From fdbdbba54075a5d18f72647ee08d4fa5f5175835 Mon Sep 17 00:00:00 2001
From: Faraz <58580514+farazkh80@users.noreply.github.com>
Date: Fri, 9 Jan 2026 12:10:52 -0500
Subject: [PATCH] [https://nvbugs/5752687][fix] Choose register model config
 over root config for VLM (#10553)

Signed-off-by: Faraz Khoubsirat <58580514+farazkh80@users.noreply.github.com>
---
 tensorrt_llm/inputs/registry.py | 19 ++++++++++++++++++-
 1 file changed, 18 insertions(+), 1 deletion(-)

diff --git a/tensorrt_llm/inputs/registry.py b/tensorrt_llm/inputs/registry.py
index 54902a5ba3..8f2d6b940f 100644
--- a/tensorrt_llm/inputs/registry.py
+++ b/tensorrt_llm/inputs/registry.py
@@ -356,6 +356,20 @@ class BaseMultimodalDummyInputsBuilder(ABC):
     def get_dummy_prompt(self, input_seq_len: int):
         # TODO(yechank): We use the max resolution as starting point and keep reducing the resolution until the prompt length is less than the input sequence length.
         # Need to find better way to calculate the dummy prompt length as this iteration may not be efficient.
+
+        # Use the registered model_type from the decorator if available,
+        # otherwise fall back to HuggingFace config's model_type.
+        # This ensures consistency between placeholder registration and lookup.
+        registered_model_type = getattr(self.__class__,
+                                        '_registered_model_type', None)
+        config_model_type = self.config.model_type
+        model_type = registered_model_type or config_model_type
+
+        logger.debug(
+            f"[get_dummy_prompt] registered_model_type={registered_model_type}, "
+            f"config.model_type={config_model_type}, using model_type={model_type}"
+        )
+
         while self.image_max_dim >= self.image_min_dim:
             image = self.get_dummy_image(max_width=self.image_max_dim,
                                          max_height=self.image_max_dim)
@@ -363,7 +377,7 @@ class BaseMultimodalDummyInputsBuilder(ABC):
             test_mm_prompt = tensorrt_llm.inputs.utils.default_multimodal_input_loader(
                 tokenizer=self.tokenizer,
                 model_dir=self.model_path,
-                model_type=self.config.model_type,
+                model_type=model_type,
                 modality="image",
                 prompts=[""],
                 media=[[image]],
@@ -565,6 +579,9 @@ def register_input_processor(
         MULTIMODAL_PLACEHOLDER_REGISTRY.set_placeholder_metadata(
             model_type, placeholder_metadata)
 
+        # Store model_type on processor class for use in get_dummy_prompt
+        processor_cls._registered_model_type = model_type
+
         return model_cls
 
     return wrapper