diff --git a/vllm/model_executor/models/llama4.py b/vllm/model_executor/models/llama4.py
index 4c6d1d4244755..e1bdfc3405f70 100644
--- a/vllm/model_executor/models/llama4.py
+++ b/vllm/model_executor/models/llama4.py
@@ -53,6 +53,7 @@ from vllm.model_executor.models.utils import sequence_parallel_chunk
 from .llama import LlamaForCausalLM, LlamaMLP, LlamaModel
 from .utils import (
     AutoWeightsLoader,
+    PPMissingLayer,
     extract_layer_index,
     fast_topk,
     is_pp_missing_parameter,
@@ -729,6 +730,9 @@ class Llama4ForCausalLM(LlamaForCausalLM, MixtureOfExperts):
         self.moe_layers = []
         example_moe = None
         for layer in self.model.layers:
+            if isinstance(layer, PPMissingLayer):
+                continue
+
             assert isinstance(layer, Llama4DecoderLayer)
             if isinstance(layer.feed_forward, Llama4MoE):
                 # Pick last one layer since the first ones may be dense layers.
@@ -765,6 +769,9 @@ class Llama4ForCausalLM(LlamaForCausalLM, MixtureOfExperts):
         self.num_local_physical_experts = num_local_physical_experts
         self.num_redundant_experts = num_physical_experts - self.num_logical_experts
         for layer in self.model.layers:
+            if isinstance(layer, PPMissingLayer):
+                continue
+
             if isinstance(layer.feed_forward, Llama4MoE):
                 moe = layer.feed_forward
                 moe.n_local_physical_experts = num_local_physical_experts