diff --git a/tools/mo/openvino/tools/mo/ops/activation_ops.py b/tools/mo/openvino/tools/mo/ops/activation_ops.py
index bdf48463b9b..2d76a274c1e 100644
--- a/tools/mo/openvino/tools/mo/ops/activation_ops.py
+++ b/tools/mo/openvino/tools/mo/ops/activation_ops.py
@@ -291,6 +291,6 @@ class Swish(Op):
                 assert beta.ndim == 0, 'The "beta" value for node {} must be a scalar'.format(node_name)
                 beta = beta.item()
 
-        input_value = node.in_port(1).data.get_value()
+        input_value = node.in_port(0).data.get_value()
         if input_value is not None and beta is not None:
             node.out_port(0).data.set_value(input_value / (1.0 + np.exp(-input_value * beta)))
diff --git a/tools/mo/unit_tests/mo/ops/activation_test.py b/tools/mo/unit_tests/mo/ops/activation_test.py
index d1ea12e9726..95310356b02 100644
--- a/tools/mo/unit_tests/mo/ops/activation_test.py
+++ b/tools/mo/unit_tests/mo/ops/activation_test.py
@@ -5,7 +5,7 @@ import unittest
 
 import numpy as np
 
-from openvino.tools.mo.ops.activation_ops import Elu, SoftPlus, Mish
+from openvino.tools.mo.ops.activation_ops import Elu, SoftPlus, Mish, Swish
 from openvino.tools.mo.graph.graph import Node
 from unit_tests.utils.graph import build_graph
 
@@ -115,3 +115,32 @@ class TestActivationOp(unittest.TestCase):
             self.assertEqual(res_shape[i], value)
         for i, value in enumerate(exp_value):
             self.assertAlmostEqual(res_value[i], value)
+
+    def test_activation_swish_infer(self):
+        graph = build_graph(self.nodes_attributes,
+                            [
+                                ('node_1', 'activation_node'),
+                                ('activation_node', 'node_3')
+                            ],
+                            {
+                                'node_1': {
+                                    'value': np.array([-1.0, 0.0, 1.0, 20.0])
+                                },
+                                'activation_node': {
+                                    'op': 'Swish',
+                                },
+                                'node_3': {
+                                    'value': None
+                                }
+                            })
+        graph.graph['layout'] = 'NCHW'
+        activation_node = Node(graph, 'activation_node')
+        Swish.infer(activation_node)
+        exp_shape = np.array([4])
+        res_shape = graph.node['node_3']['shape']
+        res_value = graph.node['node_3']['value']
+        exp_value = np.array([-0.26894142, 0.0, 0.73105858, 19.99999996])
+        for i, value in enumerate(exp_shape):
+            self.assertEqual(res_shape[i], value)
+        for i, value in enumerate(exp_value):
+            self.assertAlmostEqual(res_value[i], value)