diff --git a/tests/models/utils.py b/tests/models/utils.py
index ed1625d8d591a..8e3a86f426d5d 100644
--- a/tests/models/utils.py
+++ b/tests/models/utils.py
@@ -483,7 +483,11 @@ def dummy_hf_overrides(
         "num_kv_shared_layers": 1,
     }
 
-    model_arch_config = ModelConfig.get_model_arch_config(hf_config, text_config)
+    class DummyConfig:
+        hf_config = hf_config
+        hf_text_config = text_config
+
+    model_arch_config = ModelConfig.get_model_arch_config(DummyConfig)
     # Only set MoE related config when the model has MoE layers.
     # Otherwise all models detected as MoE by _get_transformers_backend_cls.
     if model_arch_config.num_experts > 0:
diff --git a/vllm/config/model.py b/vllm/config/model.py
index 2062377d34640..dfe191199f1a9 100644
--- a/vllm/config/model.py
+++ b/vllm/config/model.py
@@ -484,9 +484,7 @@ class ModelConfig:
         self.hf_image_processor_config = get_hf_image_processor_config(
             self.model, hf_token=self.hf_token, revision=self.revision
         )
-        self.model_arch_config = self.get_model_arch_config(
-            self.hf_config, self.hf_text_config
-        )
+        self.model_arch_config = self.get_model_arch_config()
 
         architectures = self.architectures
         registry = self.registry
@@ -604,14 +602,13 @@ class ModelConfig:
         self._verify_cuda_graph()
         self._verify_bnb_config()
 
-    @classmethod
     def get_model_arch_config(
-        cls, hf_config, hf_text_config
+        self,
     ) -> ModelArchitectureConfig:
         convertor_cls = MODEL_ARCH_CONFIG_CONVERTORS.get(
-            hf_config.model_type, ModelArchConfigConvertorBase
+            self.hf_config.model_type, ModelArchConfigConvertorBase
         )
-        convertor = convertor_cls(hf_config, hf_text_config)
+        convertor = convertor_cls(self.hf_config, self.hf_text_config)
         return convertor.convert()
 
     @field_validator("tokenizer", "max_model_len", mode="wrap")