diff --git a/inference/core/registries/roboflow.py b/inference/core/registries/roboflow.py
index fddb1c0099..c706a5e834 100644
--- a/inference/core/registries/roboflow.py
+++ b/inference/core/registries/roboflow.py
@@ -43,6 +43,8 @@
 from inference.core.utils.roboflow import get_model_id_chunks
 from inference.models.aliases import resolve_roboflow_model_alias
 
+_MODEL_TYPE_CACHE = {}
+
 GENERIC_MODELS = {
     "clip": ("embed", "clip"),
     "sam": ("embed", "sam"),
@@ -88,12 +90,16 @@ def get_model(
         Raises:
             ModelNotRecognisedError: If the model type is not supported or found.
         """
-        model_type = get_model_type(
-            model_id,
-            api_key,
-            countinference=countinference,
-            service_secret=service_secret,
-        )
+        cache_key = (api_key, model_id, countinference, service_secret)
+        model_type = _MODEL_TYPE_CACHE.get(cache_key)
+        if model_type is None:
+            model_type = get_model_type(
+                model_id,
+                api_key,
+                countinference=countinference,
+                service_secret=service_secret,
+            )
+            _MODEL_TYPE_CACHE[cache_key] = model_type
         logger.debug(f"Model type: {model_type}")
 
         if model_type not in self.registry_dict:
@@ -162,7 +168,6 @@ def get_model_type(
     if dataset_id in GENERIC_MODELS:
         logger.debug(f"Loading generic model: {dataset_id}.")
         return GENERIC_MODELS[dataset_id]
-
     if MODELS_CACHE_AUTH_ENABLED:
         if not _check_if_api_key_has_access_to_model(
             api_key=api_key,
@@ -180,6 +185,7 @@ def get_model_type(
 
     if cached_metadata is not None:
         return cached_metadata[0], cached_metadata[1]
+
     if version_id == STUB_VERSION_ID:
         if api_key is None:
             raise MissingApiKeyError(
@@ -222,8 +228,6 @@ def get_model_type(
     # some older projects do not have type field - hence defaulting
     model_type = api_data.get("modelType")
     if model_type is None or model_type == "ort":
-        # some very old model versions do not have modelType reported - and API respond in a generic way -
-        # then we shall attempt using default model for given task type
         model_type = MODEL_TYPE_DEFAULTS.get(project_task_type)
     if model_type is None or project_task_type is None:
         raise ModelArtefactError("Error loading model artifacts from Roboflow API.")