diff --git a/bigframes/ml/llm.py b/bigframes/ml/llm.py
index 111ad20f8a..f93ba8b720 100644
--- a/bigframes/ml/llm.py
+++ b/bigframes/ml/llm.py
@@ -53,6 +53,7 @@
 _GEMINI_2_FLASH_EXP_ENDPOINT = "gemini-2.0-flash-exp"
 _GEMINI_2_FLASH_001_ENDPOINT = "gemini-2.0-flash-001"
 _GEMINI_2_FLASH_LITE_001_ENDPOINT = "gemini-2.0-flash-lite-001"
+_GEMINI_2P5_PRO_PREVIEW_ENDPOINT = "gemini-2.5-pro-preview-05-06"
 _GEMINI_ENDPOINTS = (
     _GEMINI_1P5_PRO_PREVIEW_ENDPOINT,
     _GEMINI_1P5_PRO_FLASH_PREVIEW_ENDPOINT,
@@ -104,6 +105,12 @@
 
 _REMOVE_DEFAULT_MODEL_WARNING = "Since upgrading the default model can cause unintended breakages, the default model will be removed in BigFrames 3.0. Please supply an explicit model to avoid this message."
 
+_GEMINI_MULTIMODAL_MODEL_NOT_SUPPORTED_WARNING = (
+    "The model '{model_name}' may not be fully supported by GeminiTextGenerator for Multimodal prompts. "
+    "GeminiTextGenerator is known to support the following models for Multimodal prompts: {known_models}. "
+    "If you proceed with '{model_name}', it might not work as expected or could lead to errors with multimodal inputs."
+)
+
 
 @log_adapter.class_logger
 class TextEmbeddingGenerator(base.RetriableRemotePredictor):
@@ -540,9 +547,10 @@ def fit(
             GeminiTextGenerator: Fitted estimator.
         """
         if self.model_name not in _GEMINI_FINE_TUNE_SCORE_ENDPOINTS:
-            raise NotImplementedError(
+            msg = exceptions.format_message(
                 "fit() only supports gemini-1.5-pro-002, or gemini-1.5-flash-002 model."
             )
+            warnings.warn(msg)
 
         X, y = utils.batch_convert_to_dataframe(X, y)
 
@@ -651,9 +659,13 @@ def predict(
 
         if prompt:
             if self.model_name not in _GEMINI_MULTIMODAL_ENDPOINTS:
-                raise NotImplementedError(
-                    f"GeminiTextGenerator only supports model_name {', '.join(_GEMINI_MULTIMODAL_ENDPOINTS)} for Multimodal prompt."
+                msg = exceptions.format_message(
+                    _GEMINI_MULTIMODAL_MODEL_NOT_SUPPORTED_WARNING.format(
+                        model_name=self.model_name,
+                        known_models=", ".join(_GEMINI_MULTIMODAL_ENDPOINTS),
+                    )
                 )
+                warnings.warn(msg)
 
             df_prompt = X[[X.columns[0]]].rename(
                 columns={X.columns[0]: "bigframes_placeholder_col"}
@@ -750,9 +762,10 @@ def score(
             raise RuntimeError("A model must be fitted before score")
 
         if self.model_name not in _GEMINI_FINE_TUNE_SCORE_ENDPOINTS:
-            raise NotImplementedError(
+            msg = exceptions.format_message(
                 "score() only supports gemini-1.5-pro-002, gemini-1.5-flash-2, gemini-2.0-flash-001, and gemini-2.0-flash-lite-001 model."
             )
+            warnings.warn(msg)
 
         X, y = utils.batch_convert_to_dataframe(X, y, session=self._bqml_model.session)
 
diff --git a/bigframes/ml/loader.py b/bigframes/ml/loader.py
index 83c665a50b..a6366273fe 100644
--- a/bigframes/ml/loader.py
+++ b/bigframes/ml/loader.py
@@ -66,6 +66,7 @@
         llm._GEMINI_2_FLASH_EXP_ENDPOINT: llm.GeminiTextGenerator,
         llm._GEMINI_2_FLASH_001_ENDPOINT: llm.GeminiTextGenerator,
         llm._GEMINI_2_FLASH_LITE_001_ENDPOINT: llm.GeminiTextGenerator,
+        llm._GEMINI_2P5_PRO_PREVIEW_ENDPOINT: llm.GeminiTextGenerator,
         llm._CLAUDE_3_HAIKU_ENDPOINT: llm.Claude3TextGenerator,
         llm._CLAUDE_3_SONNET_ENDPOINT: llm.Claude3TextGenerator,
         llm._CLAUDE_3_5_SONNET_ENDPOINT: llm.Claude3TextGenerator,