diff --git a/python/tvm/relay/frontend/tflite.py b/python/tvm/relay/frontend/tflite.py
index 532318b804da..043da8704221 100644
--- a/python/tvm/relay/frontend/tflite.py
+++ b/python/tvm/relay/frontend/tflite.py
@@ -2432,11 +2432,6 @@ def convert_reverse_sequence(self, op):
         except ImportError:
             raise ImportError("The tflite package must be installed")
 
-        if self.is_quantized(op):
-            raise tvm.error.OpNotImplemented(
-                "TFLite does not support quantized REVERSE_SEQUENCE operator yet."
-            )
-
         input_tensors = self.get_input_tensors(op)
         assert len(input_tensors) == 2, "input tensors length should be 2"
 
diff --git a/tests/python/frontend/tflite/test_forward.py b/tests/python/frontend/tflite/test_forward.py
index f60166702454..8780ced60efa 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -4272,28 +4272,43 @@ def test_forward_spacetodepth():
 #######################################################################
 # ReverseSequence
 # ---------------
-
-
-def _test_reverse_sequence(shape, dtype, seq_lengths, batch_axis, seq_axis):
+def _test_reverse_sequence(shape, dtype, seq_lengths, batch_axis, seq_axis, quantized=False):
     """One iteration of reverse_sequence operation with given data and attributes"""
-
     data = np.random.uniform(0, 100, size=shape).astype(dtype)
     with tf.Graph().as_default():
-        in_data = array_ops.placeholder(dtype=dtype, name="input", shape=shape)
-        out = tf.reverse_sequence(
-            in_data, seq_lengths=seq_lengths, batch_axis=batch_axis, seq_axis=seq_axis
-        )
-
-        compare_tflite_with_tvm(data, "input", [in_data], [out])
+        in_data = array_ops.placeholder(dtype="float32", name="in_0", shape=shape)
+        if quantized:
+            inq_data = tf.quantization.fake_quant_with_min_max_args(
+                in_data, min=0, max=10, name="inq_0"
+            )
+            input_range = {"inq_0": (-10, 10)}
+            out = tf.reverse_sequence(
+                inq_data, seq_lengths=seq_lengths, batch_axis=batch_axis, seq_axis=seq_axis
+            )
+            out = tf.quantization.fake_quant_with_min_max_args(out, min=0, max=6, name="out")
+            compare_tflite_with_tvm(
+                data, "inq_0:0", [inq_data], [out], quantized=True, input_range=input_range
+            )
+        else:
+            out = tf.reverse_sequence(
+                in_data, seq_lengths=seq_lengths, batch_axis=batch_axis, seq_axis=seq_axis
+            )
+            compare_tflite_with_tvm(data, "in_0:0", [in_data], [out])
 
 
 def test_forward_reverse_sequence():
+    """Tests the reverse_sequence function with different input shapes, data types."""
     if package_version.parse(tf.VERSION) >= package_version.parse("1.14.0"):
         _test_reverse_sequence([4, 3], "float32", [3, 2, 1], 1, 0)
         _test_reverse_sequence([4, 3], "float32", [3, 2, 1, 3], 0, 1)
         _test_reverse_sequence([2, 3, 3, 3], "float32", [2, 3, 2], 2, 1)
         _test_reverse_sequence([2, 4, 6, 4, 5], "float32", [5, 3], 0, 2)
         _test_reverse_sequence([2, 4, 6, 4, 5], "float32", [5, 3, 1, 4], 3, 2)
+        _test_reverse_sequence([4, 3], "uint8", [3, 2, 1], 1, 0, quantized=True)
+        _test_reverse_sequence([4, 3], "uint8", [3, 2, 1, 3], 0, 1, quantized=True)
+        _test_reverse_sequence([2, 3, 3, 3], "uint8", [2, 3, 2], 2, 1, quantized=True)
+        _test_reverse_sequence([2, 4, 6, 4, 5], "uint8", [5, 3], 0, 2, quantized=True)
+        _test_reverse_sequence([2, 4, 6, 4, 5], "uint8", [5, 3, 1, 4], 3, 2, quantized=True)
 
 
 #######################################################################