diff --git a/paddle/phi/kernels/funcs/elementwise_functor.h b/paddle/phi/kernels/funcs/elementwise_functor.h
index af0ae3b6447be5bfa8b261bfbc2b6baafd7de65d..a291c1542d3e2b986a757d359e6f3854956b2dcb 100644
--- a/paddle/phi/kernels/funcs/elementwise_functor.h
+++ b/paddle/phi/kernels/funcs/elementwise_functor.h
@@ -14,6 +14,7 @@ limitations under the License. */
 
 #pragma once
 
+#include "paddle/phi/common/bfloat16.h"
 #include "paddle/phi/common/complex.h"
 #include "paddle/phi/common/float16.h"
 #include "paddle/phi/core/enforce.h"
@@ -190,6 +191,17 @@ struct FMinFunctor<dtype::float16> {
   }
 };
 
+template <>
+struct FMinFunctor<dtype::bfloat16> {
+  inline HOSTDEVICE dtype::bfloat16 operator()(const dtype::bfloat16 a,
+                                               const dtype::bfloat16 b) const {
+    float float_a = static_cast<float>(a);
+    float float_b = static_cast<float>(b);
+    auto result = std::fmin(float_a, float_b);
+    return static_cast<dtype::bfloat16>(result);
+  }
+};
+
 template <>
 struct FMinFunctor<int> {
   inline HOSTDEVICE int operator()(const int a, const int b) const {
diff --git a/paddle/phi/kernels/gpu/elementwise_grad_kernel.cu b/paddle/phi/kernels/gpu/elementwise_grad_kernel.cu
index 30e222663da1000e2be0573dca16ff8526dc8458..b69434c82da8c362c9fdb74edd19478cb35d5385 100644
--- a/paddle/phi/kernels/gpu/elementwise_grad_kernel.cu
+++ b/paddle/phi/kernels/gpu/elementwise_grad_kernel.cu
@@ -108,6 +108,7 @@ PD_REGISTER_KERNEL(fmin_grad,
                    double,
                    int,
                    phi::dtype::float16,
+                   phi::dtype::bfloat16,
                    int64_t) {}
 
 PD_REGISTER_KERNEL(maximum_grad,
diff --git a/paddle/phi/kernels/kps/elementwise_kernel.cu b/paddle/phi/kernels/kps/elementwise_kernel.cu
index cbf811a9830b0c21946096b5a2d37b737657e3ef..550e579ac1159639b5ae128356310414a4e93a85 100644
--- a/paddle/phi/kernels/kps/elementwise_kernel.cu
+++ b/paddle/phi/kernels/kps/elementwise_kernel.cu
@@ -166,6 +166,7 @@ PD_REGISTER_KERNEL(fmin,
                    double,
                    int,
                    float16,
+                   bfloat16,
                    int64_t) {}
 
 PD_REGISTER_KERNEL(heaviside,
diff --git a/python/paddle/fluid/tests/unittests/test_fmin_op.py b/python/paddle/fluid/tests/unittests/test_fmin_op.py
index 19e43fa3d1d6c5acf508e6a72cfec8810db2f41b..1956d5b4fc433ce2da7e1f690f4003710581677e 100644
--- a/python/paddle/fluid/tests/unittests/test_fmin_op.py
+++ b/python/paddle/fluid/tests/unittests/test_fmin_op.py
@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from eager_op_test import OpTest
+from eager_op_test import OpTest, convert_float_to_uint16
 
 import paddle
 from paddle.fluid import core
@@ -243,6 +243,35 @@ class TestElementwiseFmin3Op(OpTest):
         self.check_grad(['X', 'Y'], 'Out')
 
 
+@unittest.skipIf(
+    not core.is_compiled_with_cuda()
+    or not core.is_bfloat16_supported(core.CUDAPlace(0)),
+    "core is not compiled with CUDA and not support the bfloat16",
+)
+class TestFminBF16OP(OpTest):
+    def setUp(self):
+        self.op_type = "elementwise_fmin"
+        self.python_api = paddle.fmin
+        self.dtype = np.uint16
+        x = np.random.uniform(1, 1, [13, 17]).astype("float32")
+        sgn = np.random.choice([-1, 1], [13, 17]).astype("float32")
+        y = x + sgn * np.random.uniform(1, 1, [13, 17]).astype("float32")
+        out = np.fmin(x, y)
+        self.inputs = {
+            'X': convert_float_to_uint16(x),
+            'Y': convert_float_to_uint16(y),
+        }
+        self.outputs = {'Out': convert_float_to_uint16(out)}
+
+    def test_check_output(self):
+        place = core.CUDAPlace(0)
+        self.check_output_with_place(place)
+
+    def test_check_grad(self):
+        place = core.CUDAPlace(0)
+        self.check_grad_with_place(place, ['X', 'Y'], 'Out')
+
+
 if __name__ == "__main__":
     paddle.enable_static()
     unittest.main()