diff --git a/jax_ai_stack/tests/test_tf_with_orbax_export.py b/jax_ai_stack/tests/test_tf_with_orbax_export.py
new file mode 100644
index 0000000..9b77f7c
--- /dev/null
+++ b/jax_ai_stack/tests/test_tf_with_orbax_export.py
@@ -0,0 +1,83 @@
+# Copyright 2024 The JAX Authors.
+#
+# 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
+#
+#     https://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.
+
+import contextlib
+import tempfile
+import unittest
+
+import jax.numpy as jnp
+import numpy as np
+from orbax.export import ExportManager, JaxModule, ServingConfig
+import tensorflow as tf
+
+
+class NNXTFDSTest(unittest.TestCase):
+  tmp_dir: tempfile.TemporaryDirectory
+
+  def setUp(self):
+    self.tmp_dir = tempfile.TemporaryDirectory()
+
+    if hasattr(self, 'enterContext'):  # Python 3.11 or newer
+      self.enterContext(self.tmp_dir)
+    else:
+      with contextlib.ExitStack() as stack:
+        stack.enter_context(self.tmp_dir)
+        self.addCleanup(stack.pop_all().close)
+
+  def test_tf_model_with_checkpoint(self):
+    params = {'a': np.array(5.0), 'b': np.array(1.1), 'c': np.array(0.55)}
+
+    def model_fn(params, inputs):
+      a, b, c = params['a'], params['b'], params['c']
+      return a * jnp.sin(inputs) + b * inputs + c
+
+    def preprocess(inputs):
+      norm_inputs = tf.nest.map_structure(
+          lambda x: x / tf.math.reduce_max(x), inputs
+      )
+      return norm_inputs
+
+    def postprocess(model_fn_outputs):
+      return {'outputs': model_fn_outputs}
+
+    inputs = tf.random.normal([16], dtype=tf.float32)
+
+    model_outputs = postprocess(model_fn(params, np.array(preprocess(inputs))))
+
+    jax_module = JaxModule(params, model_fn)
+    export_mgr = ExportManager(
+        jax_module,
+        [
+            ServingConfig(
+                'serving_default',
+                input_signature=[tf.TensorSpec(shape=[16], dtype=tf.float32)],
+                tf_preprocessor=preprocess,
+                tf_postprocessor=postprocess,
+            ),
+        ],
+    )
+    export_mgr.save(self.tmp_dir.name)
+    loaded_model = tf.saved_model.load(self.tmp_dir.name)
+    loaded_model_outputs = loaded_model(inputs)
+
+    np.testing.assert_allclose(
+        model_outputs['outputs'],
+        loaded_model_outputs['outputs'],
+        atol=1e-5,
+        rtol=1e-5,
+    )
+
+
+if __name__ == '__main__':
+  unittest.main()