diff --git a/vllm_ascend/spec_decode/eagle_proposer.py b/vllm_ascend/spec_decode/eagle_proposer.py
index 0a5e5d74..3086ae30 100644
--- a/vllm_ascend/spec_decode/eagle_proposer.py
+++ b/vllm_ascend/spec_decode/eagle_proposer.py
@@ -718,7 +718,17 @@ class AscendEagleProposer(EagleProposer):
             hidden_states = torch.index_select(
                 hidden_states, 0, self.runner.pcp_manager.pcp_allgather_restore_idx.gpu[: hidden_states.shape[0]]
             )
-            last_hidden_states = hidden_states  # TODO: check it
+            if self.method == "mtp":
+                last_hidden_states = hidden_states
+            else:
+                # eagle and eagle3 need allgather last_hidden_states.
+                last_hidden_states = last_hidden_states[:num_tokens]
+                last_hidden_states = get_pcp_group().all_gather(last_hidden_states, 0)
+                last_hidden_states = torch.index_select(
+                    last_hidden_states,
+                    0,
+                    self.runner.pcp_manager.pcp_allgather_restore_idx.gpu[: last_hidden_states.shape[0]],
+                )
 
         num_indices = last_token_indices.shape[0]
         if lmhead_tp_enable() and not is_dummy:
@@ -957,7 +967,7 @@ class AscendEagleProposer(EagleProposer):
 
         if self.pcp_size * self.dcp_size > 1:
             num_computed_tokens_of_pcp_dcp = self.runner.pcp_manager._get_cp_local_seq_lens(
-                ori_seq_len + draft_step,
+                ori_seq_len + draft_step + 1,
                 self.pcp_size,
                 self.dcp_size,
                 self.runner.parallel_config.cp_kv_cache_interleave_size,
diff --git a/vllm_ascend/worker/model_runner_v1.py b/vllm_ascend/worker/model_runner_v1.py
index 7fa58a44..64f4c22d 100644
--- a/vllm_ascend/worker/model_runner_v1.py
+++ b/vllm_ascend/worker/model_runner_v1.py
@@ -1048,7 +1048,7 @@ class NPUModelRunner(GPUModelRunner):
                     target_positions = positions
                     target_hidden_states = hidden_states
                     if self.use_aux_hidden_state_outputs:
-                        target_hidden_states = torch.cat([h[token_indices] for h in aux_hidden_states], dim=-1)
+                        target_hidden_states = torch.cat([h for h in aux_hidden_states], dim=-1)
                 else:
                     target_token_ids = self.input_ids.gpu[token_indices]
                     target_positions = self._get_positions(token_indices)