diff --git a/optimum/intel/openvino/modeling.py b/optimum/intel/openvino/modeling.py
index 6d0af462cc..f6d3061a7a 100644
--- a/optimum/intel/openvino/modeling.py
+++ b/optimum/intel/openvino/modeling.py
@@ -554,7 +554,7 @@ def from_pretrained(
             model = TimmForImageClassification.from_pretrained(model_id, **kwargs)
             onnx_config = TimmOnnxConfig(model.config)
 
-            return cls._to_load(model=model, config=config, onnx_config=onnx_config, stateful=False)
+            return cls._to_load(model=model, config=config, onnx_config=onnx_config, stateful=False, **kwargs)
         else:
             return super().from_pretrained(
                 model_id=model_id,
diff --git a/tests/openvino/test_modeling.py b/tests/openvino/test_modeling.py
index f26bb92fb8..e51b50a5b2 100644
--- a/tests/openvino/test_modeling.py
+++ b/tests/openvino/test_modeling.py
@@ -748,6 +748,7 @@ def test_pipeline(self, model_arch):
     @parameterized.expand(TIMM_MODELS)
     def test_compare_to_timm(self, model_id):
         ov_model = OVModelForImageClassification.from_pretrained(model_id, export=True, ov_config=F32_CONFIG)
+        self.assertEqual(ov_model.request.get_property("INFERENCE_PRECISION_HINT").to_string(), "f32")
         self.assertIsInstance(ov_model.config, PretrainedConfig)
         timm_model = timm.create_model(model_id, pretrained=True)
         preprocessor = TimmImageProcessor.from_pretrained(model_id)