with_gamma.prototxt
new file mode 100644
index 00000000000..6d7dab3c676
--- /dev/null
+++ b/ngraph/test/models/onnx/skip_layer_normalization_with_gamma.prototxt
@@ -0,0 +1,92 @@
+ir_version: 6
+producer_name: "nGraph"
+graph {
+  node {
+    input: "input"
+    input: "skip"
+    input: "gamma"
+    output: "out"
+    name: "SkipLayerNorm"
+    op_type: "SkipLayerNormalization"
+    attribute {
+      name: "epsilon"
+      f: 9.999999960041972e-13
+      type: FLOAT
+    }
+    domain: "com.microsoft"
+  }
+  name: "torch-jit-export"
+  initializer {
+    dims: 4
+    data_type: 1
+    name: "gamma"
+    float_data: 0.1
+    float_data: 0.2
+    float_data: 0.3
+    float_data: 0.4
+  }
+  input {
+    name: "input"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  input {
+    name: "skip"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "out"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 11
+}
+opset_import {
+  domain: "com.microsoft"
+  version: 1
+}
diff --git a/ngraph/test/models/onnx/skip_layer_normalization_with_gamma_beta.prototxt b/ngraph/test/models/onnx/skip_layer_normalization_with_gamma_beta.prototxt
new file mode 100644
index 00000000000..90e92553245
--- /dev/null
+++ b/ngraph/test/models/onnx/skip_layer_normalization_with_gamma_beta.prototxt
@@ -0,0 +1,102 @@
+ir_version: 6
+producer_name: "nGraph"
+graph {
+  node {
+    input: "input"
+    input: "skip"
+    input: "gamma"
+    input: "beta"
+    output: "out"
+    name: "SkipLayerNorm"
+    op_type: "SkipLayerNormalization"
+    attribute {
+      name: "epsilon"
+      f: 9.999999960041972e-13
+      type: FLOAT
+    }
+    domain: "com.microsoft"
+  }
+  name: "torch-jit-export"
+  initializer {
+    dims: 4
+    data_type: 1
+    name: "gamma"
+    float_data: 0.1
+    float_data: 0.2
+    float_data: 0.3
+    float_data: 0.4
+  }
+  initializer {
+    dims: 4
+    data_type: 1
+    name: "beta"
+    float_data: -0.07
+    float_data: -0.4
+    float_data: 0.22
+    float_data: 0
+  }
+  input {
+    name: "input"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  input {
+    name: "skip"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "out"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 11
+}
+opset_import {
+  domain: "com.microsoft"
+  version: 1
+}
diff --git a/ngraph/test/models/onnx/skip_layer_normalization_with_gamma_beta_bias.prototxt b/ngraph/test/models/onnx/skip_layer_normalization_with_gamma_beta_bias.prototxt
new file mode 100644
index 00000000000..8d61aca7a57
--- /dev/null
+++ b/ngraph/test/models/onnx/skip_layer_normalization_with_gamma_beta_bias.prototxt
@@ -0,0 +1,112 @@
+ir_version: 6
+producer_name: "nGraph"
+graph {
+  node {
+    input: "input"
+    input: "skip"
+    input: "gamma"
+    input: "beta"
+    input: "bias"
+    output: "out"
+    name: "SkipLayerNorm"
+    op_type: "SkipLayerNormalization"
+    attribute {
+      name: "epsilon"
+      f: 9.999999960041972e-13
+      type: FLOAT
+    }
+    domain: "com.microsoft"
+  }
+  name: "torch-jit-export"
+  initializer {
+    dims: 4
+    data_type: 1
+    name: "gamma"
+    float_data: 0.1
+    float_data: 0.2
+    float_data: 0.3
+    float_data: 0.4
+  }
+  initializer {
+    dims: 4
+    data_type: 1
+    name: "beta"
+    float_data: -0.07
+    float_data: -0.4
+    float_data: 0.22
+    float_data: 0
+  }
+  initializer {
+    dims: 4
+    data_type: 1
+    name: "bias"
+    float_data: -0.07
+    float_data: -0.4
+    float_data: 0.22
+    float_data: 0
+  }
+  input {
+    name: "input"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  input {
+    name: "skip"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+  output {
+    name: "out"
+    type {
+      tensor_type {
+        elem_type: 1
+        shape {
+          dim {
+            dim_value: 3
+          }
+          dim {
+            dim_value: 2
+          }
+          dim {
+            dim_value: 4
+          }
+        }
+      }
+    }
+  }
+}
+opset_import {
+  version: 11
+}
+opset_import {
+  domain: "com.microsoft"
+  version: 1
+}
diff --git a/ngraph/test/onnx/onnx_import.in.cpp b/ngraph/test/onnx/onnx_import.in.cpp
index e3be4a31d70..d31f4a3b0a8 100644
--- a/ngraph/test/onnx/onnx_import.in.cpp
+++ b/ngraph/test/onnx/onnx_import.in.cpp
@@ -4150,23 +4150,3 @@ NGRAPH_TEST(${BACKEND_NAME}, onnx_model_random_uniform_like) {
     test_case.add_input<ngraph::float16>(Shape{2, 2}, {41, 42, 43, 44});
     test_case.run();
 }
-
-NGRAPH_TEST(${BACKEND_NAME}, onnx_model_bias_gelu) {
-    const auto function = onnx_import::import_onnx_model(file_util::path_join(SERIALIZED_ZOO, "onnx/bias_gelu.onnx"));
-
-    auto test_case = test::TestCase<TestEngine>(function);
-    test_case.add_input<float>({0.5488135,
-                                0.71518934,
-                                0.60276335,
-                                0.5448832,
-                                0.4236548,
-                                0.6458941,
-                                0.4375872,
-                                0.891773,
-                                0.96366274,
-                                0.3834415});
-    test_case.add_input<float>({0.79172504, 0.5288949, 0.56804454, 0.92559665, 0.07103606});
-    test_case.add_expected_output<float>(
-        {1.2198428, 1.1112978, 1.0293297, 1.366493, 0.3411342, 1.329408, 0.8051748, 1.354462, 1.8336612, 0.3068893});
-    test_case.run();
-}
diff --git a/ngraph/test/onnx/onnx_import_com_microsoft.in.cpp b/ngraph/test/onnx/onnx_import_com_microsoft.in.cpp
new file mode 100644
index 00000000000..43f74e64b06
--- /dev/null
+++ b/ngraph/test/onnx/onnx_import_com_microsoft.in.cpp
@@ -0,0 +1,177 @@
+// Copyright (C) 2018-2021 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include <vector>
+
+// clang-format off
+#ifdef ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
+#define DEFAULT_FLOAT_TOLERANCE_BITS ${BACKEND_NAME}_FLOAT_TOLERANCE_BITS
+#endif
+#ifdef ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
+#define DEFAULT_DOUBLE_TOLERANCE_BITS ${BACKEND_NAME}_DOUBLE_TOLERANCE_BITS
+#endif
+// clang-format on
+
+#include "onnx_import/onnx.hpp"
+#include "default_opset.hpp"
+#include "engines_util/test_case.hpp"
+#include "engines_util/test_engines.hpp"
+#include "util/test_control.hpp"
+
+NGRAPH_SUPPRESS_DEPRECATED_START
+
+using namespace ngraph;
+
+static std::string s_manifest = "${MANIFEST}";
+
+using Inputs = std::vector<std::vector<float>>;
+using Outputs = std::vector<std::vector<float>>;
+
+using TestEngine = test::ENGINE_CLASS_NAME(${BACKEND_NAME});
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_bias_gelu) {
+    const auto function = onnx_import::import_onnx_model(file_util::path_join(SERIALIZED_ZOO, "onnx/bias_gelu.onnx"));
+
+    auto test_case = test::TestCase<TestEngine>(function);
+    test_case.add_input<float>({0.5488135,
+                                0.71518934,
+                                0.60276335,
+                                0.5448832,
+                                0.4236548,
+                                0.6458941,
+                                0.4375872,
+                                0.891773,
+                                0.96366274,
+                                0.3834415});
+    test_case.add_input<float>({0.79172504, 0.5288949, 0.56804454, 0.92559665, 0.07103606});
+    test_case.add_expected_output<float>(
+        {1.2198428, 1.1112978, 1.0293297, 1.366493, 0.3411342, 1.329408, 0.8051748, 1.354462, 1.8336612, 0.3068893});
+    test_case.run();
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_skip_layer_normalization_with_gamma_beta_bias) {
+    const auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/skip_layer_normalization_with_gamma_beta_bias.onnx"));
+
+    std::vector<float> input = {
+        0.54881352, 0.71518934, 0.60276335, 0.54488319, 0.42365479, 0.64589411, 0.43758720, 0.89177299,
+        0.96366274, 0.38344151, 0.79172504, 0.52889490, 0.56804454, 0.92559665, 0.07103606, 0.08712930,
+        0.02021840, 0.83261985, 0.77815676, 0.87001216, 0.97861832, 0.79915857, 0.46147937, 0.78052920,
+    };
+    std::vector<float> skip = {
+        0.11827443, 0.63992101, 0.14335328, 0.94466889, 0.52184832, 0.41466194, 0.26455560, 0.77423370,
+        0.45615032, 0.56843394, 0.01878980, 0.61763549, 0.61209571, 0.61693400, 0.94374806, 0.68182027,
+        0.35950789, 0.43703195, 0.69763118, 0.06022547, 0.66676670, 0.67063785, 0.21038257, 0.12892629,
+    };
+    std::vector<float> expected = {
+        -0.19721794, -0.42944565, 0.18620640, 0.61282152,  -0.11097327, -0.59518522, 0.13393641,  0.66901535,
+        0.04256713,  -0.71902490, 0.23107991, 0.17300847,  -0.04390603, -0.31109563, 0.51021838,  -0.66914201,
+        -0.20009395, -0.43313017, 0.67281967, -0.01712347, 0.09767530,  -0.43024653, -0.01836969, -0.29238200,
+    };
+    auto test_case = test::TestCase<TestEngine>(function);
+    test_case.add_input<float>(input);
+    test_case.add_input<float>(skip);
+    test_case.add_expected_output<float>(expected);
+    test_case.run(5);
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_skip_layer_normalization_with_gamma_beta) {
+    const auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/skip_layer_normalization_with_gamma_beta.onnx"));
+
+    std::vector<float> input = {
+        0.54881352, 0.71518934, 0.60276335, 0.54488319, 0.42365479, 0.64589411, 0.43758720, 0.89177299,
+        0.96366274, 0.38344151, 0.79172504, 0.52889490, 0.56804454, 0.92559665, 0.07103606, 0.08712930,
+        0.02021840, 0.83261985, 0.77815676, 0.87001216, 0.97861832, 0.79915857, 0.46147937, 0.78052920,
+    };
+    std::vector<float> skip = {
+        0.11827443, 0.63992101, 0.14335328, 0.94466889, 0.52184832, 0.41466194, 0.26455560, 0.77423370,
+        0.45615032, 0.56843394, 0.01878980, 0.61763549, 0.61209571, 0.61693400, 0.94374806, 0.68182027,
+        0.35950789, 0.43703195, 0.69763118, 0.06022547, 0.66676670, 0.67063785, 0.21038257, 0.12892629,
+    };
+    std::vector<float> expected = {
+        -0.17974678, -0.23946194, -0.04376268, 0.46959469,  -0.11171167, -0.41859278, -0.11082965, 0.64513868,
+        0.07773457,  -0.51403606, -0.13661698, 0.11262375,  -0.05096011, -0.10416907, 0.10070466,  -0.50876135,
+        -0.22290939, -0.27663514, 0.55416691,  -0.08064821, 0.04857478,  -0.25121087, -0.15912610, -0.26637587,
+    };
+    auto test_case = test::TestCase<TestEngine>(function);
+    test_case.add_input<float>(input);
+    test_case.add_input<float>(skip);
+    test_case.add_expected_output<float>(expected);
+    test_case.run(7);
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_skip_layer_normalization_with_gamma) {
+    const auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/skip_layer_normalization_with_gamma.onnx"));
+
+    std::vector<float> input = {
+        0.54881352, 0.71518934, 0.60276335, 0.54488319, 0.42365479, 0.64589411, 0.43758720, 0.89177299,
+        0.96366274, 0.38344151, 0.79172504, 0.52889490, 0.56804454, 0.92559665, 0.07103606, 0.08712930,
+        0.02021840, 0.83261985, 0.77815676, 0.87001216, 0.97861832, 0.79915857, 0.46147937, 0.78052920,
+    };
+    std::vector<float> skip = {
+        0.11827443, 0.63992101, 0.14335328, 0.94466889, 0.52184832, 0.41466194, 0.26455560, 0.77423370,
+        0.45615032, 0.56843394, 0.01878980, 0.61763549, 0.61209571, 0.61693400, 0.94374806, 0.68182027,
+        0.35950789, 0.43703195, 0.69763118, 0.06022547, 0.66676670, 0.67063785, 0.21038257, 0.12892629,
+    };
+    std::vector<float> expected = {
+        -0.10974677, 0.16053806,  -0.26376268, 0.46959469,  -0.04171166, -0.01859277, -0.33082965, 0.64513868,
+        0.14773457,  -0.11403608, -0.35661697, 0.11262375,  0.01903989,  0.29583094,  -0.11929534, -0.50876135,
+        -0.15290938, 0.12336487,  0.33416691,  -0.08064821, 0.11857478,  0.14878914,  -0.37912610, -0.26637587,
+    };
+    auto test_case = test::TestCase<TestEngine>(function);
+    test_case.add_input<float>(input);
+    test_case.add_input<float>(skip);
+    test_case.add_expected_output<float>(expected);
+    test_case.run(6);
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, onnx_model_skip_layer_normalization_dynamic_shapes) {
+    const auto function = onnx_import::import_onnx_model(
+        file_util::path_join(SERIALIZED_ZOO, "onnx/dynamic_shapes/skip_layer_normalization.onnx"));
+
+    std::vector<float> input = {
+        0.54881352, 0.71518934, 0.60276335, 0.54488319, 0.42365479, 0.64589411, 0.43758720, 0.89177299,
+        0.96366274, 0.38344151, 0.79172504, 0.52889490, 0.56804454, 0.92559665, 0.07103606, 0.08712930,
+        0.02021840, 0.83261985, 0.77815676, 0.87001216, 0.97861832, 0.79915857, 0.46147937, 0.78052920,
+    };
+    std::vector<float> skip = {
+        0.11827443, 0.63992101, 0.14335328, 0.94466889, 0.52184832, 0.41466194, 0.26455560, 0.77423370,
+        0.45615032, 0.56843394, 0.01878980, 0.61763549, 0.61209571, 0.61693400, 0.94374806, 0.68182027,
+        0.35950789, 0.43703195, 0.69763118, 0.06022547, 0.66676670, 0.67063785, 0.21038257, 0.12892629,
+    };
+    std::vector<float> gamma = {
+        0.31542835,
+        0.36371076,
+        0.57019675,
+        0.43860152,
+    };
+    std::vector<float> beta = {
+        0.98837382,
+        0.10204481,
+        0.20887676,
+        0.16130951,
+    };
+    std::vector<float> bias = {
+        0.65310830,
+        0.25329161,
+        0.46631077,
+        0.24442559,
+    };
+    std::vector<float> expected = {
+        0.76600611, 0.34308332,  -0.48470584, 0.71335256,  1.10028172, -0.13354334, -0.45232186, 0.79840088,
+        1.52454257, -0.19450217, -0.13759643, 0.03988872,  1.27861762, 0.39529073,  0.12247884,  -0.52944231,
+        0.64228040, 0.21059875,  1.05966032,  -0.14278713, 1.46366918, 0.21215858,  -0.31640187, -0.22832340,
+    };
+
+    auto test_case = test::TestCase<TestEngine, test::TestCaseType::DYNAMIC>(function);
+    test_case.add_input<float>(Shape{3, 2, 4}, input);
+    test_case.add_input<float>(Shape{3, 2, 4}, skip);
+    test_case.add_input<float>(Shape{4}, gamma);
+    test_case.add_input<float>(Shape{4}, beta);
+    test_case.add_input<float>(Shape{4}, bias);
+    test_case.add_expected_output<float>(Shape{3, 2, 4}, expected);
+    test_case.run(7);
+}
diff --git a/ngraph/test/runtime/ie/unit_test.manifest b/ngraph/test/runtime/ie/unit_test.manifest
index 59ddde899f6..fb73dc50382 100644
--- a/ngraph/test/runtime/ie/unit_test.manifest
+++ b/ngraph/test/runtime/ie/unit_test.manifest
@@ -1572,3 +1572,6 @@ IE_GPU.deformable_convolution_opset8_2D_integral_offsets_groups_and_deforgroups
 
 # Not yet implemented - refer PR#6601
 IE_CPU.onnx_model_gather_float_2D_neg_indices
+
+# CPU plug-in doesn't support operation with dynamic rank
+onnx_model_skip_layer_normalization_dynamic_shapes