diff --git a/tensorflow/compiler/jit/xla_kernel_creator_util.cc b/tensorflow/compiler/jit/xla_kernel_creator_util.cc
index 3cc68f2a1a4..61c89d8a67a 100644
--- a/tensorflow/compiler/jit/xla_kernel_creator_util.cc
+++ b/tensorflow/compiler/jit/xla_kernel_creator_util.cc
@@ -80,31 +80,35 @@ Status CreateXlaKernel(FunctionLibraryRuntime* flr, const NodeDef& node_def,
 
   // Make sure that kernels have been registered on the JIT device.
   XlaOpRegistry::RegisterCompilationKernels();
-  RecursiveCompilabilityChecker::UncompilableNodesMap uncompilable_nodes_map;
-  if (!IsCompilable(flr, node_def, &uncompilable_nodes_map)) {
-    std::vector<RecursiveCompilabilityChecker::UncompilableNodeInfo>
-        uncompilable_node_info;
-    for (const auto& it : uncompilable_nodes_map) {
-      for (const auto& info : it.second.second) {
-        uncompilable_node_info.emplace_back(info);
+
+  // Only check for compilability if the MLIR bridge is not enabled.
+  if (!GetMlirCommonFlags()->tf_mlir_enable_mlir_bridge) {
+    RecursiveCompilabilityChecker::UncompilableNodesMap uncompilable_nodes_map;
+    if (!IsCompilable(flr, node_def, &uncompilable_nodes_map)) {
+      std::vector<RecursiveCompilabilityChecker::UncompilableNodeInfo>
+          uncompilable_node_info;
+      for (const auto& it : uncompilable_nodes_map) {
+        for (const auto& info : it.second.second) {
+          uncompilable_node_info.emplace_back(info);
+        }
       }
-    }
-    string message = absl::StrCat(
-        "Function invoked by the following node is not compilable: ",
-        SummarizeNodeDef(node_def, /*max_inputs_in_summary=*/10), ".\n");
-    absl::StrAppend(&message, "Uncompilable nodes:");
-    for (const auto& node_info : uncompilable_node_info) {
-      string node_message =
-          absl::StrCat("\n", node_info.name, ": ",
-                       node_info.uncompilable_reason, "\n", "\tStacktrace:\n");
-      for (const auto& stack_frame : node_info.stack_trace) {
-        absl::StrAppendFormat(&node_message, "\t\tNode: %s, function: %s\n",
-                              stack_frame.name, stack_frame.function_name);
+      string message = absl::StrCat(
+          "Function invoked by the following node is not compilable: ",
+          SummarizeNodeDef(node_def, /*max_inputs_in_summary=*/10), ".\n");
+      absl::StrAppend(&message, "Uncompilable nodes:");
+      for (const auto& node_info : uncompilable_node_info) {
+        string node_message = absl::StrCat("\n", node_info.name, ": ",
+                                           node_info.uncompilable_reason, "\n",
+                                           "\tStacktrace:\n");
+        for (const auto& stack_frame : node_info.stack_trace) {
+          absl::StrAppendFormat(&node_message, "\t\tNode: %s, function: %s\n",
+                                stack_frame.name, stack_frame.function_name);
+        }
+        absl::StrAppend(&message, node_message);
       }
-      absl::StrAppend(&message, node_message);
+      VLOG(1) << message;
+      return errors::InvalidArgument(message);
     }
-    VLOG(1) << message;
-    return errors::InvalidArgument(message);
   }
 
   // Get function body, constant args, and resource args.
diff --git a/tensorflow/compiler/tests/BUILD b/tensorflow/compiler/tests/BUILD
index d9450cb6364..c2b5000647d 100644
--- a/tensorflow/compiler/tests/BUILD
+++ b/tensorflow/compiler/tests/BUILD
@@ -123,7 +123,6 @@ tf_xla_py_test(
     name = "adagrad_da_test",
     size = "small",
     srcs = ["adagrad_da_test.py"],
-    enable_mlir_bridge = True,
     python_version = "PY3",
     tags = [
         "no_pip",  # TODO(b/149738646): fix pip install so these tests run on kokoro pip
@@ -161,7 +160,6 @@ tf_xla_py_test(
     srcs = ["add_n_test.py"],
     # TensorList ops are not implemented in the on-demand compilation model yet.
     disabled_backends = ["cpu_ondemand"],
-    enable_mlir_bridge = True,
     python_version = "PY3",
     tags = [
         "no_pip",  # TODO(b/149738646): fix pip install so these tests run on kokoro pip
@@ -689,7 +687,6 @@ tf_xla_py_test(
     name = "fft_test",
     size = "medium",
     srcs = ["fft_test.py"],
-    enable_mlir_bridge = True,
     python_version = "PY3",
     shard_count = 6,
     tags = [
@@ -929,7 +926,6 @@ tf_xla_py_test(
     name = "pooling_ops_test",
     size = "medium",
     srcs = ["pooling_ops_test.py"],
-    enable_mlir_bridge = True,
     python_version = "PY3",
     shard_count = 20,
     tags = [
@@ -1243,7 +1239,6 @@ tf_xla_py_test(
     name = "stack_ops_test",
     size = "small",
     srcs = ["stack_ops_test.py"],
-    enable_mlir_bridge = True,
     python_version = "PY3",
     tags = [
         "config-cuda-only",
@@ -1304,7 +1299,6 @@ tf_xla_py_test(
     srcs = ["tensor_array_ops_test.py"],
     # TensorArray ops are not implemented in the on-demand compilation model yet.
     disabled_backends = ["cpu_ondemand"],
-    enable_mlir_bridge = True,
     python_version = "PY3",
     tags = [
         "config-cuda-only",
@@ -1333,7 +1327,6 @@ tf_xla_py_test(
     srcs = ["tensor_list_ops_test.py"],
     # TensorList ops are not implemented in the on-demand compilation model yet.
     disabled_backends = ["cpu_ondemand"],
-    enable_mlir_bridge = True,
     python_version = "PY3",
     tags = [
         "no_pip",  # TODO(b/149738646): fix pip install so these tests run on kokoro pip
@@ -1889,7 +1882,6 @@ tf_xla_py_test(
     name = "special_math_test",
     size = "medium",
     srcs = ["special_math_test.py"],
-    enable_mlir_bridge = True,
     shard_count = 5,
     tags = [
         "no_pip",  # TODO(b/149738646): fix pip install so these tests run on kokoro pip
diff --git a/tensorflow/compiler/tf2xla/xla_compiler.cc b/tensorflow/compiler/tf2xla/xla_compiler.cc
index db54f2f6563..0045a7958b4 100644
--- a/tensorflow/compiler/tf2xla/xla_compiler.cc
+++ b/tensorflow/compiler/tf2xla/xla_compiler.cc
@@ -23,6 +23,7 @@ limitations under the License.
 #include "tensorflow/compiler/jit/defs.h"
 #include "tensorflow/compiler/jit/flags.h"
 #include "tensorflow/compiler/jit/shape_inference.h"
+#include "tensorflow/compiler/mlir/tensorflow/utils/compile_mlir_util.h"
 #include "tensorflow/compiler/tf2xla/graph_compiler.h"
 #include "tensorflow/compiler/tf2xla/rearrange_function_argument.h"
 #include "tensorflow/compiler/tf2xla/shape_util.h"
@@ -52,6 +53,7 @@ limitations under the License.
 #include "tensorflow/core/lib/hash/hash.h"
 #include "tensorflow/core/platform/logging.h"
 #include "tensorflow/core/protobuf/error_codes.pb.h"
+#include "tensorflow/core/protobuf/graph_debug_info.pb.h"
 #include "tensorflow/core/util/dump_graph.h"
 
 namespace tensorflow {
@@ -726,8 +728,18 @@ Status XlaCompiler::CompileFunction(
   }
 
   VLOG(1) << "====================================================";
-  TF_RETURN_IF_ERROR(
-      CompileGraph(options, function_id, std::move(graph), args, result));
+  if (GetMlirCommonFlags()->tf_mlir_enable_mlir_bridge) {
+    VLOG(1) << "Using MLIR bridge";
+    GraphDebugInfo debug_info;
+    TF_RETURN_IF_ERROR(CompileGraphToXlaHlo(
+        std::move(*graph), {args.data(), args.size()},
+        options_.device_type.type_string(), options.use_tuple_arg,
+        *options_.flib_def, debug_info, options_.shape_representation_fn,
+        result));
+  } else {
+    TF_RETURN_IF_ERROR(
+        CompileGraph(options, function_id, std::move(graph), args, result));
+  }
   VLOG(1) << "====================================================";
 
   cache_[{function_id, arg_vector}] = *result;