diff --git a/paddle/phi/api/yaml/backward.yaml b/paddle/phi/api/yaml/backward.yaml
index 465df08392d91094d3586965dbcaa2a7661d3167..924a5f59d505567fe2fc50fce1c9cd0342d3a7f8 100644
--- a/paddle/phi/api/yaml/backward.yaml
+++ b/paddle/phi/api/yaml/backward.yaml
@@ -1092,8 +1092,7 @@
   args : (Tensor x, Tensor[] indices, Tensor value, Tensor out_grad, bool accumulate=false)
   output : Tensor(x_grad), Tensor(value_grad)
   infer_meta :
-    func : GeneralBinaryGradInferMeta
-    param : [x, value]
+    func : IndexPutGradInferMeta
   kernel :
     func : index_put_grad
     data_type : out_grad
diff --git a/paddle/phi/infermeta/backward.cc b/paddle/phi/infermeta/backward.cc
index b028fd15b1b9396940f0660f88ddd25986345095..d1078e2d176bc0383aa3fd6ad9ec9577affe6036 100644
--- a/paddle/phi/infermeta/backward.cc
+++ b/paddle/phi/infermeta/backward.cc
@@ -1202,6 +1202,21 @@ void IndexAddGradInferMeta(const MetaTensor& index,
   }
 }
 
+void IndexPutGradInferMeta(const MetaTensor& x,
+                           const std::vector<const MetaTensor*>& indices,
+                           const MetaTensor& value,
+                           const MetaTensor& out_grad,
+                           bool accumulate,
+                           MetaTensor* x_grad,
+                           MetaTensor* value_grad) {
+  if (x_grad) {
+    x_grad->share_meta(x);
+  }
+  if (value_grad) {
+    value_grad->share_meta(value);
+  }
+}
+
 void FusedRopeGradInferMeta(const MetaTensor& dout_q,
                             const MetaTensor& dout_k,
                             const MetaTensor& dout_v,
diff --git a/paddle/phi/infermeta/backward.h b/paddle/phi/infermeta/backward.h
index cb923e16446af203a023e04240515ce6bfb5078d..c73e5ab7a4d9ecec63beb04c0ff4929df9253dae 100644
--- a/paddle/phi/infermeta/backward.h
+++ b/paddle/phi/infermeta/backward.h
@@ -467,4 +467,11 @@ void IndexAddGradInferMeta(const MetaTensor& index,
                            MetaTensor* x_grad,
                            MetaTensor* add_tensor_grad);
 
+void IndexPutGradInferMeta(const MetaTensor& x,
+                           const std::vector<const MetaTensor*>& indices,
+                           const MetaTensor& value,
+                           const MetaTensor& out_grad,
+                           bool accumulate,
+                           MetaTensor* x_grad,
+                           MetaTensor* value_grad);
 }  // namespace phi
diff --git a/test/legacy_test/test_index_put_op.py b/test/legacy_test/test_index_put_op.py
index c4bf5d6f0fd401f608eefb5495bee4e4f776f7a6..f21f7b084bde41dbf01853d19d633529b357c894 100644
--- a/test/legacy_test/test_index_put_op.py
+++ b/test/legacy_test/test_index_put_op.py
@@ -854,6 +854,39 @@ class TestIndexPutAPIBackward(unittest.TestCase):
                 atol=1e-7,
             )
 
+    def test_backward_in_static(self):
+        paddle.enable_static()
+        exe = paddle.static.Executor()
+        train_program = paddle.static.Program()
+        startup_program = paddle.static.Program()
+        with paddle.static.program_guard(train_program, startup_program):
+            x = paddle.zeros((4, 2, 5))
+            x.stop_gradient = False
+
+            y = x + 1
+            index = paddle.to_tensor([0, 1, 3])
+
+            value = paddle.ones((5,))
+            value.stop_gradient = False
+
+            z = paddle.index_put(y, (index,), value)
+            l = z.sum()
+            paddle.static.append_backward(l)
+            res = exe.run(fetch_list=[z, x.grad_name, value.grad_name])
+
+            expected_z = np.ones((4, 2, 5))
+            expected_z[[0, 1, 3]] = np.ones((5,))
+
+            expected_x_grad = np.ones((4, 2, 5))
+            expected_x_grad[[0, 1, 3]] = 0
+
+            expected_v_grad = np.ones((5,)) * 3 * 2
+
+            np.testing.assert_allclose(expected_z, res[0])
+            np.testing.assert_allclose(expected_x_grad, res[1])
+            np.testing.assert_allclose(expected_v_grad, res[2])
+        paddle.disable_static()
+
 
 class TestIndexPutAPIMixedIndices(TestIndexPutAPIBase):
     def init_dtype_type(self):