diff --git a/src/sagemaker/model.py b/src/sagemaker/model.py
index ce0eec2665..017e099ae1 100644
--- a/src/sagemaker/model.py
+++ b/src/sagemaker/model.py
@@ -115,6 +115,19 @@ def __init__(
         self._enable_network_isolation = enable_network_isolation
         self.model_kms_key = model_kms_key
 
+    def _init_sagemaker_session_if_does_not_exist(self, instance_type):
+        """Set ``self.sagemaker_session`` to be a ``LocalSession`` or
+        ``Session`` if it is not already. The type of session object is
+        determined by the instance type.
+        """
+        if self.sagemaker_session:
+            return
+
+        if instance_type in ("local", "local_gpu"):
+            self.sagemaker_session = local.LocalSession()
+        else:
+            self.sagemaker_session = session.Session()
+
     def prepare_container_def(
         self, instance_type, accelerator_type=None
     ):  # pylint: disable=unused-argument
@@ -164,6 +177,8 @@ def _create_sagemaker_model(self, instance_type, accelerator_type=None, tags=Non
         container_def = self.prepare_container_def(instance_type, accelerator_type=accelerator_type)
         self.name = self.name or utils.name_from_image(container_def["Image"])
         enable_network_isolation = self.enable_network_isolation()
+
+        self._init_sagemaker_session_if_does_not_exist(instance_type)
         self.sagemaker_session.create_model(
             self.name,
             self.role,
@@ -324,6 +339,7 @@ def compile(
         framework = framework.upper()
         framework_version = self._get_framework_version() or framework_version
 
+        self._init_sagemaker_session_if_does_not_exist(target_instance_family)
         config = self._compilation_job_config(
             target_instance_family,
             input_shape,
@@ -413,11 +429,7 @@ def deploy(
                 ``self.predictor_cls`` on the created endpoint name, if ``self.predictor_cls``
                 is not None. Otherwise, return None.
         """
-        if not self.sagemaker_session:
-            if instance_type in ("local", "local_gpu"):
-                self.sagemaker_session = local.LocalSession()
-            else:
-                self.sagemaker_session = session.Session()
+        self._init_sagemaker_session_if_does_not_exist(instance_type)
 
         if self.role is None:
             raise ValueError("Role can not be null for deploying a model")
@@ -514,6 +526,8 @@ def transformer(
             volume_kms_key (str): Optional. KMS key ID for encrypting the volume
                 attached to the ML compute instance (default: None).
         """
+        self._init_sagemaker_session_if_does_not_exist(instance_type)
+
         self._create_sagemaker_model(instance_type, tags=tags)
         if self.enable_network_isolation():
             env = None
diff --git a/tests/unit/test_model.py b/tests/unit/test_model.py
index 22d56ac117..254eefc088 100644
--- a/tests/unit/test_model.py
+++ b/tests/unit/test_model.py
@@ -435,6 +435,21 @@ def test_model_create_transformer(sagemaker_session):
     sagemaker.model.Model._create_sagemaker_model.assert_called_with(instance_type, tags=tags)
 
 
+@patch("sagemaker.session.Session")
+@patch("sagemaker.local.LocalSession")
+@patch("sagemaker.fw_utils.tar_and_upload_dir", MagicMock())
+def test_transformer_creates_correct_session(local_session, session):
+    model = DummyFrameworkModel(sagemaker_session=None)
+    transformer = model.transformer(instance_count=1, instance_type="local")
+    assert model.sagemaker_session == local_session.return_value
+    assert transformer.sagemaker_session == local_session.return_value
+
+    model = DummyFrameworkModel(sagemaker_session=None)
+    transformer = model.transformer(instance_count=1, instance_type="ml.m5.xlarge")
+    assert model.sagemaker_session == session.return_value
+    assert transformer.sagemaker_session == session.return_value
+
+
 def test_model_package_enable_network_isolation_with_no_product_id(sagemaker_session):
     sagemaker_session.sagemaker_client.describe_model_package = Mock(
         return_value=DESCRIBE_MODEL_PACKAGE_RESPONSE
@@ -561,6 +576,24 @@ def test_compile_model_for_cloud(sagemaker_session, tmpdir):
     assert model._is_compiled_model is True
 
 
+@patch("sagemaker.session.Session")
+@patch("sagemaker.fw_utils.tar_and_upload_dir", MagicMock())
+def test_compile_creates_session(session):
+    session.return_value.boto_region_name = "us-west-2"
+
+    model = DummyFrameworkModel(sagemaker_session=None)
+    model.compile(
+        target_instance_family="ml_c4",
+        input_shape={"data": [1, 3, 1024, 1024]},
+        output_path="s3://output",
+        role="role",
+        framework="tensorflow",
+        job_name="compile-model",
+    )
+
+    assert model.sagemaker_session == session.return_value
+
+
 def test_check_neo_region(sagemaker_session, tmpdir):
     sagemaker_session.wait_for_compilation_job = Mock(
         return_value=DESCRIBE_COMPILATION_JOB_RESPONSE