diff --git a/google/cloud/aiplatform/models.py b/google/cloud/aiplatform/models.py
index e79e308693..bbc7d9ab72 100644
--- a/google/cloud/aiplatform/models.py
+++ b/google/cloud/aiplatform/models.py
@@ -5368,6 +5368,13 @@ def deploy(
             system_labels=system_labels,
         )
 
+    def _should_enable_dedicated_endpoint(self, fast_tryout_enabled: bool) -> bool:
+        """Check if dedicated endpoint should be enabled for this endpoint.
+
+        Returns True if endpoint should be a dedicated endpoint.
+        """
+        return fast_tryout_enabled
+
     @base.optional_sync(return_input_arg="endpoint", bind_future_to_self=False)
     def _deploy(
         self,
@@ -5548,6 +5555,9 @@ def _deploy(
                     location=self.location,
                     credentials=self.credentials,
                     encryption_spec_key_name=encryption_spec_key_name,
+                    dedicated_endpoint_enabled=self._should_enable_dedicated_endpoint(
+                        fast_tryout_enabled
+                    ),
                 )
             else:
                 endpoint = PrivateEndpoint.create(
diff --git a/google/cloud/aiplatform/preview/models.py b/google/cloud/aiplatform/preview/models.py
index 1c6b6bc972..11837cd854 100644
--- a/google/cloud/aiplatform/preview/models.py
+++ b/google/cloud/aiplatform/preview/models.py
@@ -1548,6 +1548,13 @@ def deploy(
             system_labels=system_labels,
         )
 
+    def _should_enable_dedicated_endpoint(self, fast_tryout_enabled: bool) -> bool:
+        """Check if dedicated endpoint should be enabled for this endpoint.
+
+        Returns True if endpoint should be a dedicated endpoint.
+        """
+        return fast_tryout_enabled
+
     @base.optional_sync(return_input_arg="endpoint", bind_future_to_self=False)
     def _deploy(
         self,
@@ -1689,6 +1696,9 @@ def _deploy(
                     location=self.location,
                     credentials=self.credentials,
                     encryption_spec_key_name=encryption_spec_key_name,
+                    dedicated_endpoint_enabled=self._should_enable_dedicated_endpoint(
+                        fast_tryout_enabled
+                    ),
                 )
             else:
                 endpoint = models.PrivateEndpoint.create(
diff --git a/tests/unit/aiplatform/test_models.py b/tests/unit/aiplatform/test_models.py
index e5ab109d42..edde450308 100644
--- a/tests/unit/aiplatform/test_models.py
+++ b/tests/unit/aiplatform/test_models.py
@@ -556,6 +556,20 @@ def get_endpoint_mock():
         yield get_endpoint_mock
 
 
+@pytest.fixture
+def create_endpoint_mock():
+    with mock.patch.object(
+        endpoint_service_client.EndpointServiceClient, "create_endpoint"
+    ) as create_endpoint_mock:
+        create_endpoint_lro_mock = mock.Mock(ga_operation.Operation)
+        create_endpoint_lro_mock.result.return_value = gca_endpoint.Endpoint(
+            name=test_constants.EndpointConstants._TEST_ENDPOINT_NAME,
+            display_name=test_constants.EndpointConstants._TEST_DISPLAY_NAME,
+        )
+        create_endpoint_mock.return_value = create_endpoint_lro_mock
+        yield create_endpoint_mock
+
+
 @pytest.fixture
 def get_model_mock():
     with mock.patch.object(
@@ -2531,7 +2545,7 @@ def test_deploy_disable_container_logging(self, deploy_model_mock, sync):
     )
     @pytest.mark.parametrize("sync", [True, False])
     def test_preview_deploy_with_fast_tryout_enabled(
-        self, preview_deploy_model_mock, sync
+        self, preview_deploy_model_mock, create_endpoint_mock, sync
     ):
         test_model = models.Model(_TEST_ID).preview
         test_model._gca_resource.supported_deployment_resources_types.append(
@@ -2551,6 +2565,19 @@ def test_preview_deploy_with_fast_tryout_enabled(
         if not sync:
             test_endpoint.wait()
 
+        expected_endpoint = gca_endpoint.Endpoint(
+            display_name=_TEST_MODEL_NAME + "_endpoint",
+            dedicated_endpoint_enabled=True,
+        )
+
+        create_endpoint_mock.assert_called_once_with(
+            parent=_TEST_PARENT,
+            endpoint=expected_endpoint,
+            metadata=(),
+            timeout=None,
+            endpoint_id=None,
+        )
+
         expected_machine_spec = gca_machine_resources_v1beta1.MachineSpec(
             machine_type=_TEST_MACHINE_TYPE,
             accelerator_type=_TEST_ACCELERATOR_TYPE,
@@ -2583,7 +2610,9 @@ def test_preview_deploy_with_fast_tryout_enabled(
         "get_endpoint_mock",
     )
     @pytest.mark.parametrize("sync", [True, False])
-    def test_deploy_with_fast_tryout_enabled(self, deploy_model_mock, sync):
+    def test_deploy_with_fast_tryout_enabled(
+        self, deploy_model_mock, create_endpoint_mock, sync
+    ):
         test_model = models.Model(_TEST_ID)
         test_model._gca_resource.supported_deployment_resources_types.append(
             aiplatform.gapic.Model.DeploymentResourcesType.DEDICATED_RESOURCES
@@ -2602,6 +2631,19 @@ def test_deploy_with_fast_tryout_enabled(self, deploy_model_mock, sync):
         if not sync:
             test_endpoint.wait()
 
+        expected_endpoint = gca_endpoint.Endpoint(
+            display_name=_TEST_MODEL_NAME + "_endpoint",
+            dedicated_endpoint_enabled=True,
+        )
+
+        create_endpoint_mock.assert_called_once_with(
+            parent=_TEST_PARENT,
+            endpoint=expected_endpoint,
+            metadata=(),
+            timeout=None,
+            endpoint_id=None,
+        )
+
         expected_machine_spec = gca_machine_resources.MachineSpec(
             machine_type=_TEST_MACHINE_TYPE,
             accelerator_type=_TEST_ACCELERATOR_TYPE,