diff --git a/tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py b/tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py
index d9166d0b069..35f440c3823 100644
--- a/tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py
+++ b/tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_conv_lstm_2d.py
@@ -15,19 +15,11 @@ class TestKerasConvLSTM2D(CommonTF2LayerTest):
         assert len(input_names) == 1, "Test expects only one input"
         x_shape = inputs_info[input_names[0]]
         inputs_data = {}
-        inputs_data[input_names[0]] = np.random.uniform(-1, 1, x_shape)
+        inputs_data[input_names[0]] = np.random.uniform(-1, 1, x_shape).astype(np.float32)
 
         return inputs_data
 
     def create_keras_conv_lstm_2d_net(self, params, input_shapes):
-        activation_func_structure = {
-            "relu": tf.nn.relu,
-            "swish": tf.nn.swish,
-            "elu": tf.nn.elu,
-        }
-        if "activation" in params:
-            params["activation"] = activation_func_structure[params["activation"]]
-
         # create TensorFlow 2 model with Keras ConvLSTM2D operation
         tf.keras.backend.clear_session()
 
@@ -38,13 +30,24 @@ class TestKerasConvLSTM2D(CommonTF2LayerTest):
         return tf2_net, None
 
     test_data_basic = [
-        pytest.param(dict(params=dict(filters=4, kernel_size=(3, 3), padding='same', return_sequences=False,
-                                      activation="swish"),
-                          input_shapes=[[2, 5, 20, 30, 2]]), marks=pytest.mark.skip(reason="*-108786")),
-        pytest.param(dict(params=dict(filters=6, kernel_size=(2, 3), padding='valid', dilation_rate=3,
-                                      recurrent_activation="elu", return_sequences=True, use_bias=True,
-                                      data_format="channels_first"),
-                          input_shapes=[[2, 5, 1, 40, 30]]), marks=pytest.mark.skip(reason="110006")),
+        dict(params=dict(filters=4, kernel_size=(3, 3), padding='same', return_sequences=False,
+                         activation=tf.nn.swish),
+             input_shapes=[[2, 5, 20, 30, 2]]),
+        dict(params=dict(filters=6, kernel_size=(2, 3), padding='valid', dilation_rate=3,
+                         recurrent_activation=tf.nn.elu, return_sequences=True, use_bias=True,
+                         data_format="channels_first"),
+             input_shapes=[[2, 5, 1, 40, 30]]),
+        dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', return_sequences=False),
+             input_shapes=[[2, 5, 20, 30, 1]]),
+        dict(params=dict(filters=2, kernel_size=(2, 2), padding='same', return_sequences=False, activation=tf.nn.swish),
+             input_shapes=[[2, 5, 25, 15, 3]]),
+        dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', strides=(2, 2),
+                         return_sequences=True),
+             input_shapes=[[2, 5, 10, 15, 2]]),
+        dict(params=dict(filters=5, kernel_size=(2, 2), padding='valid', dilation_rate=3,
+                         activation=tf.nn.relu, return_sequences=False, use_bias=True,
+                         data_format="channels_last"),
+             input_shapes=[[2, 5, 18, 17, 1]])
     ]
 
     @pytest.mark.parametrize("params", test_data_basic)
@@ -56,26 +59,3 @@ class TestKerasConvLSTM2D(CommonTF2LayerTest):
                    precision,
                    temp_dir=temp_dir, use_old_api=use_old_api, ir_version=ir_version,
                    use_new_frontend=use_new_frontend, **params)
-
-    test_data_others = [
-        dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', return_sequences=False),
-             input_shapes=[[2, 5, 20, 30, 1]]),
-        dict(params=dict(filters=2, kernel_size=(2, 2), padding='same', return_sequences=False, activation="swish"),
-             input_shapes=[[2, 5, 25, 15, 3]]),
-        dict(params=dict(filters=3, kernel_size=(3, 3), padding='valid', strides=(2, 2),
-                         return_sequences=True),
-             input_shapes=[[2, 5, 10, 15, 2]]),
-        dict(params=dict(filters=5, kernel_size=(2, 2), padding='valid', dilation_rate=3,
-                         activation="relu", return_sequences=False, use_bias=True,
-                         data_format="channels_last"),
-             input_shapes=[[2, 5, 18, 17, 1]])
-    ]
-
-    @pytest.mark.parametrize("params", test_data_others)
-    @pytest.mark.nightly
-    def test_keras_conv_lstm_2d_others(self, params, ie_device, precision, ir_version, temp_dir,
-                                       use_old_api, use_new_frontend):
-        self._test(*self.create_keras_conv_lstm_2d_net(**params), ie_device,
-                   precision,
-                   temp_dir=temp_dir, use_old_api=use_old_api, ir_version=ir_version,
-                   use_new_frontend=use_new_frontend, **params)