diff --git a/vllm/model_executor/models/qwen2.py b/vllm/model_executor/models/qwen2.py
index b6a1d2db3..801741eca 100644
--- a/vllm/model_executor/models/qwen2.py
+++ b/vllm/model_executor/models/qwen2.py
@@ -52,7 +52,7 @@ from vllm.model_executor.sampling_metadata import SamplingMetadata
 from vllm.sequence import IntermediateTensors
 from vllm.transformers_utils.config import is_interleaved
 
-from .interfaces import SupportsLoRA, SupportsPP
+from .interfaces import SupportsEagle3, SupportsLoRA, SupportsPP
 from .utils import (AutoWeightsLoader, PPMissingLayer, extract_layer_index,
                     is_pp_missing_parameter,
                     make_empty_intermediate_tensors_factory, make_layers,
@@ -442,7 +442,7 @@ class Qwen2Model(nn.Module):
         return loaded_params
 
 
-class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
+class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP, SupportsEagle3):
     packed_modules_mapping = {
         "qkv_proj": [
             "q_proj",
@@ -488,6 +488,13 @@ class Qwen2ForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
     def get_input_embeddings(self, input_ids: torch.Tensor) -> torch.Tensor:
         return self.model.get_input_embeddings(input_ids)
 
+    def set_aux_hidden_state_layers(self, layers: tuple[int]) -> None:
+        self.model.aux_hidden_state_layers = layers
+
+    def get_eagle3_aux_hidden_state_layers(self) -> tuple[int]:
+        num_layers = len(self.model.layers)
+        return (2, num_layers // 2, num_layers - 3)
+
     def forward(
         self,
         input_ids: torch.Tensor,