diff --git a/python/sglang/srt/layers/attention/trtllm_mla_backend.py b/python/sglang/srt/layers/attention/trtllm_mla_backend.py
index f6d31dbc0..1882881e5 100755
--- a/python/sglang/srt/layers/attention/trtllm_mla_backend.py
+++ b/python/sglang/srt/layers/attention/trtllm_mla_backend.py
@@ -944,8 +944,16 @@ class TRTLLMMLABackend(FlashInferMLAAttnBackend):
                     metadata.max_seq_len_k + forward_batch.spec_info.draft_token_num
                 )
             else:
-                seq_lens = forward_batch.seq_lens.to(torch.int32)
-                max_seq_len = metadata.max_seq_len_k
+                # forward_batch.seq_lens is the seq_lens of the prev_context + verified tokens.
+                # To account for pad_draft_extend_query, we need seq_lens = prev_context + max_draft_tokens.
+                # This will ensure queries align with kvs correctly when calling
+                # flashinfer.decode.trtllm_batch_decode_with_kv_cache_mla.
+                seq_lens = (
+                    forward_batch.seq_lens
+                    - metadata.seq_lens_q
+                    + metadata.max_seq_len_q
+                ).to(torch.int32)
+                max_seq_len = metadata.max_seq_len_k + metadata.max_seq_len_q
                 # Check if we're in CUDA graph mode (buffers are pre-allocated)
                 if self.padded_q_buffer is not None:
                     # Use pre-allocated buffer for CUDA graph compatibility