diff --git a/vllm/v1/sample/rejection_sampler.py b/vllm/v1/sample/rejection_sampler.py
index 511cdb3234253..3d5e59addfcfa 100644
--- a/vllm/v1/sample/rejection_sampler.py
+++ b/vllm/v1/sample/rejection_sampler.py
@@ -598,17 +598,10 @@ def sample_recovered_tokens_kernel(
     vocab_offset = tl.arange(0, PADDED_VOCAB_SIZE)
     if NO_DRAFT_PROBS:
         draft_token_id = tl.load(draft_token_ids_ptr + start_idx + pos)
-        orig_prob = tl.load(target_probs_ptr + (start_idx + pos) * vocab_size +
-                            draft_token_id)
-        # Temporarily zero out the probability of the draft token.
-        # This is essentially the same as target_prob - draft_prob, except that
-        # n-gram does not have draft_prob. We regard it as 1.
-        tl.store(
-            target_probs_ptr + (start_idx + pos) * vocab_size + draft_token_id,
-            0)
         prob = tl.load(target_probs_ptr + (start_idx + pos) * vocab_size +
                        vocab_offset,
-                       mask=vocab_offset < vocab_size,
+                       mask=((vocab_offset < vocab_size) &
+                             (vocab_offset != draft_token_id)),
                        other=0)
     else:
         draft_prob = tl.load(draft_probs_ptr + (start_idx + pos) * vocab_size +
@@ -628,9 +621,3 @@ def sample_recovered_tokens_kernel(
                 other=float("-inf"))
     recovered_id = tl.argmax(prob / q, axis=-1)
     tl.store(output_token_ids_ptr + start_idx + pos, recovered_id)
-
-    if NO_DRAFT_PROBS:
-        # Restore the original probability.
-        tl.store(
-            target_probs_ptr + (start_idx + pos) * vocab_size + draft_token_id,
-            orig_prob)