diff --git a/backends/openvino/preprocess.py b/backends/openvino/preprocess.py
index 6af45ff63f9..6380d0d3b78 100644
--- a/backends/openvino/preprocess.py
+++ b/backends/openvino/preprocess.py
@@ -44,7 +44,7 @@ def preprocess(
         for spec in module_compile_spec:
             compile_options[spec.key] = spec.value.decode()
 
-        compiled = openvino_compile(edge_program.module(), *args, options=compile_options, executorch=True)
+        compiled = openvino_compile(edge_program.module(), *args, options=compile_options)
         model_bytes = compiled.export_model()
 
         return PreprocessResult(processed_bytes=model_bytes)
diff --git a/backends/openvino/tests/models/test_classification.py b/backends/openvino/tests/models/test_classification.py
new file mode 100644
index 00000000000..59558b397ab
--- /dev/null
+++ b/backends/openvino/tests/models/test_classification.py
@@ -0,0 +1,34 @@
+from executorch.backends.openvino.tests.ops.base_openvino_op_test import BaseOpenvinoOpTest
+import torch
+import timm
+import torchvision.models as torchvision_models
+from transformers import AutoModel
+
+classifier_params = [
+                     {'model': ['torchvision', 'resnet50', (1, 3, 224, 224)] },
+                     {'model': ['torchvision', 'mobilenet_v2', (1, 3, 224, 224)] },
+                    ]
+
+# Function to load a model based on the selected suite
+def load_model(suite: str, model_name: str):
+    if suite == "timm":
+        return timm.create_model(model_name, pretrained=True)
+    elif suite == "torchvision":
+        if not hasattr(torchvision_models, model_name):
+            raise ValueError(f"Model {model_name} not found in torchvision.")
+        return getattr(torchvision_models, model_name)(pretrained=True)
+    elif suite == "huggingface":
+        return AutoModel.from_pretrained(model_name)
+    else:
+        raise ValueError(f"Unsupported model suite: {suite}")
+
+class TestClassifier(BaseOpenvinoOpTest):
+
+    def test_classifier(self):
+        for params in classifier_params:
+            with self.subTest(params=params):
+                module = load_model(params['model'][0], params['model'][1])
+
+                sample_input = (torch.randn(params['model'][2]),)
+
+                self.execute_layer_test(module, sample_input)
diff --git a/backends/openvino/tests/test_openvino_delegate.py b/backends/openvino/tests/test_openvino_delegate.py
index bbf61d1ea09..eaabcf2603b 100644
--- a/backends/openvino/tests/test_openvino_delegate.py
+++ b/backends/openvino/tests/test_openvino_delegate.py
@@ -40,16 +40,25 @@ def parse_arguments():
     parser.add_argument(
         "-p",
         "--pattern",
-        help="Pattern to match test files. Provide complete file name to run individual op tests",
+        help="Pattern to match test files. Provide complete file name to run individual tests",
         type=str,
         default="test_*.py",
     )
+    parser.add_argument(
+        "-t",
+        "--test_type",
+        help="Specify the type of tests ('ops' or 'models')",
+        type=str,
+        default="ops",
+        choices={"ops", "models"},
+    )
 
     args, ns_args = parser.parse_known_args(namespace=unittest)
     test_params = {}
     test_params["device"] = args.device
     test_params["build_folder"] = args.build_folder
     test_params["pattern"] = args.pattern
+    test_params["test_type"] = args.test_type
     return test_params
 
 if __name__ == "__main__":
@@ -60,6 +69,6 @@ def parse_arguments():
     test_params = parse_arguments()
     loader.suiteClass.test_params = test_params
     # Discover all existing op tests in "ops" folder
-    suite = loader.discover("ops", pattern=test_params['pattern'])
+    suite = loader.discover(test_params['test_type'], pattern=test_params['pattern'])
     # Start running tests
     unittest.TextTestRunner().run(suite)