diff --git a/vllm/v1/spec_decode/eagle.py b/vllm/v1/spec_decode/eagle.py
index 35c2e73e8ee2c..1e18eea2330a4 100644
--- a/vllm/v1/spec_decode/eagle.py
+++ b/vllm/v1/spec_decode/eagle.py
@@ -109,6 +109,7 @@ class EagleProposer:
             else []
         )
 
+        self.use_cuda_graph = self.use_cuda_graph and bool(self.cudagraph_batch_sizes)
         # persistent buffers for cuda graph
         self.input_ids = torch.zeros(
             self.max_num_tokens, dtype=torch.int32, device=device
@@ -939,7 +940,7 @@ class EagleProposer:
             self.vllm_config, DeepseekV32IndexerCache
         )
         draft_indexer_layer_names = indexer_layers.keys() - target_indexer_layer_names
-        self.attn_layer_names = list(draft_attn_layer_names)
+        self.attn_layer_names = list(draft_attn_layer_names - draft_indexer_layer_names)
         self.indexer_layer_names = list(draft_indexer_layer_names)
 
         if self.indexer_layer_names:
@@ -1050,16 +1051,18 @@ class EagleProposer:
         num_tokens: int,
         use_cudagraphs=True,
     ) -> None:
-        if use_cudagraphs and num_tokens <= self.cudagraph_batch_sizes[-1]:
+        # Determine if CUDA graphs should be used for this run.
+        cudagraphs_enabled = use_cudagraphs and self.use_cuda_graph
+        if cudagraphs_enabled and num_tokens <= self.cudagraph_batch_sizes[-1]:
             num_tokens = self.vllm_config.pad_for_cudagraph(num_tokens)
 
         with set_forward_context(
             None,
             self.vllm_config,
             num_tokens=num_tokens,
-            cudagraph_runtime_mode=CUDAGraphMode.PIECEWISE
-            if use_cudagraphs
-            else CUDAGraphMode.NONE,
+            cudagraph_runtime_mode=(
+                CUDAGraphMode.PIECEWISE if cudagraphs_enabled else CUDAGraphMode.NONE
+            ),
         ):
             if self.supports_mm_inputs:
                 input_ids = None