diff --git a/comfy/clip_vision.py b/comfy/clip_vision.py
index 2c8b4d5d6..57968ed85 100644
--- a/comfy/clip_vision.py
+++ b/comfy/clip_vision.py
@@ -10,6 +10,7 @@ import comfy.utils
 import comfy.clip_model
 import comfy.image_encoders.dino2
 import comfy.image_encoders.dino3
+from comfy.image_encoders.naf import NAF
 
 class Output:
     def __getitem__(self, key):
@@ -53,6 +54,7 @@ class ClipVisionModel():
         self.model.eval()
 
         self.patcher = comfy.model_patcher.CoreModelPatcher(self.model, load_device=self.load_device, offload_device=offload_device)
+        self.naf = None
 
     def load_sd(self, sd):
         return self.model.load_state_dict(sd, strict=False, assign=self.patcher.is_dynamic())
@@ -155,6 +157,13 @@ def load_clipvision_from_sd(sd, prefix="", convert_keys=False):
     for k in keys:
         if k not in u:
             sd.pop(k)
+    # NAF feature upsampler ships bundled into the DINOv3 file under the `naf.` prefix.
+    naf_keys = [k for k in sd if k.startswith("naf.")]
+    if naf_keys:
+        naf_sd = {k[len("naf."):]: sd.pop(k) for k in naf_keys}
+        naf = NAF().eval()
+        naf.load_state_dict(naf_sd, strict=False)
+        clip.naf = comfy.model_patcher.CoreModelPatcher(naf, load_device=clip.load_device, offload_device=comfy.model_management.text_encoder_offload_device())
     return clip
 
 def load(ckpt_path):
diff --git a/comfy/ldm/trellis2/naf/model.py b/comfy/image_encoders/naf.py
similarity index 100%
rename from comfy/ldm/trellis2/naf/model.py
rename to comfy/image_encoders/naf.py
diff --git a/comfy_extras/nodes_trellis2.py b/comfy_extras/nodes_trellis2.py
index 9e496e4da..3e5256e0c 100644
--- a/comfy_extras/nodes_trellis2.py
+++ b/comfy_extras/nodes_trellis2.py
@@ -2,15 +2,12 @@ from typing_extensions import override
 from comfy_api.latest import ComfyExtension, IO, Types, UI, io
 from comfy.ldm.trellis2.vae import SparseTensor
 from comfy.ldm.trellis2.model import build_proj_transform_matrix, compute_stage_proj_feats
-from comfy.ldm.trellis2.naf.model import NAF
 
 from comfy_extras.nodes_mesh_postprocess import pack_variable_mesh_batch
 from server import PromptServer
 import comfy.latent_formats
 import comfy.model_management
-import comfy.model_patcher
 import comfy.utils
-import folder_paths
 from PIL import Image
 import logging
 import numpy as np
@@ -18,7 +15,6 @@ import math
 import torch
 
 ShapeSubdivides = io.Custom("SHAPE_SUBDIVIDES")
-NAFModel = io.Custom("NAF_MODEL")
 
 
 shape_slat_format = comfy.latent_formats.Trellis2ShapeSLAT()
@@ -864,12 +860,6 @@ class Pixal3DConditioning(IO.ComfyNode):
                             "Wire a MoGeGeometryToFOV (axis='horizontal', unit='degrees') "
                             "output here for a MoGe-derived FOV.",
                 ),
-                NAFModel.Input(
-                    "naf_model",
-                    optional=True,
-                    tooltip="Optional NAF feature upsampler. Required for shape/texture stages "
-                            "to match upstream's trained feature distribution.",
-                ),
             ],
             outputs=[
                 IO.Conditioning.Output(display_name="positive"),
@@ -878,7 +868,8 @@ class Pixal3DConditioning(IO.ComfyNode):
         )
 
     @classmethod
-    def execute(cls, clip_vision_model, image, mask, camera_angle_x, naf_model=None) -> IO.NodeOutput:
+    def execute(cls, clip_vision_model, image, mask, camera_angle_x) -> IO.NodeOutput:
+        naf_model = getattr(clip_vision_model, "naf", None)
         if image.ndim == 3:
             image = image.unsqueeze(0)
         if mask.ndim == 2:
@@ -987,40 +978,6 @@ class Pixal3DConditioning(IO.ComfyNode):
         return IO.NodeOutput(positive, negative)
 
 
-class LoadNAFModel(IO.ComfyNode):
-
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="LoadNAFModel",
-            display_name="Load NAF Model",
-            category="loaders",
-            inputs=[
-                IO.Combo.Input(
-                    "naf_name",
-                    options=folder_paths.get_filename_list("upscale_models"),
-                    tooltip="NAF safetensors checkpoint (e.g. naf_release.safetensors).",
-                ),
-            ],
-            outputs=[NAFModel.Output(display_name="naf_model")],
-        )
-
-    @classmethod
-    def execute(cls, naf_name) -> IO.NodeOutput:
-        path = folder_paths.get_full_path_or_raise("upscale_models", naf_name)
-        sd = comfy.utils.load_torch_file(path, safe_load=True)
-        model = NAF().eval()
-        _, unexpected = model.load_state_dict(sd, strict=False)
-        if unexpected:
-            raise ValueError(f"Unexpected keys in NAF state_dict: {sorted(unexpected)[:8]}...")
-        patcher = comfy.model_patcher.CoreModelPatcher(
-            model,
-            load_device=comfy.model_management.get_torch_device(),
-            offload_device=comfy.model_management.unet_offload_device(),
-        )
-        return IO.NodeOutput(patcher)
-
-
 class GetMeshInfo(IO.ComfyNode):
     """Report vertex / face counts and attributes for a MESH, displayed on the
     node (and as a string output). Counts are comma-formatted since meshes can
@@ -1096,7 +1053,6 @@ class Trellis2Extension(ComfyExtension):
         return [
             Trellis2Conditioning,
             Pixal3DConditioning,
-            LoadNAFModel,
             Trellis2ShapeStage,
             EmptyTrellis2LatentStructure,
             Trellis2TextureStage,