diff --git a/modelopt/torch/prune/plugins/mcore_minitron.py b/modelopt/torch/prune/plugins/mcore_minitron.py
index abba65bc9..2fd4b439a 100644
--- a/modelopt/torch/prune/plugins/mcore_minitron.py
+++ b/modelopt/torch/prune/plugins/mcore_minitron.py
@@ -59,38 +59,6 @@
 }
 
 
-def get_supported_models():
-    """Get the supported models for Minitron pruning.
-
-    NOTE: Keep inside function to avoid circular import issues.
-    """
-    supported_models = set()
-
-    try:
-        from megatron.core.models.gpt import GPTModel
-
-        supported_models.add(GPTModel)
-    except Exception:
-        pass
-
-    try:
-        from megatron.core.models.mamba import MambaModel
-
-        supported_models.add(MambaModel)
-    except Exception:
-        pass
-
-    try:
-        from nemo.collections import llm
-
-        # NOTE: llm.MambaModel is a subclass of llm.GPTModel
-        supported_models.add(llm.GPTModel)
-    except Exception:
-        pass
-
-    return supported_models
-
-
 class MCoreMinitronSearcher(BaseSearcher):
     """Searcher for Minitron pruning algorithm."""
 
@@ -158,17 +126,6 @@ def before_search(self) -> None:
     def run_search(self) -> None:
         """Run actual search."""
         # Run forward loop to collect activations and sort parameters
-        model_cfg = None
-        supported_models = get_supported_models()
-        for m_type in supported_models:
-            if isinstance(self.model, m_type):
-                model_cfg = self.model.config
-                break
-        if model_cfg is None:
-            raise NotImplementedError(
-                f"Only {supported_models} models are supported! Got: {type(self.model)}"
-            )
-
         assert self.forward_loop is not None
         is_training = self.model.training
         self.model.eval()
@@ -187,6 +144,7 @@ def run_search(self) -> None:
                 hp.active = export_config[hp_name]
 
         # kv_channels can be None so we need to save original from original hidden_size and num_attention_heads
+        model_cfg = self.model.config
         orig_kv_channels = getattr(model_cfg, "kv_channels")
         if orig_kv_channels is None:
             orig_kv_channels = getattr(model_cfg, "hidden_size") // getattr(