diff --git a/tests/e2e/llm_translation/test_embeddings_endpoint_e2e.py b/tests/e2e/llm_translation/test_embeddings_endpoint_e2e.py
index 56f2de8bd4f..d365beee84b 100644
--- a/tests/e2e/llm_translation/test_embeddings_endpoint_e2e.py
+++ b/tests/e2e/llm_translation/test_embeddings_endpoint_e2e.py
@@ -1,9 +1,7 @@
 """Live e2e: POST /embeddings returns a real vector.
 
-Registers an OpenAI embedding deployment at runtime and asserts a non-empty,
-non-zero vector came back. Migrated from
-litellm-regression-tests/tests/test_inference_endpoints.py; the LIT-3167 guard in
-tests/e2e/embeddings/ covers the Gemini embedding path.
+Registers embedding deployments at runtime (OpenAI + Vertex) and asserts a
+non-empty, non-zero vector came back.
 """
 
 from __future__ import annotations
@@ -20,6 +18,7 @@ pytestmark = pytest.mark.e2e
 
 
 class TestEmbeddingsEndpoint:
+    @pytest.mark.covers("llm.embeddings.openai.basic.nonstream.works")
     def test_embeddings_returns_vector(
         self, endpoints_client: EndpointsClient, resources: ResourceManager
     ) -> None:
@@ -40,3 +39,28 @@ class TestEmbeddingsEndpoint:
         assert any(component != 0.0 for component in parsed.first_vector), (
             f"embedding vector is all zeros: {result.body[:300]}"
         )
+
+    @pytest.mark.covers("llm.embeddings.vertex.basic.nonstream.works")
+    def test_vertex_embeddings_returns_vector(
+        self, endpoints_client: EndpointsClient, resources: ResourceManager
+    ) -> None:
+        model = f"e2e-embeddings-vertex-{unique_marker()}"
+        model_id = endpoints_client.create_model(
+            model,
+            LiteLLMParamsBody(
+                model="vertex_ai/text-embedding-005",
+                vertex_project="os.environ/VERTEXAI_PROJECT",
+                vertex_location="us-central1",
+                vertex_credentials="os.environ/VERTEXAI_CREDENTIALS",
+            ),
+        )
+        resources.defer(lambda: endpoints_client.delete_model(model_id))
+        key = resources.key()
+
+        result = endpoints_client.embeddings(key, model, "Say this is a test!")
+        require_successful_call(result)
+        parsed = EmbeddingsResult.model_validate_json(result.body)
+        assert parsed.first_vector, f"vertex /embeddings returned no vector: {result.body[:300]}"
+        assert any(component != 0.0 for component in parsed.first_vector), (
+            f"vertex embedding vector is all zeros: {result.body[:300]}"
+        )
diff --git a/tests/e2e/llm_translation/test_responses_e2e.py b/tests/e2e/llm_translation/test_responses_e2e.py
index 2188bcc7f29..350748ca3d3 100644
--- a/tests/e2e/llm_translation/test_responses_e2e.py
+++ b/tests/e2e/llm_translation/test_responses_e2e.py
@@ -237,6 +237,74 @@ class TestResponses:
             f"got {result.response_cost!r}"
         )
 
+    @pytest.mark.covers("llm.responses.vertex.basic.nonstream.works")
+    def test_responses_vertex_returns_completion(
+        self, endpoints_client: EndpointsClient, resources: ResourceManager
+    ) -> None:
+        model = f"e2e-responses-vertex-{unique_marker()}"
+        model_id = endpoints_client.create_model(model, _vertex_gemini_params())
+        resources.defer(lambda: endpoints_client.delete_model(model_id))
+        key = resources.key()
+
+        result = endpoints_client.responses(key, model, "reply with one word")
+        require_successful_call(result)
+        assert result.call_id, "Responses→Vertex must set x-litellm-call-id"
+        parsed = ResponsesResult.model_validate_json(result.body)
+        assert parsed.text.strip(), f"/responses vertex returned no output text: {result.body[:300]}"
+        assert result.response_cost is not None and result.response_cost > 0, (
+            f"Responses→Vertex must set x-litellm-response-cost > 0; got {result.response_cost!r}"
+        )
+
+    @pytest.mark.covers("llm.responses.vertex.tool_use.nonstream.works")
+    def test_responses_vertex_returns_function_call(
+        self, endpoints_client: EndpointsClient, resources: ResourceManager
+    ) -> None:
+        model = f"e2e-responses-vertex-{unique_marker()}"
+        model_id = endpoints_client.create_model(model, _vertex_gemini_params())
+        resources.defer(lambda: endpoints_client.delete_model(model_id))
+        key = resources.key()
+
+        result = endpoints_client.responses_with_tools(
+            key,
+            model,
+            "What is the weather in San Francisco? Use the get_weather tool.",
+            [
+                ResponsesFunctionTool(
+                    name="get_weather",
+                    description="Get the weather for a location",
+                    parameters=FunctionParameters(
+                        properties={"location": FunctionParameterProperty(type="string")},
+                        required=["location"],
+                    ),
+                )
+            ],
+        )
+        require_successful_call(result)
+        parsed = ResponsesResult.model_validate_json(result.body)
+        function_call = next(
+            (call for call in parsed.function_calls if call.name == "get_weather"),
+            None,
+        )
+        assert function_call is not None, (
+            f"vertex responses returned no get_weather function call: {result.body[:500]}"
+        )
+        assert function_call.arguments is not None
+        raw_arguments = cast(object, json.loads(function_call.arguments))
+        arguments = WeatherArguments.model_validate(raw_arguments)
+        assert arguments.location, (
+            f"vertex function call arguments missing location: {function_call.arguments}"
+        )
+
+
+def _vertex_gemini_params() -> LiteLLMParamsBody:
+    """Vertex Gemini via gateway-held SA (os.environ/* resolved on the proxy)."""
+    return LiteLLMParamsBody(
+        model="vertex_ai/gemini-2.5-flash",
+        vertex_project="os.environ/VERTEXAI_PROJECT",
+        vertex_location="us-central1",
+        vertex_credentials="os.environ/VERTEXAI_CREDENTIALS",
+    )
+
 
 def _parse_stream_event(
     event: str,
diff --git a/tests/e2e/management/test_management_e2e.py b/tests/e2e/management/test_management_e2e.py
index adbf3e8b065..34a499ab364 100644
--- a/tests/e2e/management/test_management_e2e.py
+++ b/tests/e2e/management/test_management_e2e.py
@@ -189,6 +189,20 @@ class TestTeamRoutes:
             f"key generated under team {team_id} carries team_id {key_info.team_id!r} in /key/info"
         )
 
+    @pytest.mark.covers("mgmt.team.new.persists")
+    def test_team_model_allowlist_enforced_on_chat(
+        self, client: ManagementClient, resources: ResourceManager
+    ) -> None:
+        """Team-scoped keys only reach models on the team's allow-list (central for
+        org/team access control). Allowed model is callable; a sibling model is 403."""
+        team_id = _create_team(
+            client, resources, f"e2e-mgmt-team-{unique_marker()}", ["gemini-2.5-flash"]
+        )
+        key = _generate_key(client, resources, KeyGenerateBody(team_id=team_id))
+
+        _poll_chat_ok(client, key, "gemini-2.5-flash")
+        _poll_chat_denied(client, key, "gpt-5.5")
+
     @pytest.mark.covers("mgmt.team.member_add.persists")
     def test_member_add_and_delete_persist_to_team_info(
         self, client: ManagementClient, resources: ResourceManager