diff --git a/akg b/akg
index c460176523d039c8995f1d71089753725ebc0792..df57a6cf9450e347d1854687d1fe66a420ee3b35 160000
--- a/akg
+++ b/akg
@@ -1 +1 @@
-Subproject commit c460176523d039c8995f1d71089753725ebc0792
+Subproject commit df57a6cf9450e347d1854687d1fe66a420ee3b35
diff --git a/mindspore/ccsrc/kernel/kernel_query.cc b/mindspore/ccsrc/kernel/kernel_query.cc
index 6538c28765c298ae4386a1735c39d096b101a18d..16aa8de3c28d1642c091f44e1950a70471facc3c 100755
--- a/mindspore/ccsrc/kernel/kernel_query.cc
+++ b/mindspore/ccsrc/kernel/kernel_query.cc
@@ -23,6 +23,7 @@
 #include "kernel/tbe/tbe_kernel_select/tbe_kernel_select.h"
 #include "kernel/akg/akg_kernel_metadata.h"
 #include "session/anf_runtime_algorithm.h"
+#include "utils/context/ms_context.h"
 
 namespace mindspore {
 namespace kernel {
@@ -96,6 +97,12 @@ void KernelQuery(const CNodePtr &kernel_node, std::vector<std::shared_ptr<kernel
 
   std::string op_name = AnfAlgo::GetCNodeName(kernel_node);
 
+  auto context_ptr = MsContext::GetInstance();
+  MS_EXCEPTION_IF_NULL(context_ptr);
+  if (context_ptr->enable_graph_kernel() && IsPrimitiveCNode(kernel_node, prim::kPrimBatchMatMul)) {
+    kernel_type = KernelType::AKG_KERNEL;
+  }
+
   switch (kernel_type) {
     case KernelType::AKG_KERNEL:
       AkgMetadataInfo(kernel_node, kernel_info_list);
diff --git a/mindspore/ops/_op_impl/akg/__init__.py b/mindspore/ops/_op_impl/akg/__init__.py
index f38b99f5e4f02f75bcff0c0a147761e77a013383..fd86dbf999160ecbced337b9f2427caaece7fd28 100644
--- a/mindspore/ops/_op_impl/akg/__init__.py
+++ b/mindspore/ops/_op_impl/akg/__init__.py
@@ -47,6 +47,7 @@ from .gather_v2 import _gather_v2_akg
 from .less import _less_akg
 from .log import _log_akg
 from .matmul import _matmul_akg
+from .batchmatmul import _batchmatmul_akg
 from .max_pool_grad_with_argmax import _max_pool_grad_with_argmax_akg
 from .max_pool_with_argmax import _max_pool_with_argmax_akg
 from .max import _max_akg
diff --git a/mindspore/ops/_op_impl/akg/batchmatmul.py b/mindspore/ops/_op_impl/akg/batchmatmul.py
new file mode 100644
index 0000000000000000000000000000000000000000..f5da71aa25e7634bb6515ef7516d73d21daf371e
--- /dev/null
+++ b/mindspore/ops/_op_impl/akg/batchmatmul.py
@@ -0,0 +1,73 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+"""BatchMatMul op"""
+from mindspore.ops.op_info_register import op_info_register
+
+
+@op_info_register("""{
+    "op_name": "BatchMatMul",
+    "imply_type": "AutoDiff",
+    "fusion_type": "OPAQUE",
+    "attr": [
+        {
+            "name": "transpose_a",
+            "param_type": "optional",
+            "type": "bool"
+        },
+        {
+            "name": "transpose_b",
+            "param_type": "optional",
+            "type": "bool"
+        }
+    ],
+    "inputs": [
+        {
+            "index": 0,
+            "dtype": [
+                "float16"
+            ],
+            "format": [
+                "FRACTAL_NZ"
+            ],
+            "name": "x1"
+        },
+        {
+            "index": 1,
+            "dtype": [
+                "float16"
+            ],
+            "format": [
+                "FRACTAL_NZ"
+            ],
+            "name": "x2"
+        }
+    ],
+    "outputs": [
+        {
+            "index": 0,
+            "dtype": [
+                "float16"
+            ],
+            "format": [
+                "FRACTAL_NZ"
+            ],
+            "name": "output"
+        }
+    ]
+}""")
+def _batchmatmul_akg():
+    """BatchMatMul AKG register"""
+    return