diff --git a/python/paddle/tensor/stat.py b/python/paddle/tensor/stat.py
index 376b0ce1d421e5..4dafa608cc2948 100644
--- a/python/paddle/tensor/stat.py
+++ b/python/paddle/tensor/stat.py
@@ -628,7 +628,23 @@ def median(
             axis += dims
     sz = x.shape[axis]
     kth = sz >> 1
-    tensor_topk, idx = paddle.topk(x, kth + 1, axis=axis, largest=False)
+    # Use `sort` when:
+    # 1. The axis is not the last dimension (memory non-contiguous)
+    # 2. The axis size exceeds 10000 (heuristic threshold for performance crossover)
+    # Rationale:
+    # - `paddle.topk` in non-contiguous dimensions has O(N*k) complexity (k=n/2 for median → O(n²)). in paddle/phi/kernels/gpu/top_k_kernel.cu
+    # - `paddle.sort` has guaranteed O(n log n) complexity regardless of axis
+    use_sort = (axis != dims - 1) and (sz > 10000)
+    if use_sort:
+        sorted_x = paddle.sort(x, axis=axis, stable=True)
+        tensor_topk = paddle.slice(
+            sorted_x, axes=[axis], starts=[0], ends=[kth + 1]
+        )
+        if need_idx:
+            idx = paddle.argsort(x, axis=axis, stable=True)
+            idx = paddle.slice(idx, axes=[axis], starts=[0], ends=[kth + 1])
+    else:
+        tensor_topk, idx = paddle.topk(x, kth + 1, axis=axis, largest=False)
     if mode == 'avg':
         dtype = (
             'float64'
diff --git a/test/legacy_test/test_median.py b/test/legacy_test/test_median.py
index 3cab9133359af8..77a9145f9205c7 100644
--- a/test/legacy_test/test_median.py
+++ b/test/legacy_test/test_median.py
@@ -401,5 +401,23 @@ def test_median_dygraph(self):
         self.dygraph_single_test_median([x, 1, False])
 
 
+class TestMedianSort(unittest.TestCase):
+    def dygraph_single_test_median(self, lis_test):
+        x, axis, keepdims = lis_test
+        res_np = np.median(x, axis=axis, keepdims=keepdims)
+        x_pd = paddle.to_tensor(x)
+        x_pd.stop_gradient = False
+        res_pd = paddle.median(x_pd, axis, keepdims)
+        np.testing.assert_allclose(res_pd.numpy(), res_np)
+
+    def test_median_dygraph(self):
+        paddle.disable_static()
+        h = 2
+        w = 20000
+        l = 2
+        x = np.arange(h * w * l).reshape([h, w, l])
+        self.dygraph_single_test_median([x, 1, False])
+
+
 if __name__ == '__main__':
     unittest.main()