diff --git a/python/tvm/relay/frontend/tflite.py b/python/tvm/relay/frontend/tflite.py
index be18bf622196b..96fcc480ad6e7 100644
--- a/python/tvm/relay/frontend/tflite.py
+++ b/python/tvm/relay/frontend/tflite.py
@@ -355,7 +355,23 @@ def convert_logistic(self, op):
         input_tensor = input_tensors[0]
         in_expr = self.get_expr(input_tensor.tensor_idx)
 
+        output_tensors = self.get_output_tensors(op)
+        assert len(output_tensors) == 1, "output tensors length should be 1"
+        output_tensor = output_tensors[0]
+        output_tensor_type = output_tensor.tensor.Type()
+        output_tensor_type_str = self.get_tensor_type_str(output_tensor_type)
+
+        if input_tensor.qnn_params:
+            in_expr = _qnn.op.dequantize(data=in_expr,
+                                         input_scale=input_tensor.qnn_params['scale'],
+                                         input_zero_point=input_tensor.qnn_params['zero_point'])
         out = _op.sigmoid(in_expr)
+        if output_tensor.qnn_params:
+            out = _qnn.op.quantize(data=out,
+                                   output_scale=output_tensor.qnn_params['scale'],
+                                   output_zero_point=output_tensor.qnn_params['zero_point'],
+                                   out_dtype=output_tensor_type_str)
+
         return out
 
     def convert_softmax(self, op):
diff --git a/tests/python/frontend/tflite/test_forward.py b/tests/python/frontend/tflite/test_forward.py
index 12ea429983e8c..c9ac2d73495e1 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -995,17 +995,24 @@ def test_forward_unpack():
 # Logistic
 # --------
 
-def _test_logistic(data):
+def _test_logistic(data, quantized=False):
     """ One iteration of LOGISTIC """
     with tf.Graph().as_default():
-        in_data = array_ops.placeholder(shape=data.shape, dtype=data.dtype)
-        out = math_ops.sigmoid(in_data)
-        compare_tflite_with_tvm(data, 'Placeholder:0', [in_data], [out])
+        in_data = [array_ops.placeholder(shape=data.shape, dtype='float32', name='in_0')]
+
+        if quantized:
+            inq_data = [tf.quantization.fake_quant_with_min_max_args(in_data[0], min=-100, max=100, name="inq_0")]
+            out = math_ops.sigmoid(inq_data)
+            out = tf.quantization.fake_quant_with_min_max_args(out, min=0, max=1, name="out")
+            compare_tflite_with_tvm(data, 'inq_0:0', inq_data, [out], quantized=True)
+        else:
+            out = math_ops.sigmoid(in_data)
+            compare_tflite_with_tvm(data, 'in_0:0', in_data, [out])
 
 def test_forward_logistic():
     """ LOGISTIC """
     _test_logistic(np.arange(6.0, dtype=np.float32).reshape((1, 6)))
-
+    _test_logistic(np.array(np.random.uniform(0, 255, (3, 6)), dtype=np.uint8), quantized=True)
 
 #######################################################################
 # Softmax