diff --git a/llama_stack/providers/remote/inference/ollama/ollama.py b/llama_stack/providers/remote/inference/ollama/ollama.py
index 58f92c829..89dc5d093 100644
--- a/llama_stack/providers/remote/inference/ollama/ollama.py
+++ b/llama_stack/providers/remote/inference/ollama/ollama.py
@@ -419,9 +419,10 @@ class OllamaInferenceAdapter(
             prompt_tokens=response.usage.prompt_tokens,
             total_tokens=response.usage.total_tokens,
         )
+        # TODO: Investigate why model_obj.identifier is used instead of response.model
         return OpenAIEmbeddingsResponse(
             data=data,
-            model=response.model,
+            model=model_obj.identifier,
             usage=usage,
         )
 
diff --git a/tests/integration/inference/test_openai_embeddings.py b/tests/integration/inference/test_openai_embeddings.py
index 1b8bd9038..40a0984da 100644
--- a/tests/integration/inference/test_openai_embeddings.py
+++ b/tests/integration/inference/test_openai_embeddings.py
@@ -55,6 +55,12 @@ def skip_if_model_doesnt_support_openai_embeddings(client, model_id):
         pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support OpenAI embeddings.")
 
 
+def skip_if_client_doesnt_support_base64_encoding(client, model_id):
+    provider = provider_from_model(client, model_id)
+    if provider.provider_type in ("remote::ollama",):
+        pytest.skip(f"Client {client} doesn't support base64 encoding for embeddings.")
+
+
 @pytest.fixture
 def openai_client(client_with_models):
     base_url = f"{client_with_models.base_url}/v1/openai/v1"
@@ -247,6 +253,7 @@ def test_openai_embeddings_with_encoding_format_base64(compat_client, client_wit
 def test_openai_embeddings_base64_batch_processing(compat_client, client_with_models, embedding_model_id):
     """Test OpenAI embeddings endpoint with base64 encoding for batch processing."""
     skip_if_model_doesnt_support_openai_embeddings(client_with_models, embedding_model_id)
+    skip_if_client_doesnt_support_base64_encoding(client_with_models, embedding_model_id)
 
     input_texts = ["First text for base64", "Second text for base64", "Third text for base64"]