diff --git a/vllm_ascend/spec_decode/eagle_proposer.py b/vllm_ascend/spec_decode/eagle_proposer.py
index 403d52a2..72ee9d9c 100644
--- a/vllm_ascend/spec_decode/eagle_proposer.py
+++ b/vllm_ascend/spec_decode/eagle_proposer.py
@@ -570,6 +570,12 @@ class SpecDecodeBaseProposer(EagleProposer):
 
         # Copy the old attn_metadata and update
         attn_metadata_i = per_layer_attn_metadata[self.attn_layer_names[0]]
+
+        # Clone the data so that when calculating the data at position 2 and position 3
+        # in the merged graph, it does not affect position 1
+        # FIXME(lilinsiman)
+        common_attn_metadata.block_table_tensor = common_attn_metadata.block_table_tensor.clone()
+
         if self.pcp_size * self.dcp_size > 1:
             if self.num_speculative_tokens > 1 and not attn_metadata_i.num_prefills:
                 # For pcp/dcp, tokens are split across different cp ranks,
@@ -1136,9 +1142,16 @@ class SpecDecodeBaseProposer(EagleProposer):
             common_attn_metadata.num_input_tokens = input_batch_size
 
         # The loop part
-
         used_update_positions += 1
 
+        # Clone the data so that when calculating the data at position 2 and position 3
+        # in the merged graph, it does not affect position 1
+        # FIXME(lilinsiman)
+        common_attn_metadata.seq_lens = common_attn_metadata.seq_lens.clone()
+        common_attn_metadata.seq_lens_cpu = common_attn_metadata.seq_lens_cpu.clone()
+        common_attn_metadata.num_computed_tokens_cpu = common_attn_metadata.num_computed_tokens_cpu.clone()
+        common_attn_metadata.positions = common_attn_metadata.positions.clone()
+
         # NOTE(woosuk): We should handle the case where the draft model
         # generates tokens beyond the max model length. Since it is complex
         # to remove such requests from the batch, we keep them in the batch