diff --git a/examples/foundational/26d-gemini-live-text.py b/examples/foundational/26d-gemini-live-text.py
deleted file mode 100644
index 05b3bdce9..000000000
--- a/examples/foundational/26d-gemini-live-text.py
+++ /dev/null
@@ -1,142 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import LLMRunFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService, GeminiModalities
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-
-SYSTEM_INSTRUCTION = f"""
-"You are Gemini Chatbot, a friendly, helpful robot.
-
-Your goal is to demonstrate your capabilities in a succinct way.
-
-Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points.
-
-Respond to what the user said in a creative and helpful way. Keep your responses brief. One or two sentences at most.
-"""
-
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    # KNOWN ISSUE: If using GeminiLiveVertexLLMService, you cannot specify a
-    # modality other than AUDIO (at least not if using the service's default
-    # model, which is a native audio model:
-    # https://cloud.google.com/vertex-ai/generative-ai/docs/live-api/tools#native-audio).
-    llm = GeminiLiveLLMService(
-        api_key=os.getenv("GOOGLE_API_KEY"),
-        settings=GeminiLiveLLMService.Settings(
-            system_instruction=SYSTEM_INSTRUCTION,
-            modalities=GeminiModalities.TEXT,
-        ),
-        tools=[{"google_search": {}}, {"code_execution": {}}],
-    )
-
-    # Optionally, you can set the response modalities via a function
-    # llm.set_model_modalities(
-    #     GeminiMultimodalModalities.TEXT
-    # )
-
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121"
-    )
-
-    messages = [
-        {
-            "role": "developer",
-            "content": 'Start by saying "Hello, I\'m Gemini".',
-        },
-    ]
-
-    # Set up conversation context and management
-    # The context_aggregator will automatically collect conversation context
-    context = LLMContext(messages)
-    # Server-side VAD is enabled by default; no local VAD is added.
-    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(context)
-
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            user_aggregator,
-            llm,
-            tts,
-            transport.output(),
-            assistant_aggregator,
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected")
-        # Kick off the conversation.
-        await task.queue_frames([LLMRunFrame()])
-
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info(f"Client disconnected")
-        await task.cancel()
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()
diff --git a/src/pipecat/services/google/gemini_live/llm.py b/src/pipecat/services/google/gemini_live/llm.py
index f58972ea4..544efdc77 100644
--- a/src/pipecat/services/google/gemini_live/llm.py
+++ b/src/pipecat/services/google/gemini_live/llm.py
@@ -787,6 +787,13 @@ class GeminiLiveLLMService(LLMService):
         if settings is not None:
             default_settings.apply_update(settings)
 
+        # Warn if user requested TEXT modality
+        if default_settings.modalities == GeminiModalities.TEXT:
+            logger.warning(
+                f"Modality {default_settings.modalities.value!r} may not be supported by recent "
+                "Gemini Live models."
+            )
+
         super().__init__(
             base_url=base_url,
             settings=default_settings,
@@ -920,6 +927,10 @@ class GeminiLiveLLMService(LLMService):
         Args:
             modalities: The modalities to use for responses.
         """
+        if modalities == GeminiModalities.TEXT:
+            logger.warning(
+                f"Modality {modalities.value!r} may not be supported by recent Gemini Live models."
+            )
         self._settings.modalities = modalities
 
     def set_language(self, language: Language):