diff --git a/paddle/phi/infermeta/multiary.cc b/paddle/phi/infermeta/multiary.cc
index e5835dc56d4718267e4715f77b35b862023591b3..56dc40cc7c9a69086e3751c916358ec171ee06d4 100644
--- a/paddle/phi/infermeta/multiary.cc
+++ b/paddle/phi/infermeta/multiary.cc
@@ -2408,7 +2408,8 @@ void SgdInferMeta(const MetaTensor& param,
 
 void StackInferMeta(const std::vector<const MetaTensor*>& x,
                     int axis,
-                    MetaTensor* out) {
+                    MetaTensor* out,
+                    MetaConfig config) {
   PADDLE_ENFORCE_GT(x.size(),
                     0UL,
                     phi::errors::InvalidArgument(
@@ -2416,17 +2417,10 @@ void StackInferMeta(const std::vector<const MetaTensor*>& x,
                         " received value is:%d.",
                         x.size()));
   const auto& input_dims = GetMetaTensorsDim(x);
-  for (size_t i = 1; i < input_dims.size(); ++i) {
-    PADDLE_ENFORCE_EQ(input_dims[i],
-                      input_dims[0],
-                      phi::errors::InvalidArgument(
-                          "Dims of all Inputs(X) must be the same, but"
-                          " received input %d dim is:%d not equal to input 0"
-                          " dim:%d.",
-                          i,
-                          input_dims[i],
-                          input_dims[0]));
-  }
+  // we reuse concat logic to compute out_dim. we set concat_axis==-1 to check
+  // every axis in input_tensors.
+  auto out_dim =
+      phi::funcs::ComputeAndCheckShape(config.is_runtime, input_dims, -1);
   int rank = input_dims[0].size();
   PADDLE_ENFORCE_GE(
       axis,
@@ -2445,7 +2439,7 @@ void StackInferMeta(const std::vector<const MetaTensor*>& x,
           rank,
           axis));
   if (axis < 0) axis += (rank + 1);
-  auto vec = phi::vectorize<int>(input_dims[0]);
+  auto vec = phi::vectorize<int>(out_dim);
   vec.insert(vec.begin() + axis, input_dims.size());
   out->set_dims(phi::make_ddim(vec));
   out->set_dtype(x.at(0)->dtype());
diff --git a/paddle/phi/infermeta/multiary.h b/paddle/phi/infermeta/multiary.h
index 0296509e43750b97fc467d7ed1e03e066e6b816e..4e95303f1a02566343e3bc8a87ebb6661f3c0b01 100644
--- a/paddle/phi/infermeta/multiary.h
+++ b/paddle/phi/infermeta/multiary.h
@@ -452,7 +452,8 @@ void SgdInferMeta(const MetaTensor& param,
 
 void StackInferMeta(const std::vector<const MetaTensor*>& x,
                     int axis,
-                    MetaTensor* out);
+                    MetaTensor* out,
+                    MetaConfig config = MetaConfig());
 
 void UnchangedMultiInferMeta(const std::vector<const MetaTensor*>& x,
                              std::vector<MetaTensor*> out);
diff --git a/python/paddle/fluid/tests/unittests/test_stack_op.py b/python/paddle/fluid/tests/unittests/test_stack_op.py
index f7b1254c880ef255681f3252d024a3bfa75a8afb..8fc004838da6c88a4aaecdc7ffda46476afac5f7 100644
--- a/python/paddle/fluid/tests/unittests/test_stack_op.py
+++ b/python/paddle/fluid/tests/unittests/test_stack_op.py
@@ -18,6 +18,7 @@ import paddle
 import paddle.fluid as fluid
 from op_test import OpTest, convert_float_to_uint16
 import paddle.fluid.core as core
+from paddle.fluid.framework import Program, program_guard
 
 
 class TestStackOpBase(OpTest):
@@ -268,5 +269,30 @@ class API_DygraphTest(unittest.TestCase):
             self.assertRaises(Exception, paddle.stack, x)
 
 
+class TestStackOpWithNegativeShape(unittest.TestCase):
+
+    def test_out(self):
+        main_prg, startup_prg = Program(), Program()
+        with program_guard(main_prg, startup_prg):
+            b = paddle.static.data(name='b', shape=[-1], dtype='int64')
+            e = paddle.static.data(name='e', shape=[3], dtype='int64')
+            k = paddle.stack([b, e], axis=0)
+            exe = paddle.static.Executor()
+            exe.run(startup_prg)
+            out = exe.run(main_prg,
+                          feed={
+                              'b': np.ones([
+                                  3,
+                              ]).astype("int64"),
+                              'e': np.zeros([
+                                  3,
+                              ]).astype("int64")
+                          },
+                          fetch_list=[k])
+        np.testing.assert_allclose(out[0],
+                                   np.array([[1, 1, 1], [0, 0, 0]]),
+                                   rtol=1e-05)
+
+
 if __name__ == '__main__':
     unittest.main()