diff --git a/tensorflow/lite/build_def.bzl b/tensorflow/lite/build_def.bzl
index fb4046731cb..afc761570ea 100644
--- a/tensorflow/lite/build_def.bzl
+++ b/tensorflow/lite/build_def.bzl
@@ -635,6 +635,8 @@ def gen_zip_test(
         flags += " --ignore_converter_errors --run_with_flex"
     elif conversion_mode == "forward-compat":
         flags += " --make_forward_compat_test"
+    elif conversion_mode == "mlir-quant":
+        flags += " --mlir_quantizer"
     if test_name.startswith(merged_test_model_name() + "_"):
         flags += flags_for_merged_test_models(test_name, conversion_mode)
 
diff --git a/tensorflow/lite/testing/generate_examples.py b/tensorflow/lite/testing/generate_examples.py
index bc87fde9467..ed08373b534 100644
--- a/tensorflow/lite/testing/generate_examples.py
+++ b/tensorflow/lite/testing/generate_examples.py
@@ -91,6 +91,10 @@ parser.add_argument(
     help=("Comma-separated list of test set names to generate. "
           "If not specified, a test set is selected by parsing the name of "
           "'zip_to_output' file."))
+parser.add_argument(
+    "--mlir_quantizer",
+    action="store_true",
+    help=("Whether the new MLIR quantizer is being used."))
 
 
 # Toco binary path provided by the generate rule.
@@ -116,6 +120,7 @@ def main(unused_args):
   options.tflite_convert_function = toco_convert.toco_convert
   options.no_tests_limit = FLAGS.no_tests_limit
   options.no_conversion_report = FLAGS.no_conversion_report
+  options.mlir_quantizer = FLAGS.mlir_quantizer
 
   if FLAGS.test_sets:
     test_sets = FLAGS.test_sets.split(",")
diff --git a/tensorflow/lite/testing/generate_examples_lib.py b/tensorflow/lite/testing/generate_examples_lib.py
index 009a407d70e..bb7e9dbde9b 100644
--- a/tensorflow/lite/testing/generate_examples_lib.py
+++ b/tensorflow/lite/testing/generate_examples_lib.py
@@ -238,6 +238,7 @@ class Options(object):
     # TODO(juhoha): Separate the state from the options.
     self.multi_gen_state = None
     self.use_experimental_converter = False
+    self.mlir_quantizer = False
 
 
 def _prepare_dir(options):
@@ -273,7 +274,10 @@ def generate_examples(options):
   else:
     # Remove suffixes to extract the test name from the output name.
     test_name = re.sub(
-        r"(_(|toco-flex|forward-compat|edgetpu))?\.zip$", "", out, count=1)
+        r"(_(|toco-flex|forward-compat|edgetpu|mlir-quant))?\.zip$",
+        "",
+        out,
+        count=1)
 
   test_function_name = "make_%s_tests" % test_name
   test_function = get_test_function(test_function_name)
@@ -313,7 +317,10 @@ def generate_multi_set_examples(options, test_sets):
 
       # Remove suffix and set test_name to run proper test generation function.
       multi_gen_state.test_name = re.sub(
-          r"(_(|toco-flex|forward-compat))?$", "", test_name, count=1)
+          r"(_(|toco-flex|forward-compat|mlir-quant))?$",
+          "",
+          test_name,
+          count=1)
       # Set label base path to write test data files with proper path.
       multi_gen_state.label_base_path = os.path.join(
           os.path.dirname(zip_path), test_name + ".zip")
diff --git a/tensorflow/lite/testing/toco_convert.py b/tensorflow/lite/testing/toco_convert.py
index 48c19c49686..5216c1febbe 100644
--- a/tensorflow/lite/testing/toco_convert.py
+++ b/tensorflow/lite/testing/toco_convert.py
@@ -115,6 +115,7 @@ def toco_convert(options, graph_def, input_tensors, output_tensors, **kwargs):
           graphdef_file.name, input_arrays, output_tensors, input_shapes)
 
       converter.experimental_new_converter = options.use_experimental_converter
+      converter._experimental_new_quantizer = options.mlir_quantizer  # pylint: disable=protected-access
       converter.optimizations = [tf.lite.Optimize.DEFAULT]
 
       if fully_quantize:
diff --git a/tensorflow/lite/testing/zip_test_utils.py b/tensorflow/lite/testing/zip_test_utils.py
index 1b4460461b6..e7ade88e787 100644
--- a/tensorflow/lite/testing/zip_test_utils.py
+++ b/tensorflow/lite/testing/zip_test_utils.py
@@ -368,6 +368,11 @@ def make_zip_of_tests(options,
           "fully_quantize", False) or param_dict.get("quant_16x8", False)):
         continue
 
+      # Skips the new quantizer tests when `fully_quantize` is set to false
+      # or it is not set.
+      if options.mlir_quantizer and not param_dict.get("fully_quantize", False):
+        continue
+
       def generate_inputs_outputs(tflite_model_binary,
                                   min_value=0,
                                   max_value=255):