diff --git a/src/llamafactory/data/mm_plugin.py b/src/llamafactory/data/mm_plugin.py
index e9df7e33..b41e84fd 100644
--- a/src/llamafactory/data/mm_plugin.py
+++ b/src/llamafactory/data/mm_plugin.py
@@ -167,16 +167,45 @@ class MMPluginMixin:
             )
 
         if self.image_token is not None and processor is None:
-            raise ValueError("Processor was not found, please check and update your processor config.")
+            raise ValueError("Processor was not found, please check and update your model file.")
 
         if self.image_token is not None and image_processor is None:
-            raise ValueError("Image processor was not found, please check and update your processor config.")
+            raise ValueError("Image processor was not found, please check and update your model file.")
 
         if self.video_token is not None and video_processor is None:
-            raise ValueError("Video processor was not found, please check and update your processor config.")
+            raise ValueError("Video processor was not found, please check and update your model file.")
 
         if self.audio_token is not None and feature_extractor is None:
-            raise ValueError("Audio feature extractor was not found, please check and update your processor config.")
+            raise ValueError("Audio feature extractor was not found, please check and update your model file.")
+
+    def _validate_messages(
+        self,
+        messages: list[dict[str, str]],
+        images: list["ImageInput"],
+        videos: list["VideoInput"],
+        audios: list["AudioInput"],
+    ):
+        r"""Validate if the number of images, videos and audios match the number of placeholders in messages."""
+        num_image_tokens, num_video_tokens, num_audio_tokens = 0, 0, 0
+        for message in messages:
+            num_image_tokens += message["content"].count(IMAGE_PLACEHOLDER)
+            num_video_tokens += message["content"].count(VIDEO_PLACEHOLDER)
+            num_audio_tokens += message["content"].count(AUDIO_PLACEHOLDER)
+
+        if len(images) != num_image_tokens:
+            raise ValueError(
+                f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens in {messages}."
+            )
+
+        if len(videos) != num_video_tokens:
+            raise ValueError(
+                f"The number of videos does not match the number of {VIDEO_PLACEHOLDER} tokens in {messages}."
+            )
+
+        if len(audios) != num_audio_tokens:
+            raise ValueError(
+                f"The number of audios does not match the number of {AUDIO_PLACEHOLDER} tokens in {messages}."
+            )
 
     def _preprocess_image(
         self, image: "ImageObject", image_max_pixels: int, image_min_pixels: int, **kwargs
@@ -364,6 +393,7 @@ class BasePlugin(MMPluginMixin):
     ) -> list[dict[str, str]]:
         r"""Pre-process input messages before tokenization for VLMs."""
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         return messages
 
     def process_token_ids(
@@ -420,6 +450,7 @@ class Gemma3Plugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens = 0
         messages = deepcopy(messages)
         boi_token: str = getattr(processor, "boi_token")
@@ -446,9 +477,6 @@ class Gemma3Plugin(BasePlugin):
 
             message["content"] = content.replace("{{image}}", image_str)
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -566,8 +594,8 @@ class InternVLPlugin(BasePlugin):
         processor: Optional["ProcessorMixin"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
-        num_image_tokens = 0
-        num_video_tokens = 0
+        self._validate_messages(messages, images, videos, audios)
+        num_image_tokens, num_video_tokens = 0, 0
         image_seqlen = getattr(processor, "image_seq_length") if self.expand_mm_tokens else 1
         messages = deepcopy(messages)
         mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
@@ -579,9 +607,6 @@ class InternVLPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 content = content.replace(
                     IMAGE_PLACEHOLDER,
                     f"<img>{'<IMG_CONTEXT>' * image_seqlen * image_pixel_patch_list[num_image_tokens]}</img>",
@@ -590,9 +615,6 @@ class InternVLPlugin(BasePlugin):
                 num_image_tokens += 1
 
             while VIDEO_PLACEHOLDER in content:
-                if num_video_tokens >= len(videos):
-                    raise ValueError(f"`len(videos)` is less than the number of {VIDEO_PLACEHOLDER} tokens.")
-
                 current_patch_index = video_patch_indices[num_video_tokens - 1] if num_video_tokens > 0 else 0
                 end_patch_index = video_patch_indices[num_video_tokens]
                 num_patches = list(video_num_patches[current_patch_index:end_patch_index])
@@ -605,12 +627,6 @@ class InternVLPlugin(BasePlugin):
 
             message["content"] = content
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
-        if len(videos) != num_video_tokens:
-            raise ValueError(f"The number of videos does not match the number of {VIDEO_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -637,6 +653,7 @@ class KimiVLPlugin(BasePlugin):
     @override
     def process_messages(self, messages, images, videos, audios, processor):
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         if self.expand_mm_tokens:
             mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
 
@@ -648,9 +665,6 @@ class KimiVLPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 image_seqlen = image_grid_hws[num_image_tokens].prod() // merge_length if self.expand_mm_tokens else 1
                 content = content.replace(
                     IMAGE_PLACEHOLDER,
@@ -661,9 +675,6 @@ class KimiVLPlugin(BasePlugin):
 
             message["content"] = content
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
 
@@ -679,6 +690,7 @@ class Llama4Plugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         if self.expand_mm_tokens:
             mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
             if "pixel_values" in mm_inputs:
@@ -701,9 +713,6 @@ class Llama4Plugin(BasePlugin):
                 for local_image_index, split_part in enumerate(prompt_splits):
                     new_content.append(split_part)
                     if local_image_index < placeholder_count:
-                        if num_image_tokens >= len(images):
-                            raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                         tokens_for_this_image = processor._prompt_split_image(
                             aspect_ratios[num_image_tokens], num_patches_per_chunk
                         )
@@ -716,9 +725,6 @@ class Llama4Plugin(BasePlugin):
 
             message["content"] = content
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -751,7 +757,7 @@ class LlavaPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
-        num_image_tokens = 0
+        self._validate_messages(messages, images, videos, audios)
         messages = deepcopy(messages)
         if self.expand_mm_tokens:
             mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
@@ -768,17 +774,10 @@ class LlavaPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 content = content.replace(IMAGE_PLACEHOLDER, "{{image}}" * image_seqlen, 1)
-                num_image_tokens += 1
 
             message["content"] = content.replace("{{image}}", self.image_token)
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
 
@@ -794,6 +793,7 @@ class LlavaNextPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens = 0
         messages = deepcopy(messages)
         if self.expand_mm_tokens:
@@ -805,9 +805,6 @@ class LlavaNextPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 if self.expand_mm_tokens:
                     orig_height, orig_width = next(image_sizes)
                     image_seqlen = processor._get_number_of_features(orig_height, orig_width, height, width)
@@ -821,9 +818,6 @@ class LlavaNextPlugin(BasePlugin):
 
             message["content"] = content.replace("{{image}}", self.image_token)
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
 
@@ -839,7 +833,7 @@ class LlavaNextVideoPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
-        num_image_tokens, num_video_tokens = 0, 0
+        self._validate_messages(messages, images, videos, audios)
         messages = deepcopy(messages)
         if self.expand_mm_tokens:
             mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
@@ -850,9 +844,6 @@ class LlavaNextVideoPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 if self.expand_mm_tokens:
                     orig_height, orig_width = next(image_sizes)
                     image_seqlen = processor._get_number_of_features(orig_height, orig_width, height, width)
@@ -862,7 +853,6 @@ class LlavaNextVideoPlugin(BasePlugin):
                     image_seqlen = 1
 
                 content = content.replace(IMAGE_PLACEHOLDER, "{{image}}" * image_seqlen, 1)
-                num_image_tokens += 1
 
             message["content"] = content.replace("{{image}}", self.image_token)
 
@@ -879,20 +869,10 @@ class LlavaNextVideoPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while VIDEO_PLACEHOLDER in content:
-                if num_video_tokens >= len(videos):
-                    raise ValueError(f"`len(videos)` is less than the number of {VIDEO_PLACEHOLDER} tokens.")
-
                 content = content.replace(VIDEO_PLACEHOLDER, "{{video}}" * video_seqlen, 1)
-                num_video_tokens += 1
 
             message["content"] = content.replace("{{video}}", self.video_token)
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
-        if len(videos) != num_video_tokens:
-            raise ValueError(f"The number of videos does not match the number of {VIDEO_PLACEHOLDER} tokens.")
-
         return messages
 
 
@@ -978,6 +958,7 @@ class MiniCPMVPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens, num_video_tokens, num_audio_tokens = 0, 0, 0
         messages = deepcopy(messages)
         image_processor: BaseImageProcessor = getattr(processor, "image_processor")
@@ -996,24 +977,15 @@ class MiniCPMVPlugin(BasePlugin):
         for i, message in enumerate(messages):
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 content = content.replace(IMAGE_PLACEHOLDER, "{{image}}", 1)
                 num_image_tokens += 1
 
             while VIDEO_PLACEHOLDER in content:
-                if num_video_tokens >= len(videos):
-                    raise ValueError(f"`len(videos)` is less than the number of {VIDEO_PLACEHOLDER} tokens.")
-
                 video_seqlen = len(mm_inputs["pixel_values"][num_video_tokens]) if self.expand_mm_tokens else 1
                 content = content.replace(VIDEO_PLACEHOLDER, "{{image}}" * video_seqlen, 1)
                 num_video_tokens += 1
 
             while AUDIO_PLACEHOLDER in content:
-                if num_audio_tokens >= len(audios):
-                    raise ValueError(f"`len(audios)` is less than the number of {AUDIO_PLACEHOLDER} tokens.")
-
                 content = content.replace(AUDIO_PLACEHOLDER, "{{audio}}", 1)
                 num_audio_tokens += 1
 
@@ -1065,15 +1037,6 @@ class MiniCPMVPlugin(BasePlugin):
                 final_text += text_chunks[-1]
                 messages[index]["content"] = final_text
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
-        if len(videos) != num_video_tokens:
-            raise ValueError(f"The number of videos does not match the number of {VIDEO_PLACEHOLDER} tokens.")
-
-        if len(audios) != num_audio_tokens:
-            raise ValueError(f"The number of audios does not match the number of {AUDIO_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -1157,6 +1120,7 @@ class MllamaPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens = 0
         messages = deepcopy(messages)
         for message in messages:
@@ -1164,9 +1128,6 @@ class MllamaPlugin(BasePlugin):
             num_image_tokens += content.count(IMAGE_PLACEHOLDER)
             message["content"] = content.replace(IMAGE_PLACEHOLDER, self.image_token)
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -1214,6 +1175,7 @@ class PaliGemmaPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens = 0
         messages = deepcopy(messages)
         for message in messages:
@@ -1224,9 +1186,6 @@ class PaliGemmaPlugin(BasePlugin):
 
             message["content"] = content
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -1281,7 +1240,7 @@ class PixtralPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
-        num_image_tokens = 0
+        self._validate_messages(messages, images, videos, audios)
         messages = deepcopy(messages)
         if self.expand_mm_tokens:
             mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
@@ -1291,15 +1250,13 @@ class PixtralPlugin(BasePlugin):
                     image_sizes = iter(mm_inputs["image_sizes"][0])
                 else:
                     image_sizes = iter(mm_inputs["image_sizes"].tolist())
+
                 image_break_token: str = getattr(processor, "image_break_token")
                 image_end_token: str = getattr(processor, "image_end_token")
 
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 if self.expand_mm_tokens:
                     height, width = next(image_sizes)
                     num_height_tokens = height // processor.patch_size
@@ -1312,13 +1269,9 @@ class PixtralPlugin(BasePlugin):
                     replace_str = self.image_token
 
                 content = content.replace(IMAGE_PLACEHOLDER, replace_str, 1)
-                num_image_tokens += 1
 
             message["content"] = content
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -1355,9 +1308,9 @@ class Qwen2AudioPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         bos_token: str = getattr(processor, "audio_bos_token")
         eos_token: str = getattr(processor, "audio_eos_token")
-        num_audio_tokens = 0
         messages = deepcopy(messages)
         if self.expand_mm_tokens:
             mm_inputs = self._get_mm_inputs([], [], audios, processor)
@@ -1367,9 +1320,6 @@ class Qwen2AudioPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while AUDIO_PLACEHOLDER in content:
-                if num_audio_tokens >= len(audios):
-                    raise ValueError(f"`len(audios)` is less than the number of {AUDIO_PLACEHOLDER} tokens.")
-
                 if self.expand_mm_tokens:
                     audio_length = audio_lengths.pop(0)
                     input_length = (audio_length - 1) // 2 + 1
@@ -1380,13 +1330,9 @@ class Qwen2AudioPlugin(BasePlugin):
                 content = content.replace(
                     AUDIO_PLACEHOLDER, f"{bos_token}{self.audio_token * audio_seqlen}{eos_token}", 1
                 )
-                num_audio_tokens += 1
 
             message["content"] = content
 
-        if len(audios) != num_audio_tokens:
-            raise ValueError(f"The number of audios does not match the number of {AUDIO_PLACEHOLDER} tokens.")
-
         return messages
 
     @override
@@ -1494,6 +1440,7 @@ class Qwen2VLPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens, num_video_tokens = 0, 0
         messages = deepcopy(messages)
         image_processor: BaseImageProcessor = getattr(processor, "image_processor")
@@ -1510,9 +1457,6 @@ class Qwen2VLPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 image_seqlen = image_grid_thw[num_image_tokens].prod() // merge_length if self.expand_mm_tokens else 1
                 content = content.replace(
                     IMAGE_PLACEHOLDER, f"<|vision_start|>{self.image_token * image_seqlen}<|vision_end|>", 1
@@ -1520,9 +1464,6 @@ class Qwen2VLPlugin(BasePlugin):
                 num_image_tokens += 1
 
             while VIDEO_PLACEHOLDER in content:
-                if num_video_tokens >= len(videos):
-                    raise ValueError(f"`len(videos)` is less than the number of {VIDEO_PLACEHOLDER} tokens.")
-
                 video_seqlen = video_grid_thw[num_video_tokens].prod() // merge_length if self.expand_mm_tokens else 1
                 content = content.replace(
                     VIDEO_PLACEHOLDER, f"<|vision_start|>{self.video_token * video_seqlen}<|vision_end|>", 1
@@ -1531,12 +1472,6 @@ class Qwen2VLPlugin(BasePlugin):
 
             message["content"] = content
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
-        if len(videos) != num_video_tokens:
-            raise ValueError(f"The number of videos does not match the number of {VIDEO_PLACEHOLDER} tokens.")
-
         return messages
 
 
@@ -1602,6 +1537,7 @@ class Qwen2OmniPlugin(Qwen2VLPlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens, num_video_tokens, num_audio_tokens = 0, 0, 0
         messages = deepcopy(messages)
         image_processor: BaseImageProcessor = getattr(processor, "image_processor", None)
@@ -1624,9 +1560,6 @@ class Qwen2OmniPlugin(Qwen2VLPlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 image_seqlen = image_grid_thw[num_image_tokens].prod() // merge_length if self.expand_mm_tokens else 1
                 content = content.replace(
                     IMAGE_PLACEHOLDER, f"<|vision_bos|>{self.image_token * image_seqlen}<|vision_eos|>", 1
@@ -1642,11 +1575,6 @@ class Qwen2OmniPlugin(Qwen2VLPlugin):
                     )
 
                 while VIDEO_PLACEHOLDER in content:
-                    if num_video_tokens >= len(videos):
-                        raise ValueError(f"`len(videos)` is less than the number of {VIDEO_PLACEHOLDER} tokens.")
-                    if num_audio_tokens >= len(audios):
-                        raise ValueError(f"`len(audios)` is less than the number of {AUDIO_PLACEHOLDER} tokens.")
-
                     video_pos = content.find(VIDEO_PLACEHOLDER)
                     audio_pos = content.find(AUDIO_PLACEHOLDER, video_pos)
                     if audio_pos == -1 or audio_pos < video_pos:
@@ -1688,9 +1616,6 @@ class Qwen2OmniPlugin(Qwen2VLPlugin):
                     num_video_tokens += 1
             else:
                 while AUDIO_PLACEHOLDER in content:
-                    if num_audio_tokens >= len(audios):
-                        raise ValueError(f"`len(audios)` is less than the number of {AUDIO_PLACEHOLDER} tokens.")
-
                     audio_seqlen = audio_lengths[num_audio_tokens] if self.expand_mm_tokens else 1
                     content = content.replace(
                         AUDIO_PLACEHOLDER, f"<|audio_bos|>{self.audio_token * audio_seqlen}<|audio_eos|>", 1
@@ -1698,9 +1623,6 @@ class Qwen2OmniPlugin(Qwen2VLPlugin):
                     num_audio_tokens += 1
 
                 while VIDEO_PLACEHOLDER in content:
-                    if num_video_tokens >= len(videos):
-                        raise ValueError(f"`len(videos)` is less than the number of {VIDEO_PLACEHOLDER} tokens.")
-
                     video_seqlen = (
                         video_grid_thw[num_video_tokens].prod() // merge_length if self.expand_mm_tokens else 1
                     )
@@ -1711,15 +1633,6 @@ class Qwen2OmniPlugin(Qwen2VLPlugin):
 
             message["content"] = content
 
-        if len(audios) != num_audio_tokens:
-            raise ValueError(f"The number of audios does not match the number of {AUDIO_PLACEHOLDER} tokens.")
-
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
-        if len(videos) != num_video_tokens:
-            raise ValueError(f"The number of videos does not match the number of {VIDEO_PLACEHOLDER} tokens.")
-
         return messages
 
 
@@ -1735,6 +1648,7 @@ class VideoLlavaPlugin(BasePlugin):
         processor: Optional["MMProcessor"],
     ) -> list[dict[str, str]]:
         self._validate_input(processor, images, videos, audios)
+        self._validate_messages(messages, images, videos, audios)
         num_image_tokens, num_video_tokens = 0, 0
         messages = deepcopy(messages)
         num_frames = 0
@@ -1762,28 +1676,16 @@ class VideoLlavaPlugin(BasePlugin):
         for message in messages:
             content = message["content"]
             while IMAGE_PLACEHOLDER in content:
-                if num_image_tokens >= len(images):
-                    raise ValueError(f"`len(images)` is less than the number of {IMAGE_PLACEHOLDER} tokens.")
-
                 content = content.replace(IMAGE_PLACEHOLDER, "{{image}}" * image_seqlen, 1)
                 num_image_tokens += 1
 
             while VIDEO_PLACEHOLDER in content:
-                if num_video_tokens >= len(videos):
-                    raise ValueError(f"`len(videos)` is less than the number of {VIDEO_PLACEHOLDER} tokens.")
-
                 content = content.replace(VIDEO_PLACEHOLDER, "{{video}}" * video_seqlen, 1)
                 num_video_tokens += 1
 
             content = content.replace("{{image}}", self.image_token)
             message["content"] = content.replace("{{video}}", self.video_token)
 
-        if len(images) != num_image_tokens:
-            raise ValueError(f"The number of images does not match the number of {IMAGE_PLACEHOLDER} tokens.")
-
-        if len(videos) != num_video_tokens:
-            raise ValueError(f"The number of videos does not match the number of {VIDEO_PLACEHOLDER} tokens.")
-
         return messages