diff --git a/tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_causal_conv1d.py b/tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_causal_conv1d.py
index 88fc9591..655d18b5 100644
--- a/tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_causal_conv1d.py
+++ b/tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_causal_conv1d.py
@@ -458,3 +458,61 @@ def test_causal_conv1d_update_with_batch_gather(batch_size, with_padding, dim,
     gc.collect()
     torch.npu.empty_cache()
     torch.npu.reset_peak_memory_stats()
+
+
+def test_causal_conv1d_update_qwen3_next_shape():
+    device = "npu"
+    itype = torch.bfloat16
+    rtol, atol = (3e-4, 1e-3) if itype == torch.float32 else (3e-3, 5e-3)
+    if itype == torch.bfloat16:
+        rtol, atol = 1e-2, 5e-2
+
+    total_tokens = 192
+    dim = 4096
+    kernel_size = 4
+    batch_size = 96
+    num_states = 929
+
+    x = torch.randn(total_tokens, dim, dtype=itype, device=device)
+    conv_state = torch.randn(num_states, dim, kernel_size, dtype=itype, device=device)
+    weight = torch.randn(dim, kernel_size, dtype=itype, device=device)
+    bias = None
+    conv_state_indices = torch.randint(0, num_states, (batch_size,), dtype=torch.int32, device=device)
+    num_accepted_tokens = torch.ones(total_tokens, dtype=torch.int32, device=device)
+    query_start_loc = torch.arange(0, total_tokens + 1, dtype=torch.int32, device=device)
+
+    activation = "silu"
+    max_query_len = 2
+    pad_slot_id = -1
+    validate_data = False
+
+    block_idx_last_scheduled_token = None
+    initial_state_idx = None
+
+    out = causal_conv1d_update(
+        x,
+        conv_state,
+        weight,
+        bias,
+        activation,
+        conv_state_indices,
+        num_accepted_tokens,
+        query_start_loc,
+        max_query_len,
+        pad_slot_id,
+        block_idx_last_scheduled_token,
+        initial_state_idx,
+        validate_data,
+    )
+
+    x_ref = x.clone()
+    conv_state_ref = conv_state[conv_state_indices, :].detach().clone()
+    out_ref = causal_conv1d_update_ref(
+        x_ref[:batch_size].transpose(1, 2), conv_state_ref, weight, bias, activation=activation
+    ).transpose(1, 2)
+
+    assert torch.allclose(out[:batch_size], out_ref, rtol=rtol, atol=atol)
+
+    gc.collect()
+    torch.npu.empty_cache()
+    torch.npu.reset_peak_memory_stats()
\ No newline at end of file
diff --git a/vllm_ascend/ops/triton/mamba/causal_conv1d.py b/vllm_ascend/ops/triton/mamba/causal_conv1d.py
index da7f4183..4c9a0c00 100644
--- a/vllm_ascend/ops/triton/mamba/causal_conv1d.py
+++ b/vllm_ascend/ops/triton/mamba/causal_conv1d.py
@@ -164,7 +164,6 @@ def extract_last_width(x, start_loc, width):
         "stride_x_seq",
         "stride_x_token",
         "stride_conv_state_seq",
-        "stride_conv_state_tok",
         "stride_state_indices",
         "stride_o_seq",
         "stride_o_token",
@@ -195,7 +194,7 @@ def _causal_conv1d_update_kernel_npu_tiled(
     stride_w_width: tl.constexpr,
     stride_conv_state_seq,
     stride_conv_state_dim: tl.constexpr,
-    stride_conv_state_tok,
+    stride_conv_state_tok: tl.constexpr,
     stride_state_indices,
     stride_o_seq,
     stride_o_dim: tl.constexpr,