diff --git a/vllm/v1/spec_decode/eagle.py b/vllm/v1/spec_decode/eagle.py
index dc6db0138806..743265b2e50d 100644
--- a/vllm/v1/spec_decode/eagle.py
+++ b/vllm/v1/spec_decode/eagle.py
@@ -585,6 +585,16 @@ def prepare_inputs_padded(self,
 
         return spec_common_attn_metadata, token_indices, token_indices_to_sample
 
+    def _is_tree_attention(self) -> bool:
+        if not hasattr(self.runner,
+                       "attn_groups") or not self.runner.attn_groups:
+            return False
+
+        tree_attn_metadata_builder = \
+            self.runner.attn_groups[0][0].get_metadata_builder()
+        return isinstance(tree_attn_metadata_builder,
+                          TreeAttentionMetadataBuilder)
+
     def propose_tree(
         self,
         batch_size: int,
@@ -980,21 +990,26 @@ def dummy_run(
         self,
         num_tokens: int,
     ) -> None:
-        with set_forward_context(None, self.vllm_config,
-                                 num_tokens=num_tokens):
-            if self.supports_mm_inputs:
-                input_ids = None
-                inputs_embeds = self.inputs_embeds[:num_tokens]
-            else:
-                input_ids = self.input_ids[:num_tokens]
-                inputs_embeds = None
+        assert not self._is_tree_attention(
+        ), "Dummy run for tree attention not implemented"
 
-            self.model(
-                input_ids=input_ids,
-                positions=self._get_positions(num_tokens),
-                hidden_states=self.hidden_states[:num_tokens],
-                inputs_embeds=inputs_embeds,
-            )
+        for _ in range(self.num_speculative_tokens):
+            with set_forward_context(None,
+                                     self.vllm_config,
+                                     num_tokens=num_tokens):
+                if self.supports_mm_inputs:
+                    input_ids = None
+                    inputs_embeds = self.inputs_embeds[:num_tokens]
+                else:
+                    input_ids = self.input_ids[:num_tokens]
+                    inputs_embeds = None
+
+                self.model(
+                    input_ids=input_ids,
+                    positions=self._get_positions(num_tokens),
+                    hidden_states=self.hidden_states[:num_tokens],
+                    inputs_embeds=inputs_embeds,
+                )
 
     def _get_attention_metadata_builder(
             self) -> list[AttentionMetadataBuilder]: