diff --git a/llama_stack/providers/remote/inference/sambanova/sambanova.py b/llama_stack/providers/remote/inference/sambanova/sambanova.py
index 20f863665..9c2dda889 100644
--- a/llama_stack/providers/remote/inference/sambanova/sambanova.py
+++ b/llama_stack/providers/remote/inference/sambanova/sambanova.py
@@ -7,6 +7,7 @@
 import json
 from collections.abc import Iterable
 
+import requests
 from openai.types.chat import (
     ChatCompletionAssistantMessageParam as OpenAIChatCompletionAssistantMessage,
 )
@@ -56,6 +57,7 @@ from llama_stack.apis.inference import (
     ToolResponseMessage,
     UserMessage,
 )
+from llama_stack.apis.models import Model
 from llama_stack.log import get_logger
 from llama_stack.models.llama.datatypes import BuiltinTool
 from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
@@ -176,10 +178,11 @@ class SambaNovaInferenceAdapter(LiteLLMOpenAIMixin):
 
     def __init__(self, config: SambaNovaImplConfig):
         self.config = config
+        self.environment_available_models = []
         LiteLLMOpenAIMixin.__init__(
             self,
             model_entries=MODEL_ENTRIES,
-            api_key_from_config=self.config.api_key,
+            api_key_from_config=self.config.api_key.get_secret_value() if self.config.api_key else None,
             provider_data_api_key_field="sambanova_api_key",
         )
 
@@ -246,6 +249,22 @@ class SambaNovaInferenceAdapter(LiteLLMOpenAIMixin):
             **get_sampling_options(request.sampling_params),
         }
 
+    async def register_model(self, model: Model) -> Model:
+        model_id = self.get_provider_model_id(model.provider_resource_id)
+
+        list_models_url = self.config.url + "/models"
+        if len(self.environment_available_models) == 0:
+            try:
+                response = requests.get(list_models_url)
+                response.raise_for_status()
+            except requests.exceptions.RequestException as e:
+                raise RuntimeError(f"Request to {list_models_url} failed") from e
+            self.environment_available_models = [model.get("id") for model in response.json().get("data", {})]
+
+        if model_id.split("sambanova/")[-1] not in self.environment_available_models:
+            logger.warning(f"Model {model_id} not available in {list_models_url}")
+        return model
+
     async def initialize(self):
         await super().initialize()
 
diff --git a/llama_stack/providers/remote/safety/sambanova/sambanova.py b/llama_stack/providers/remote/safety/sambanova/sambanova.py
index 84c8267ae..1a65f6aa1 100644
--- a/llama_stack/providers/remote/safety/sambanova/sambanova.py
+++ b/llama_stack/providers/remote/safety/sambanova/sambanova.py
@@ -33,6 +33,7 @@ CANNED_RESPONSE_TEXT = "I can't answer that. Can I help with something else?"
 class SambaNovaSafetyAdapter(Safety, ShieldsProtocolPrivate, NeedsRequestProviderData):
     def __init__(self, config: SambaNovaSafetyConfig) -> None:
         self.config = config
+        self.environment_available_models = []
 
     async def initialize(self) -> None:
         pass
@@ -54,18 +55,18 @@ class SambaNovaSafetyAdapter(Safety, ShieldsProtocolPrivate, NeedsRequestProvide
 
     async def register_shield(self, shield: Shield) -> None:
         list_models_url = self.config.url + "/models"
-        try:
-            response = requests.get(list_models_url)
-            response.raise_for_status()
-        except requests.exceptions.RequestException as e:
-            raise RuntimeError(f"Request to {list_models_url} failed") from e
-        available_models = [model.get("id") for model in response.json().get("data", {})]
+        if len(self.environment_available_models) == 0:
+            try:
+                response = requests.get(list_models_url)
+                response.raise_for_status()
+            except requests.exceptions.RequestException as e:
+                raise RuntimeError(f"Request to {list_models_url} failed") from e
+            self.environment_available_models = [model.get("id") for model in response.json().get("data", {})]
         if (
-            len(available_models) == 0
-            or "guard" not in shield.provider_resource_id.lower()
-            or shield.provider_resource_id.split("sambanova/")[-1] not in available_models
+            "guard" not in shield.provider_resource_id.lower()
+            or shield.provider_resource_id.split("sambanova/")[-1] not in self.environment_available_models
         ):
-            raise ValueError(f"Shield {shield.provider_resource_id} not found in SambaNova")
+            logger.warning(f"Shield {shield.provider_resource_id} not available in {list_models_url}")
 
     async def run_shield(
         self, shield_id: str, messages: list[Message], params: dict[str, Any] | None = None
diff --git a/tests/integration/inference/test_openai_completion.py b/tests/integration/inference/test_openai_completion.py
index 05aee5096..e82714ffd 100644
--- a/tests/integration/inference/test_openai_completion.py
+++ b/tests/integration/inference/test_openai_completion.py
@@ -71,7 +71,6 @@ def skip_if_model_doesnt_support_openai_chat_completion(client_with_models, mode
         "remote::cerebras",
         "remote::databricks",
         "remote::runpod",
-        "remote::sambanova",
         "remote::tgi",
     ):
         pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support OpenAI chat completions.")