diff --git a/py/metadata_collector/node_extractors.py b/py/metadata_collector/node_extractors.py
index 289e2160..41c27620 100644
--- a/py/metadata_collector/node_extractors.py
+++ b/py/metadata_collector/node_extractors.py
@@ -3,6 +3,18 @@ import os
 from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER
 
 
+def _store_checkpoint_metadata(metadata, node_id, model_name):
+    """Store checkpoint model information when available."""
+    if not model_name:
+        return
+    metadata.setdefault(MODELS, {})
+    metadata[MODELS][node_id] = {
+        "name": model_name,
+        "type": "checkpoint",
+        "node_id": node_id
+    }
+
+
 class NodeMetadataExtractor:
     """Base class for node-specific metadata extraction"""
     
@@ -29,12 +41,27 @@ class CheckpointLoaderExtractor(NodeMetadataExtractor):
             return
             
         model_name = inputs.get("ckpt_name")
-        if model_name:
-            metadata[MODELS][node_id] = {
-                "name": model_name,
-                "type": "checkpoint",
-                "node_id": node_id
-            }
+        _store_checkpoint_metadata(metadata, node_id, model_name)
+
+
+class NunchakuFluxDiTLoaderExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "model_path" not in inputs:
+            return
+
+        model_name = inputs.get("model_path")
+        _store_checkpoint_metadata(metadata, node_id, model_name)
+
+
+class NunchakuQwenImageDiTLoaderExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "model_name" not in inputs:
+            return
+
+        model_name = inputs.get("model_name")
+        _store_checkpoint_metadata(metadata, node_id, model_name)
 
 class TSCCheckpointLoaderExtractor(NodeMetadataExtractor):
     @staticmethod
@@ -43,12 +70,7 @@ class TSCCheckpointLoaderExtractor(NodeMetadataExtractor):
             return
             
         model_name = inputs.get("ckpt_name")
-        if model_name:
-            metadata[MODELS][node_id] = {
-                "name": model_name,
-                "type": "checkpoint",
-                "node_id": node_id
-            }
+        _store_checkpoint_metadata(metadata, node_id, model_name)
 
         # For loader node has lora_stack input, like Efficient Loader from Efficient Nodes
         active_loras = []
@@ -660,6 +682,8 @@ NODE_EXTRACTORS = {
     "comfyLoader": CheckpointLoaderExtractor,  # easy comfyLoader
     "CheckpointLoaderSimpleWithImages": CheckpointLoaderExtractor,  # CheckpointLoader|pysssss
     "TSC_EfficientLoader": TSCCheckpointLoaderExtractor,  # Efficient Nodes
+    "NunchakuFluxDiTLoader": NunchakuFluxDiTLoaderExtractor,  # ComfyUI-Nunchaku
+    "NunchakuQwenImageDiTLoader": NunchakuQwenImageDiTLoaderExtractor,  # ComfyUI-Nunchaku
     "UNETLoader": UNETLoaderExtractor,          # Updated to use dedicated extractor
     "UnetLoaderGGUF": UNETLoaderExtractor,  # Updated to use dedicated extractor
     "LoraLoader": LoraLoaderExtractor,