diff --git a/vllm/model_executor/models/pixtral.py b/vllm/model_executor/models/pixtral.py
index 45e5010e2a3a..684c32a3a9e5 100644
--- a/vllm/model_executor/models/pixtral.py
+++ b/vllm/model_executor/models/pixtral.py
@@ -70,7 +70,7 @@
     SupportsPP,
 )
 from .module_mapping import MultiModelKeys
-from .utils import init_vllm_registered_model, maybe_prefix
+from .utils import StageMissingLayer, init_vllm_registered_model, maybe_prefix
 from .vision import (
     VisionEncoderInfo,
     VisionFeatureSelectStrategy,
@@ -93,6 +93,10 @@
 PATCH_MERGE = "patch_merge"
 
 
+def _is_layer_none_or_staged(layer: nn.Module) -> bool:
+    return layer is None or isinstance(layer, StageMissingLayer)
+
+
 class PixtralImagePixelInputs(TensorSchema):
     """
     Dimensions:
@@ -542,7 +546,7 @@ def llm_weights_generator():
             # Single pass over weights
             for name, w in weights:
                 if is_vision_encoder_weights((name, w)):
-                    if self.vision_encoder is None:
+                    if _is_layer_none_or_staged(self.vision_encoder):
                         continue
                     # Load vision encoder weights directly
                     trimmed_name = ".".join(name.split(".")[1:])
@@ -551,7 +555,7 @@ def llm_weights_generator():
                         with torch.no_grad():
                             default_weight_loader(param, w)
                 elif is_patch_merger((name, w)):
-                    if self.patch_merger is None:
+                    if _is_layer_none_or_staged(self.patch_merger):
                         continue
                     # Load vision patch merger weights directly
                     trimmed_name = ".".join(name.split(".")[1:])
@@ -559,7 +563,7 @@ def llm_weights_generator():
                     with torch.no_grad():
                         default_weight_loader(param, w)
                 elif is_pre_mm_projector_norm((name, w)):
-                    if self.pre_mm_projector_norm is None:
+                    if _is_layer_none_or_staged(self.pre_mm_projector_norm):
                         continue
                     # Load vision pre_mm_projector_norm weights directly
                     trimmed_name = ".".join(name.split(".")[1:])
@@ -567,7 +571,7 @@ def llm_weights_generator():
                     with torch.no_grad():
                         default_weight_loader(param, w)
                 elif is_vision_lang_adapter_weights((name, w)):
-                    if self.vision_language_adapter is None:
+                    if _is_layer_none_or_staged(self.vision_language_adapter):
                         continue
                     # Load vision-language adapter weights directly
                     trimmed_name = ".".join(name.split(".")[1:])