diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 3f9f6e1c67..93492770d2 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -2,14 +2,26 @@
 CHANGELOG
 =========
 
-1.18.3.dev
+1.18.4.dev
 ==========
 
+* doc-fix: Remove incorrect parameter for EI TFS Python README
+* feature: ``Predictor``: delete SageMaker model
+* feature: ``Pipeline``: delete SageMaker model
+
+1.18.3.post1
+============
+
+* doc-fix: fix README for PyPI
+
+1.18.3
+======
+
 * doc-fix: update information about saving models in the MXNet README
 * doc-fix: change ReadTheDocs links from latest to stable
 * doc-fix: add ``transform_fn`` information and fix ``input_fn`` signature in the MXNet README
-* feature: Support for ``Predictor`` to delete endpoint configuration by default when calling ``delete_endpoint()``
-* feature: Support for ``model`` to delete SageMaker model
+* feature: Support for ``Predictor`` to delete model, and delete endpoint configuration by default when calling ``delete_endpoint()``
+* feature: Support for ``Model`` to delete SageMaker model
 * feature: Support for ``Transformer`` to delete SageMaker model
 * bug-fix: Default account for SKLearnModel fixed
 
diff --git a/README.rst b/README.rst
index b468c0c912..aa509ea301 100644
--- a/README.rst
+++ b/README.rst
@@ -192,10 +192,13 @@ Here is an end to end example of how to use a SageMaker Estimator:
     # Tears down the SageMaker endpoint and endpoint configuration
     mxnet_predictor.delete_endpoint()
 
+    # Deletes SageMaker model
+    mxnet_predictor.delete_model()
 
 The example above will eventually delete both the SageMaker endpoint and endpoint configuration through `delete_endpoint()`. If you want to keep your SageMaker endpoint configuration, use the value False for the `delete_endpoint_config` parameter, as shown below.
 
 .. code:: python
+
     # Only delete the SageMaker endpoint, while keeping the corresponding endpoint configuration.
     mxnet_predictor.delete_endpoint(delete_endpoint_config=False)
 
@@ -229,6 +232,9 @@ For more `information <https://boto3.amazonaws.com/v1/documentation/api/latest/r
     # Tears down the SageMaker endpoint and endpoint configuration
     mxnet_predictor.delete_endpoint()
 
+    # Deletes SageMaker model
+    mxnet_predictor.delete_model()
+
 Training Metrics
 ~~~~~~~~~~~~~~~~
 The SageMaker Python SDK allows you to specify a name and a regular expression for metrics you want to track for training.
@@ -283,6 +289,9 @@ We can take the example in  `Using Estimators <#using-estimators>`__ , and use e
     # Tears down the endpoint container and deletes the corresponding endpoint configuration
     mxnet_predictor.delete_endpoint()
 
+    # Deletes the model
+    mxnet_predictor.delete_model()
+
 
 If you have an existing model and want to deploy it locally, don't specify a sagemaker_session argument to the ``MXNetModel`` constructor.
 The correct session is generated when you call ``model.deploy()``.
@@ -306,6 +315,9 @@ Here is an end-to-end example:
     # Tear down the endpoint container and delete the corresponding endpoint configuration
     predictor.delete_endpoint()
 
+    # Deletes the model
+    predictor.delete_model()
+
 
 If you don't want to deploy your model locally, you can also choose to perform a Local Batch Transform Job. This is
 useful if you want to test your container before creating a Sagemaker Batch Transform Job. Note that the performance
diff --git a/setup.py b/setup.py
index 3372a45467..ce6ca0f16d 100644
--- a/setup.py
+++ b/setup.py
@@ -33,7 +33,7 @@ def read(fname):
     required_packages.append('enum34>=1.1.6')
 
 setup(name="sagemaker",
-      version='1.18.2',
+      version='1.18.3.post1',
       description="Open source library for training and deploying models on Amazon SageMaker.",
       packages=find_packages('src'),
       package_dir={'': 'src'},
diff --git a/src/sagemaker/pipeline.py b/src/sagemaker/pipeline.py
index af379a6b3d..4d9d3cd19e 100644
--- a/src/sagemaker/pipeline.py
+++ b/src/sagemaker/pipeline.py
@@ -103,3 +103,14 @@ def deploy(self, initial_instance_count, instance_type, endpoint_name=None, tags
         self.sagemaker_session.endpoint_from_production_variants(self.endpoint_name, [production_variant], tags)
         if self.predictor_cls:
             return self.predictor_cls(self.endpoint_name, self.sagemaker_session)
+
+    def delete_model(self):
+        """Delete the SageMaker model backing this pipeline model. This does not delete the list of SageMaker models used
+        in multiple containers to build the inference pipeline.
+
+        """
+
+        if self.name is None:
+            raise ValueError('The SageMaker model must be created before attempting to delete.')
+
+        self.sagemaker_session.delete_model(self.name)
diff --git a/src/sagemaker/predictor.py b/src/sagemaker/predictor.py
index 958b21afe6..dd47b27e17 100644
--- a/src/sagemaker/predictor.py
+++ b/src/sagemaker/predictor.py
@@ -56,6 +56,7 @@ def __init__(self, endpoint, sagemaker_session=None, serializer=None, deserializ
         self.deserializer = deserializer
         self.content_type = content_type or getattr(serializer, 'content_type', None)
         self.accept = accept or getattr(deserializer, 'accept', None)
+        self._model_names = self._get_model_names()
 
     def predict(self, data, initial_args=None):
         """Return the inference from the specified endpoint.
@@ -109,16 +110,16 @@ def _delete_endpoint_config(self):
         """Delete the Amazon SageMaker endpoint configuration
 
         """
-        endpoint_description = self.sagemaker_session.sagemaker_client.describe_endpoint(EndpointName=self.endpoint)
-        endpoint_config_name = endpoint_description['EndpointConfigName']
-        self.sagemaker_session.delete_endpoint_config(endpoint_config_name)
+        self.sagemaker_session.delete_endpoint_config(self._endpoint_config_name)
 
     def delete_endpoint(self, delete_endpoint_config=True):
-        """Delete the Amazon SageMaker endpoint and endpoint configuration backing this predictor.
+        """Delete the Amazon SageMaker endpoint backing this predictor. Also delete the endpoint configuration attached
+           to it if delete_endpoint_config is True.
 
         Args:
-            delete_endpoint_config (bool): Flag to indicate whether to delete the corresponding SageMaker endpoint
-                configuration tied to the endpoint. If False, only the endpoint will be deleted. (default: True)
+            delete_endpoint_config (bool, optional): Flag to indicate whether to delete endpoint configuration together
+                with endpoint. Defaults to True. If True, both endpoint and endpoint configuration will be deleted. If
+                False, only endpoint will be deleted.
 
         """
         if delete_endpoint_config:
@@ -126,6 +127,25 @@ def delete_endpoint(self, delete_endpoint_config=True):
 
         self.sagemaker_session.delete_endpoint(self.endpoint)
 
+    def delete_model(self):
+        """Deletes the Amazon SageMaker models backing this predictor.
+
+        """
+        for model_name in self._model_names:
+            self.sagemaker_session.delete_model(model_name)
+
+    def _get_endpoint_config_desc(self):
+        endpoint_desc = self.sagemaker_session.sagemaker_client.describe_endpoint(EndpointName=self.endpoint)
+        self._endpoint_config_name = endpoint_desc['EndpointConfigName']
+        endpoint_config = self.sagemaker_session.sagemaker_client.describe_endpoint_config(
+            EndpointConfigName=self._endpoint_config_name)
+        return endpoint_config
+
+    def _get_model_names(self):
+        endpoint_config = self._get_endpoint_config_desc()
+        production_variants = endpoint_config['ProductionVariants']
+        return map(lambda d: d['ModelName'], production_variants)
+
 
 class _CsvSerializer(object):
     def __init__(self):
diff --git a/src/sagemaker/tensorflow/deploying_python.rst b/src/sagemaker/tensorflow/deploying_python.rst
index 6a7fc6c78b..fdacbdd92b 100644
--- a/src/sagemaker/tensorflow/deploying_python.rst
+++ b/src/sagemaker/tensorflow/deploying_python.rst
@@ -31,8 +31,7 @@ TensorFlow serving on SageMaker has support for `Elastic Inference <https://docs
 
   predictor = estimator.deploy(initial_instance_count=1,
                                instance_type='ml.c5.xlarge',
-                               accelerator_type='ml.eia1.medium'
-                               endpoint_type='tensorflow-serving-elastic-inference')
+                               accelerator_type='ml.eia1.medium')
 
 What happens when deploy is called
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
diff --git a/tests/integ/test_inference_pipeline.py b/tests/integ/test_inference_pipeline.py
index d3c597b13e..1fbe45c618 100644
--- a/tests/integ/test_inference_pipeline.py
+++ b/tests/integ/test_inference_pipeline.py
@@ -92,3 +92,8 @@ def test_inference_pipeline_model_deploy(sagemaker_session):
 
         invalid_data = "1.0,28.0,C,38.0,71.5,1.0"
         assert (predictor.predict(invalid_data) is None)
+
+    model.delete_model()
+    with pytest.raises(Exception) as exception:
+        sagemaker_session.sagemaker_client.describe_model(ModelName=model.name)
+        assert 'Could not find model' in str(exception.value)
diff --git a/tests/integ/test_kmeans.py b/tests/integ/test_kmeans.py
index 85f6b247e8..37e18fbfd7 100644
--- a/tests/integ/test_kmeans.py
+++ b/tests/integ/test_kmeans.py
@@ -75,6 +75,11 @@ def test_kmeans(sagemaker_session):
             assert record.label["closest_cluster"] is not None
             assert record.label["distance_to_cluster"] is not None
 
+    predictor.delete_model()
+    with pytest.raises(Exception) as exception:
+        sagemaker_session.sagemaker_client.describe_model(ModelName=model.name)
+        assert 'Could not find model' in str(exception.value)
+
 
 def test_async_kmeans(sagemaker_session):
     training_job_name = ""
diff --git a/tests/integ/test_mxnet_train.py b/tests/integ/test_mxnet_train.py
index 3d67f3b4c2..ed57789933 100644
--- a/tests/integ/test_mxnet_train.py
+++ b/tests/integ/test_mxnet_train.py
@@ -72,6 +72,11 @@ def test_deploy_model(mxnet_training_job, sagemaker_session, mxnet_full_version)
         data = numpy.zeros(shape=(1, 1, 28, 28))
         predictor.predict(data)
 
+    predictor.delete_model()
+    with pytest.raises(Exception) as exception:
+        sagemaker_session.sagemaker_client.describe_model(ModelName=model.name)
+        assert 'Could not find model' in str(exception.value)
+
 
 def test_deploy_model_with_update_endpoint(mxnet_training_job, sagemaker_session, mxnet_full_version):
     endpoint_name = 'test-mxnet-deploy-model-{}'.format(sagemaker_timestamp())
diff --git a/tests/unit/test_chainer.py b/tests/unit/test_chainer.py
index fbc439ecde..aa712038da 100644
--- a/tests/unit/test_chainer.py
+++ b/tests/unit/test_chainer.py
@@ -45,6 +45,15 @@
 GPU = 'ml.p2.xlarge'
 CPU = 'ml.c4.xlarge'
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -54,6 +63,8 @@ def sagemaker_session():
 
     describe = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/m.tar.gz'}}
     session.sagemaker_client.describe_training_job = Mock(return_value=describe)
+    session.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    session.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     session.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     session.expand_role = Mock(name="expand_role", return_value=ROLE)
     return session
diff --git a/tests/unit/test_estimator.py b/tests/unit/test_estimator.py
index 04afe65b5c..59d803254e 100644
--- a/tests/unit/test_estimator.py
+++ b/tests/unit/test_estimator.py
@@ -102,6 +102,15 @@
     'ModelDataUrl': MODEL_DATA,
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 class DummyFramework(Framework):
     __framework_name__ = 'dummy'
@@ -146,6 +155,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     return sms
 
 
diff --git a/tests/unit/test_fm.py b/tests/unit/test_fm.py
index 9dbb7c014c..d420301378 100644
--- a/tests/unit/test_fm.py
+++ b/tests/unit/test_fm.py
@@ -37,6 +37,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -47,6 +56,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     return sms
 
 
diff --git a/tests/unit/test_ipinsights.py b/tests/unit/test_ipinsights.py
index e64adbd1be..402383348b 100644
--- a/tests/unit/test_ipinsights.py
+++ b/tests/unit/test_ipinsights.py
@@ -39,6 +39,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -49,6 +58,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_kmeans.py b/tests/unit/test_kmeans.py
index a5b829fa60..dc87a38ec1 100644
--- a/tests/unit/test_kmeans.py
+++ b/tests/unit/test_kmeans.py
@@ -36,6 +36,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -46,6 +55,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_knn.py b/tests/unit/test_knn.py
index 890f6ec9fc..fad5ae64b1 100644
--- a/tests/unit/test_knn.py
+++ b/tests/unit/test_knn.py
@@ -40,6 +40,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -50,6 +59,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_lda.py b/tests/unit/test_lda.py
index 5c0528e322..eed9902292 100644
--- a/tests/unit/test_lda.py
+++ b/tests/unit/test_lda.py
@@ -35,6 +35,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -44,6 +53,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_linear_learner.py b/tests/unit/test_linear_learner.py
index 8819717957..1e5fa64f0f 100644
--- a/tests/unit/test_linear_learner.py
+++ b/tests/unit/test_linear_learner.py
@@ -37,6 +37,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -47,6 +56,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_mxnet.py b/tests/unit/test_mxnet.py
index 0136053c13..18302fdb20 100644
--- a/tests/unit/test_mxnet.py
+++ b/tests/unit/test_mxnet.py
@@ -45,6 +45,15 @@
 CPU_C5 = 'ml.c5.xlarge'
 LAUNCH_PS_DISTRIBUTIONS_DICT = {'parameter_server': {'enabled': True}}
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -55,6 +64,8 @@ def sagemaker_session():
     describe = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/m.tar.gz'}}
     describe_compilation = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/model_c5.tar.gz'}}
     session.sagemaker_client.describe_training_job = Mock(return_value=describe)
+    session.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    session.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     session.wait_for_compilation_job = Mock(return_value=describe_compilation)
     session.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     session.expand_role = Mock(name="expand_role", return_value=ROLE)
diff --git a/tests/unit/test_ntm.py b/tests/unit/test_ntm.py
index 1f3866968b..c72e8cea70 100644
--- a/tests/unit/test_ntm.py
+++ b/tests/unit/test_ntm.py
@@ -36,6 +36,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -46,6 +55,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_object2vec.py b/tests/unit/test_object2vec.py
index 4fc6130722..8d8e557014 100644
--- a/tests/unit/test_object2vec.py
+++ b/tests/unit/test_object2vec.py
@@ -45,6 +45,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -55,6 +64,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_pca.py b/tests/unit/test_pca.py
index c72cd4fedd..0748d90ca6 100644
--- a/tests/unit/test_pca.py
+++ b/tests/unit/test_pca.py
@@ -36,6 +36,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -46,6 +55,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_pipeline_model.py b/tests/unit/test_pipeline_model.py
index e45c34409e..d640aa3235 100644
--- a/tests/unit/test_pipeline_model.py
+++ b/tests/unit/test_pipeline_model.py
@@ -138,3 +138,22 @@ def test_deploy_tags(tfo, time, sagemaker_session):
           'InitialInstanceCount': 1,
           'VariantName': 'AllTraffic'}],
         tags)
+
+
+def test_delete_model_without_deploy(sagemaker_session):
+    pipeline_model = PipelineModel([], role=ROLE, sagemaker_session=sagemaker_session)
+
+    expected_error_message = 'The SageMaker model must be created before attempting to delete.'
+    with pytest.raises(ValueError, match=expected_error_message):
+        pipeline_model.delete_model()
+
+
+@patch('tarfile.open')
+@patch('time.strftime', return_value=TIMESTAMP)
+def test_delete_model(tfo, time, sagemaker_session):
+    framework_model = DummyFrameworkModel(sagemaker_session)
+    pipeline_model = PipelineModel([framework_model], role=ROLE, sagemaker_session=sagemaker_session)
+    pipeline_model.deploy(instance_type=INSTANCE_TYPE, initial_instance_count=1)
+
+    pipeline_model.delete_model()
+    sagemaker_session.delete_model.assert_called_with(pipeline_model.name)
diff --git a/tests/unit/test_predictor.py b/tests/unit/test_predictor.py
index 55ac1f5f9a..c03b3a338f 100644
--- a/tests/unit/test_predictor.py
+++ b/tests/unit/test_predictor.py
@@ -16,7 +16,7 @@
 import json
 import os
 import pytest
-from mock import Mock
+from mock import Mock, call
 
 import numpy as np
 
@@ -319,11 +319,22 @@ def test_numpy_deser_from_npy_object_array():
 RETURN_VALUE = 0
 CSV_RETURN_VALUE = "1,2,3\r\n"
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': ENDPOINT
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 def empty_sagemaker_session():
     ims = Mock(name='sagemaker_session')
     ims.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     ims.sagemaker_runtime_client = Mock(name='sagemaker_runtime')
+    ims.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    ims.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     response_body = Mock('body')
     response_body.read = Mock('read', return_value=RETURN_VALUE)
@@ -379,6 +390,9 @@ def json_sagemaker_session():
     ims.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     ims.sagemaker_runtime_client = Mock(name='sagemaker_runtime')
 
+    ims.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    ims.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
+
     response_body = Mock('body')
     response_body.read = Mock('read', return_value=json.dumps([RETURN_VALUE]))
     response_body.close = Mock('close', return_value=None)
@@ -417,6 +431,9 @@ def ret_csv_sagemaker_session():
     ims.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     ims.sagemaker_runtime_client = Mock(name='sagemaker_runtime')
 
+    ims.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    ims.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
+
     response_body = Mock('body')
     response_body.read = Mock('read', return_value=CSV_RETURN_VALUE)
     response_body.close = Mock('close', return_value=None)
@@ -466,3 +483,15 @@ def test_delete_endpoint_only():
 
     sagemaker_session.delete_endpoint.assert_called_with(ENDPOINT)
     sagemaker_session.delete_endpoint_config.assert_not_called()
+
+
+def test_delete_model():
+    sagemaker_session = empty_sagemaker_session()
+    predictor = RealTimePredictor(ENDPOINT, sagemaker_session=sagemaker_session)
+
+    predictor.delete_model()
+
+    expected_call_count = 2
+    expected_call_args_list = [call('model-1'), call('model-2')]
+    assert sagemaker_session.delete_model.call_count == expected_call_count
+    assert sagemaker_session.delete_model.call_args_list == expected_call_args_list
diff --git a/tests/unit/test_pytorch.py b/tests/unit/test_pytorch.py
index 20edf62640..3a71d320b8 100644
--- a/tests/unit/test_pytorch.py
+++ b/tests/unit/test_pytorch.py
@@ -43,6 +43,15 @@
 GPU = 'ml.p2.xlarge'
 CPU = 'ml.c4.xlarge'
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture(name='sagemaker_session')
 def fixture_sagemaker_session():
@@ -52,6 +61,8 @@ def fixture_sagemaker_session():
 
     describe = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/m.tar.gz'}}
     session.sagemaker_client.describe_training_job = Mock(return_value=describe)
+    session.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    session.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     session.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     session.expand_role = Mock(name="expand_role", return_value=ROLE)
     return session
diff --git a/tests/unit/test_randomcutforest.py b/tests/unit/test_randomcutforest.py
index d265d22ba6..561f7c29ac 100644
--- a/tests/unit/test_randomcutforest.py
+++ b/tests/unit/test_randomcutforest.py
@@ -38,6 +38,15 @@
     }
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -48,6 +57,8 @@ def sagemaker_session():
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.sagemaker_client.describe_training_job = Mock(name='describe_training_job',
                                                       return_value=DESCRIBE_TRAINING_JOB_RESULT)
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
 
     return sms
 
diff --git a/tests/unit/test_rl.py b/tests/unit/test_rl.py
index c9e28f3c23..a4657c901d 100644
--- a/tests/unit/test_rl.py
+++ b/tests/unit/test_rl.py
@@ -40,6 +40,15 @@
 GPU = 'ml.p2.xlarge'
 CPU = 'ml.c4.xlarge'
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture(name='sagemaker_session')
 def fixture_sagemaker_session():
@@ -49,6 +58,8 @@ def fixture_sagemaker_session():
 
     describe = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/m.tar.gz'}}
     session.sagemaker_client.describe_training_job = Mock(return_value=describe)
+    session.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    session.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     session.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     session.expand_role = Mock(name="expand_role", return_value=ROLE)
     return session
diff --git a/tests/unit/test_sklearn.py b/tests/unit/test_sklearn.py
index 5795aa3e90..9a3b199156 100644
--- a/tests/unit/test_sklearn.py
+++ b/tests/unit/test_sklearn.py
@@ -43,6 +43,15 @@
 REGION = 'us-west-2'
 CPU = 'ml.c4.xlarge'
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -52,6 +61,8 @@ def sagemaker_session():
 
     describe = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/m.tar.gz'}}
     session.sagemaker_client.describe_training_job = Mock(return_value=describe)
+    session.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    session.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     session.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     session.expand_role = Mock(name="expand_role", return_value=ROLE)
     return session
diff --git a/tests/unit/test_sparkml_serving.py b/tests/unit/test_sparkml_serving.py
index bbd588170d..bacf64a81f 100644
--- a/tests/unit/test_sparkml_serving.py
+++ b/tests/unit/test_sparkml_serving.py
@@ -26,6 +26,15 @@
 BUCKET_NAME = 'Some-Bucket'
 ENDPOINT = 'some-endpoint'
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': ENDPOINT
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -33,6 +42,8 @@ def sagemaker_session():
     sms = Mock(name='sagemaker_session', boto_session=boto_mock,
                region_name=REGION, config=None, local_mode=False)
     sms.boto_region_name = REGION
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     return sms
 
 
diff --git a/tests/unit/test_tf_estimator.py b/tests/unit/test_tf_estimator.py
index d6482ae479..e2777d0326 100644
--- a/tests/unit/test_tf_estimator.py
+++ b/tests/unit/test_tf_estimator.py
@@ -48,6 +48,15 @@
 DISTRIBUTION_ENABLED = {'parameter_server': {'enabled': True}}
 DISTRIBUTION_MPI_ENABLED = {'mpi': {'enabled': True, 'custom_mpi_options': 'options', 'processes_per_host': 2}}
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -58,6 +67,8 @@ def sagemaker_session():
     session.expand_role = Mock(name="expand_role", return_value=ROLE)
     describe = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/m.tar.gz'}}
     session.sagemaker_client.describe_training_job = Mock(return_value=describe)
+    session.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    session.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     return session
 
 
diff --git a/tests/unit/test_tf_predictor.py b/tests/unit/test_tf_predictor.py
index a9ff684df6..b58971adbf 100644
--- a/tests/unit/test_tf_predictor.py
+++ b/tests/unit/test_tf_predictor.py
@@ -43,12 +43,23 @@
 JSON_CONTENT_TYPE = "application/json"
 PROTO_CONTENT_TYPE = "application/octet-stream"
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': ENDPOINT
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
     boto_mock = Mock(name='boto_session', region_name=REGION)
     ims = Mock(name='sagemaker_session', boto_session=boto_mock)
     ims.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
+    ims.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    ims.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     return ims
 
 
diff --git a/tests/unit/test_tfs.py b/tests/unit/test_tfs.py
index e29e3d4098..77f68561a2 100644
--- a/tests/unit/test_tfs.py
+++ b/tests/unit/test_tfs.py
@@ -40,6 +40,15 @@
 }
 REGRESS_RESPONSE = {'results': [3.5, 4.0]}
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -50,6 +59,8 @@ def sagemaker_session():
     session.expand_role = Mock(name="expand_role", return_value=ROLE)
     describe = {'ModelArtifacts': {'S3ModelArtifacts': 's3://m/m.tar.gz'}}
     session.sagemaker_client.describe_training_job = Mock(return_value=describe)
+    session.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    session.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
     return session
 
 
@@ -191,14 +202,14 @@ def test_predictor_regress(sagemaker_session):
     assert REGRESS_RESPONSE == result
 
 
-def test_predictor_regress_bad_content_type():
+def test_predictor_regress_bad_content_type(sagemaker_session):
     predictor = Predictor('endpoint', sagemaker_session, csv_serializer)
 
     with pytest.raises(ValueError):
         predictor.regress(REGRESS_INPUT)
 
 
-def test_predictor_classify_bad_content_type():
+def test_predictor_classify_bad_content_type(sagemaker_session):
     predictor = Predictor('endpoint', sagemaker_session, csv_serializer)
 
     with pytest.raises(ValueError):
diff --git a/tests/unit/test_tuner.py b/tests/unit/test_tuner.py
index 76480d9cf5..4fec84965e 100644
--- a/tests/unit/test_tuner.py
+++ b/tests/unit/test_tuner.py
@@ -127,6 +127,15 @@
     'HyperParameterTuningJobArn': 'arn:tuning_job',
 }
 
+ENDPOINT_DESC = {
+    'EndpointConfigName': 'test-endpoint'
+}
+
+ENDPOINT_CONFIG_DESC = {
+    'ProductionVariants': [{'ModelName': 'model-1'},
+                           {'ModelName': 'model-2'}]
+}
+
 
 @pytest.fixture()
 def sagemaker_session():
@@ -135,6 +144,10 @@ def sagemaker_session():
     sms.boto_region_name = REGION
     sms.default_bucket = Mock(name='default_bucket', return_value=BUCKET_NAME)
     sms.config = None
+
+    sms.sagemaker_client.describe_endpoint = Mock(return_value=ENDPOINT_DESC)
+    sms.sagemaker_client.describe_endpoint_config = Mock(return_value=ENDPOINT_CONFIG_DESC)
+
     return sms