diff --git a/tests/unit/sagemaker/model/test_deploy.py b/tests/unit/sagemaker/model/test_deploy.py
index ed911b4021..dd1bb0e57c 100644
--- a/tests/unit/sagemaker/model/test_deploy.py
+++ b/tests/unit/sagemaker/model/test_deploy.py
@@ -25,6 +25,7 @@
 TIMESTAMP = "2017-10-10-14-14-15"
 MODEL_NAME = "{}-{}".format(MODEL_IMAGE, TIMESTAMP)
 
+ACCELERATOR_TYPE = "ml.eia.medium"
 INSTANCE_COUNT = 2
 INSTANCE_TYPE = "ml.c4.4xlarge"
 ROLE = "some-role"
@@ -83,21 +84,19 @@ def test_deploy_accelerator_type(production_variant, create_sagemaker_model, sag
         MODEL_DATA, MODEL_IMAGE, role=ROLE, name=MODEL_NAME, sagemaker_session=sagemaker_session
     )
 
-    accelerator_type = "ml.eia.medium"
-
     production_variant_result = copy.deepcopy(BASE_PRODUCTION_VARIANT)
-    production_variant_result["AcceleratorType"] = accelerator_type
+    production_variant_result["AcceleratorType"] = ACCELERATOR_TYPE
     production_variant.return_value = production_variant_result
 
     model.deploy(
         instance_type=INSTANCE_TYPE,
         initial_instance_count=INSTANCE_COUNT,
-        accelerator_type=accelerator_type,
+        accelerator_type=ACCELERATOR_TYPE,
     )
 
-    create_sagemaker_model.assert_called_with(INSTANCE_TYPE, accelerator_type, None)
+    create_sagemaker_model.assert_called_with(INSTANCE_TYPE, ACCELERATOR_TYPE, None)
     production_variant.assert_called_with(
-        MODEL_NAME, INSTANCE_TYPE, INSTANCE_COUNT, accelerator_type=accelerator_type
+        MODEL_NAME, INSTANCE_TYPE, INSTANCE_COUNT, accelerator_type=ACCELERATOR_TYPE
     )
 
     sagemaker_session.endpoint_from_production_variants.assert_called_with(
@@ -267,3 +266,69 @@ def test_deploy_predictor_cls(production_variant, sagemaker_session):
     assert isinstance(predictor, sagemaker.predictor.RealTimePredictor)
     assert predictor.endpoint == endpoint_name
     assert predictor.sagemaker_session == sagemaker_session
+
+
+def test_deploy_update_endpoint(sagemaker_session):
+    model = Model(MODEL_DATA, MODEL_IMAGE, role=ROLE, sagemaker_session=sagemaker_session)
+    model.deploy(
+        instance_type=INSTANCE_TYPE, initial_instance_count=INSTANCE_COUNT, update_endpoint=True
+    )
+    sagemaker_session.create_endpoint_config.assert_called_with(
+        name=model.name,
+        model_name=model.name,
+        initial_instance_count=INSTANCE_COUNT,
+        instance_type=INSTANCE_TYPE,
+        accelerator_type=None,
+        tags=None,
+        kms_key=None,
+        data_capture_config_dict=None,
+    )
+    config_name = sagemaker_session.create_endpoint_config(
+        name=model.name,
+        model_name=model.name,
+        initial_instance_count=INSTANCE_COUNT,
+        instance_type=INSTANCE_TYPE,
+        accelerator_type=ACCELERATOR_TYPE,
+    )
+    sagemaker_session.update_endpoint.assert_called_with(model.name, config_name, wait=True)
+    sagemaker_session.create_endpoint.assert_not_called()
+
+
+def test_deploy_update_endpoint_optional_args(sagemaker_session):
+    endpoint_name = "endpoint-name"
+    tags = [{"Key": "Value"}]
+    kms_key = "foo"
+    data_capture_config = Mock()
+
+    model = Model(MODEL_DATA, MODEL_IMAGE, role=ROLE, sagemaker_session=sagemaker_session)
+    model.deploy(
+        instance_type=INSTANCE_TYPE,
+        initial_instance_count=INSTANCE_COUNT,
+        update_endpoint=True,
+        endpoint_name=endpoint_name,
+        accelerator_type=ACCELERATOR_TYPE,
+        tags=tags,
+        kms_key=kms_key,
+        wait=False,
+        data_capture_config=data_capture_config,
+    )
+    sagemaker_session.create_endpoint_config.assert_called_with(
+        name=model.name,
+        model_name=model.name,
+        initial_instance_count=INSTANCE_COUNT,
+        instance_type=INSTANCE_TYPE,
+        accelerator_type=ACCELERATOR_TYPE,
+        tags=tags,
+        kms_key=kms_key,
+        data_capture_config_dict=data_capture_config._to_request_dict(),
+    )
+    config_name = sagemaker_session.create_endpoint_config(
+        name=model.name,
+        model_name=model.name,
+        initial_instance_count=INSTANCE_COUNT,
+        instance_type=INSTANCE_TYPE,
+        accelerator_type=ACCELERATOR_TYPE,
+        wait=False,
+    )
+    sagemaker_session.update_endpoint.assert_called_with(endpoint_name, config_name, wait=False)
+    sagemaker_session.create_endpoint.assert_not_called()
diff --git a/tests/unit/sagemaker/model/test_framework_model.py b/tests/unit/sagemaker/model/test_framework_model.py
index 09cb5531ce..33f52316ef 100644
--- a/tests/unit/sagemaker/model/test_framework_model.py
+++ b/tests/unit/sagemaker/model/test_framework_model.py
@@ -33,8 +33,6 @@
 BUCKET_NAME = "mybucket"
 INSTANCE_COUNT = 1
 INSTANCE_TYPE = "c4.4xlarge"
-ACCELERATOR_TYPE = "ml.eia.medium"
-IMAGE_NAME = "fakeimage"
 REGION = "us-west-2"
 MODEL_NAME = "{}-{}".format(MODEL_IMAGE, TIMESTAMP)
 GIT_REPO = "https://github.com/aws/sagemaker-python-sdk.git"
@@ -165,72 +163,6 @@ def test_prepare_container_def_no_model_defaults(sagemaker_session, tmpdir):
     }
 
 
-@patch("sagemaker.fw_utils.tar_and_upload_dir", MagicMock())
-def test_deploy_update_endpoint(sagemaker_session, tmpdir):
-    model = DummyFrameworkModel(sagemaker_session, source_dir=tmpdir)
-    model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=1, update_endpoint=True)
-    sagemaker_session.create_endpoint_config.assert_called_with(
-        name=model.name,
-        model_name=model.name,
-        initial_instance_count=INSTANCE_COUNT,
-        instance_type=INSTANCE_TYPE,
-        accelerator_type=None,
-        tags=None,
-        kms_key=None,
-        data_capture_config_dict=None,
-    )
-    config_name = sagemaker_session.create_endpoint_config(
-        name=model.name,
-        model_name=model.name,
-        initial_instance_count=INSTANCE_COUNT,
-        instance_type=INSTANCE_TYPE,
-        accelerator_type=ACCELERATOR_TYPE,
-    )
-    sagemaker_session.update_endpoint.assert_called_with(model.name, config_name, wait=True)
-    sagemaker_session.create_endpoint.assert_not_called()
-
-
-@patch("sagemaker.fw_utils.tar_and_upload_dir", MagicMock())
-def test_deploy_update_endpoint_optional_args(sagemaker_session, tmpdir):
-    endpoint_name = "endpoint-name"
-    tags = [{"Key": "Value"}]
-    kms_key = "foo"
-    data_capture_config = MagicMock()
-
-    model = DummyFrameworkModel(sagemaker_session, source_dir=tmpdir)
-    model.deploy(
-        instance_type=INSTANCE_TYPE,
-        initial_instance_count=1,
-        update_endpoint=True,
-        endpoint_name=endpoint_name,
-        accelerator_type=ACCELERATOR_TYPE,
-        tags=tags,
-        kms_key=kms_key,
-        wait=False,
-        data_capture_config=data_capture_config,
-    )
-    sagemaker_session.create_endpoint_config.assert_called_with(
-        name=model.name,
-        model_name=model.name,
-        initial_instance_count=INSTANCE_COUNT,
-        instance_type=INSTANCE_TYPE,
-        accelerator_type=ACCELERATOR_TYPE,
-        tags=tags,
-        kms_key=kms_key,
-        data_capture_config_dict=data_capture_config._to_request_dict(),
-    )
-    config_name = sagemaker_session.create_endpoint_config(
-        name=model.name,
-        model_name=model.name,
-        initial_instance_count=INSTANCE_COUNT,
-        instance_type=INSTANCE_TYPE,
-        accelerator_type=ACCELERATOR_TYPE,
-        wait=False,
-    )
-    sagemaker_session.update_endpoint.assert_called_with(endpoint_name, config_name, wait=False)
-    sagemaker_session.create_endpoint.assert_not_called()
-
-
 @patch("sagemaker.git_utils.git_clone_repo")
 @patch("sagemaker.model.fw_utils.tar_and_upload_dir")
 def test_git_support_succeed(tar_and_upload_dir, git_clone_repo, sagemaker_session):