diff --git a/ascend/test/sglang/v0.4.8/test_triton_ops_merge_state_kernel.py b/ascend/test/sglang/v0.4.8/test_triton_ops_merge_state_kernel.py
new file mode 100644
index 0000000000000000000000000000000000000000..6447f8058c765d3255fea927089c4fbfbe763f9a
--- /dev/null
+++ b/ascend/test/sglang/v0.4.8/test_triton_ops_merge_state_kernel.py
@@ -0,0 +1,90 @@
+import sys
+import pytest
+import triton
+import torch
+import triton.language as tl
+import test_common
+sys.path.append("..")
+
+
+# source: python/sglang/srt/layers/attention/triton_ops/merge_state.py
+@triton.jit
+def merge_state_kernel(
+    output,  # [NUM_TOKENS, NUM_HEADS, HEAD_SIZE] v_merged
+    output_lse,  # [NUM_TOKENS, NUM_HEADS] s_merged
+    prefix_output,  # [NUM_TOKENS, NUM_HEADS, HEAD_SIZE] v_a
+    prefix_lse,  # [NUM_TOKENS, NUM_HEADS] s_a
+    suffix_output,  # [NUM_TOKENS, NUM_HEADS, HEAD_SIZE] v_b
+    suffix_lse,  # [NUM_TOKENS, NUM_HEADS] s_b
+    HEAD_SIZE: tl.constexpr,
+    PADDED_HEAD_SIZE: tl.constexpr,
+    OUTPUT_LSE: tl.constexpr,
+):
+    token_idx = tl.program_id(0)
+    num_tokens = tl.num_programs(0)
+    head_idx = tl.program_id(1)
+    num_heads = tl.num_programs(1)
+
+    p_lse = tl.load(prefix_lse + token_idx * num_heads + head_idx)
+    s_lse = tl.load(suffix_lse + token_idx * num_heads + head_idx)
+    p_lse = float("-inf") if p_lse == float("inf") else p_lse
+    s_lse = float("-inf") if s_lse == float("inf") else s_lse
+
+    max_lse = tl.maximum(p_lse, s_lse)
+    p_lse = p_lse - max_lse
+    s_lse = s_lse - max_lse
+    out_se = tl.exp(p_lse) + tl.exp(s_lse)
+
+    if OUTPUT_LSE:
+        out_lse = tl.log(out_se) + max_lse
+        tl.store(output_lse + token_idx * num_heads + head_idx, out_lse)
+
+    head_arange = tl.arange(0, PADDED_HEAD_SIZE)
+    head_mask = head_arange < HEAD_SIZE
+    p_out = tl.load(
+        prefix_output
+        + token_idx * num_heads * HEAD_SIZE
+        + head_idx * HEAD_SIZE
+        + head_arange,
+        mask=head_mask,
+    )
+    s_out = tl.load(
+        suffix_output
+        + token_idx * num_heads * HEAD_SIZE
+        + head_idx * HEAD_SIZE
+        + head_arange,
+        mask=head_mask,
+    )
+
+    p_scale = tl.exp(p_lse) / out_se
+    s_scale = tl.exp(s_lse) / out_se
+    out = p_out * p_scale + s_out * s_scale
+    tl.store(
+        output + token_idx * num_heads * HEAD_SIZE + head_idx * HEAD_SIZE + head_arange,
+        out,
+        mask=head_mask,
+    )
+
+
+def test_triton_ops_merge_state_kernel(ptfile_path):
+    try:
+        data = torch.load(ptfile_path, map_location=torch.device('cpu'), weights_only=False)
+    except Exception as e:
+        pytest.fail(f"load file {ptfile_path} failed: {str(e)}")
+
+    # ptfile format:
+    # [input_data] (dict):
+    #     key : value
+    # [gpu_output] (dict):
+    #     key : value
+    # [grid] :
+    #     (1,)
+    input_data = test_common.convert_tensor_with_device_type(data["input_data"], device_type='npu')
+
+    merge_state_kernel[data["grid"]](**input_data)
+
+    # compare the results of GPU and NPU.
+    try:
+        test_common.compare_data_precision(data["gpu_output"], input_data, device_type='cpu')
+    except ValueError as e:
+        pytest.fail(f"The testcase failed")
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