diff --git a/optimum/exporters/openvino/convert.py b/optimum/exporters/openvino/convert.py
index c9e18cff6..66e6c13a2 100644
--- a/optimum/exporters/openvino/convert.py
+++ b/optimum/exporters/openvino/convert.py
@@ -100,9 +100,15 @@ def _set_runtime_options(
     for model_name in models_and_export_configs.keys():
         _, sub_export_config = models_and_export_configs[model_name]
         sub_export_config.runtime_options = {}
-        if "diffusers" in library_name or "text-generation" in task:
+        if (
+            "diffusers" in library_name
+            or "text-generation" in task
+            or ("image-text-to-text" in task and model_name == "language_model")
+        ):
             sub_export_config.runtime_options["ACTIVATIONS_SCALE_FACTOR"] = "8.0"
-        if not quantized_model and "text-generation" in task:
+        if not quantized_model and (
+            "text-generation" in task or ("image-text-to-text" in task and model_name == "language_model")
+        ):
             sub_export_config.runtime_options["KV_CACHE_PRECISION"] = "f16"
 
 
diff --git a/tests/openvino/test_export.py b/tests/openvino/test_export.py
index 2d57f92d0..55500471a 100644
--- a/tests/openvino/test_export.py
+++ b/tests/openvino/test_export.py
@@ -134,6 +134,14 @@ def _openvino_export(
                     self.assertTrue(ov_model.model.has_rt_info(["runtime_options", "ACTIVATIONS_SCALE_FACTOR"]))
                     self.assertTrue(ov_model.model.has_rt_info(["runtime_options", "KV_CACHE_PRECISION"]))
 
+                if task == "image-text-to-text":
+                    self.assertTrue(
+                        ov_model.language_model.model.has_rt_info(["runtime_options", "KV_CACHE_PRECISION"])
+                    )
+                    self.assertTrue(
+                        ov_model.language_model.model.has_rt_info(["runtime_options", "ACTIVATIONS_SCALE_FACTOR"])
+                    )
+
                 if library_name == "diffusers":
                     self.assertTrue(
                         ov_model.vae_encoder.model.has_rt_info(["runtime_options", "ACTIVATIONS_SCALE_FACTOR"])