diff --git a/src/sagemaker/fw_utils.py b/src/sagemaker/fw_utils.py
index ef99454a45..613bbd3742 100644
--- a/src/sagemaker/fw_utils.py
+++ b/src/sagemaker/fw_utils.py
@@ -835,6 +835,52 @@ def validate_pytorch_distribution(
         raise ValueError(err_msg)
 
 
+def validate_distribution_instance(sagemaker_session, distribution, instance_type):
+    """Check to prevent launching a modelparallel job on CPU only instances.
+
+    Args:
+        sagemaker_session (sagemaker.session.Session): Session object which
+            manages interactions with Amazon SageMaker APIs and any other
+            AWS services needed.
+        distribution (dict): A dictionary with information to enable distributed training.
+            distribution = {
+                "smdistributed": {
+                    "modelparallel": {
+                        "enabled": True,
+                        "parameters": {
+                            ...
+                        },
+                    },
+                },
+                ...
+            }
+        instance_type (str): A string representing the type of training instance selected.
+
+    Raises:
+        ValueError: when modelparallel is enabled, if the instance_type does not support GPU.
+    """
+    if "smdistributed" not in distribution:
+        # Distribution strategy other than smdistributed is selected
+        return
+
+    if "modelparallel" not in distribution["smdistributed"]:
+        # Strategy other than modelparallel is selected
+        return
+
+    if not distribution["smdistributed"]["modelparallel"]["enabled"]:
+        # Strategy modelparallel is not enabled
+        return
+
+    instance_desc = sagemaker_session.boto_session.client("ec2").describe_instance_types(
+        InstanceTypes=[f"{instance_type}"]
+    )
+    if "GpuInfo" not in instance_desc["InstanceTypes"][0]:
+        raise ValueError(
+            f"modelparallel only runs on GPU-enabled instances. "
+            f"{instance_type} does not support GPU."
+        )
+
+
 def python_deprecation_warning(framework, latest_supported_version):
     """Placeholder docstring"""
     return PYTHON_2_DEPRECATION_WARNING.format(
diff --git a/src/sagemaker/pytorch/estimator.py b/src/sagemaker/pytorch/estimator.py
index 153d4656d4..622e79084c 100644
--- a/src/sagemaker/pytorch/estimator.py
+++ b/src/sagemaker/pytorch/estimator.py
@@ -25,6 +25,7 @@
     python_deprecation_warning,
     validate_version_or_image_args,
     validate_distribution,
+    validate_distribution_instance,
 )
 from sagemaker.pytorch import defaults
 from sagemaker.pytorch.model import PyTorchModel
@@ -220,6 +221,12 @@ def __init__(
             entry_point, source_dir, hyperparameters, image_uri=image_uri, **kwargs
         )
         if distribution is not None:
+            instance_type = self._get_instance_type()
+            # remove "ml." prefix
+            if instance_type[:3] == "ml.":
+                instance_type = instance_type[3:]
+            validate_distribution_instance(self.sagemaker_session, distribution, instance_type)
+
             distribution = validate_distribution(
                 distribution,
                 self.instance_groups,
diff --git a/tests/unit/test_fw_utils.py b/tests/unit/test_fw_utils.py
index 018255cf47..5ecf196731 100644
--- a/tests/unit/test_fw_utils.py
+++ b/tests/unit/test_fw_utils.py
@@ -49,6 +49,15 @@ def sagemaker_session():
     session_mock.sagemaker_client.describe_training_job = Mock(
         return_value={"ModelArtifacts": {"S3ModelArtifacts": "s3://m/m.tar.gz"}}
     )
+    session_mock.boto_session.client("ec2").describe_instance_types = Mock(
+        return_value={
+            "InstanceTypes": [
+                {
+                    "CpuInfo": {},
+                },
+            ],
+        }
+    )
     return session_mock
 
 
@@ -733,6 +742,31 @@ def test_validate_smdistributed_not_raises():
             )
 
 
+def test_validate_distribution_instance_no_smdistributed(sagemaker_session):
+    distribution = {}
+    instance_type = "mock_type"
+    fw_utils.validate_distribution_instance(sagemaker_session, distribution, instance_type)
+
+
+def test_validate_distribution_instance_no_modelparallel(sagemaker_session):
+    distribution = {"smdistributed": {}}
+    instance_type = "mock_type"
+    fw_utils.validate_distribution_instance(sagemaker_session, distribution, instance_type)
+
+
+def test_validate_distribution_instance_disabled_modelparallel(sagemaker_session):
+    distribution = {"smdistributed": {"modelparallel": {"enabled": False}}}
+    instance_type = "mock_type"
+    fw_utils.validate_distribution_instance(sagemaker_session, distribution, instance_type)
+
+
+def test_validate_distribution_instance_raise(sagemaker_session):
+    distribution = {"smdistributed": {"modelparallel": {"enabled": True}}}
+    instance_type = "mock_type"
+    with pytest.raises(ValueError):
+        fw_utils.validate_distribution_instance(sagemaker_session, distribution, instance_type)
+
+
 def test_validate_smdistributed_raises():
     bad_args = [
         {"smdistributed": "dummy"},