diff --git a/integrations/meta_llama/tests/test_llama_chat_generator.py b/integrations/meta_llama/tests/test_llama_chat_generator.py
index 8c20a2b016..cb106d66fd 100644
--- a/integrations/meta_llama/tests/test_llama_chat_generator.py
+++ b/integrations/meta_llama/tests/test_llama_chat_generator.py
@@ -322,35 +322,6 @@ def test_live_run_wrong_model(self, chat_messages):
         with pytest.raises(OpenAIError):
             component.run(chat_messages)
 
-    @pytest.mark.skipif(
-        not os.environ.get("LLAMA_API_KEY", None),
-        reason="Export an env var called LLAMA_API_KEY containing the OpenAI API key to run this test.",
-    )
-    @pytest.mark.integration
-    def test_live_run_streaming(self):
-        class Callback:
-            def __init__(self):
-                self.responses = ""
-                self.counter = 0
-
-            def __call__(self, chunk: StreamingChunk) -> None:
-                self.counter += 1
-                self.responses += chunk.content if chunk.content else ""
-
-        callback = Callback()
-        component = MetaLlamaChatGenerator(streaming_callback=callback)
-        results = component.run([ChatMessage.from_user("What's the capital of France?")])
-
-        assert len(results["replies"]) == 1
-        message: ChatMessage = results["replies"][0]
-        assert "Paris" in message.text
-
-        assert "Llama-4-Scout-17B-16E-Instruct-FP8" in message.meta["model"]
-        assert message.meta["finish_reason"] == "stop"
-
-        assert callback.counter > 1
-        assert "Paris" in callback.responses
-
     @pytest.mark.skipif(
         not os.environ.get("LLAMA_API_KEY", None),
         reason="Export an env var called LLAMA_API_KEY containing the Llama API key to run this test.",
@@ -638,69 +609,3 @@ def tool_fn(city: str) -> str:
         )
 
         assert generator.tools == [weather_tool, toolset]
-
-    @pytest.mark.skipif(
-        not os.environ.get("LLAMA_API_KEY", None),
-        reason="Export an env var called LLAMA_API_KEY containing the OpenAI API key to run this test.",
-    )
-    @pytest.mark.integration
-    def test_live_run_with_mixed_tools(self, mixed_tools):
-        """
-        Integration test that verifies MetaLlamaChatGenerator works with mixed Tool and Toolset.
-        This tests that the LLM can correctly invoke tools from both a standalone Tool and a Toolset.
-        """
-        initial_messages = [
-            ChatMessage.from_user("What's the weather like in Paris and what is the population of Berlin?")
-        ]
-        # default model Llama-4-Scout-17B-16E-Instruct-FP8 can't handle multiple tool responses well
-        # we use stronger model Llama-4-Maverick-17B-128E-Instruct-FP8 for this test
-        component = MetaLlamaChatGenerator(model="Llama-4-Maverick-17B-128E-Instruct-FP8", tools=mixed_tools)
-        results = component.run(messages=initial_messages)
-
-        assert len(results["replies"]) > 0, "No replies received"
-
-        # Find the message with tool calls
-        tool_call_message = None
-        for message in results["replies"]:
-            if message.tool_calls:
-                tool_call_message = message
-                break
-
-        assert tool_call_message is not None, "No message with tool call found"
-        assert isinstance(tool_call_message, ChatMessage), "Tool message is not a ChatMessage instance"
-        assert ChatMessage.is_from(tool_call_message, ChatRole.ASSISTANT), "Tool message is not from the assistant"
-
-        tool_calls = tool_call_message.tool_calls
-        assert len(tool_calls) == 2, f"Expected 2 tool calls, got {len(tool_calls)}"
-
-        # Verify we got calls to both weather and population tools
-        tool_names = {tc.tool_name for tc in tool_calls}
-        assert "weather" in tool_names, "Expected 'weather' tool call"
-        assert "population" in tool_names, "Expected 'population' tool call"
-
-        # Verify tool call details
-        for tool_call in tool_calls:
-            assert tool_call.id, "Tool call does not contain value for 'id' key"
-            assert tool_call.tool_name in ["weather", "population"]
-            assert "city" in tool_call.arguments
-            assert tool_call.arguments["city"] in ["Paris", "Berlin"]
-            assert tool_call_message.meta["finish_reason"] == "tool_calls"
-
-        # Mock the response we'd get from ToolInvoker
-        tool_result_messages = []
-        for tool_call in tool_calls:
-            if tool_call.tool_name == "weather":
-                result = "The weather in Paris is sunny and 32°C"
-            else:  # population
-                result = "The population of Berlin is 2.2 million"
-            tool_result_messages.append(ChatMessage.from_tool(tool_result=result, origin=tool_call))
-
-        new_messages = [*initial_messages, tool_call_message, *tool_result_messages]
-        results = component.run(new_messages)
-
-        assert len(results["replies"]) == 1
-        final_message = results["replies"][0]
-        assert not final_message.tool_calls
-        assert len(final_message.text) > 0
-        assert "paris" in final_message.text.lower()
-        assert "berlin" in final_message.text.lower()