diff --git a/ngraph_bridge/ngraph_builder.cc b/ngraph_bridge/ngraph_builder.cc
index 9d9a0994d..3c79b4cfa 100644
--- a/ngraph_bridge/ngraph_builder.cc
+++ b/ngraph_bridge/ngraph_builder.cc
@@ -3327,8 +3327,17 @@ static Status TranslateQuantizeAndDequantizeV2Op(
       op->name(), ng_r_et, ng::Shape(), std::vector<float>({scale}));
   auto ng_offset = ConstructNgNode<ng::op::Constant>(
       op->name(), ng_q_et, ng::Shape(), std::vector<int>({0}));
-  ng::op::Quantize::RoundMode ng_round_mode =
-      ng::op::Quantize::RoundMode::ROUND_NEAREST_TOWARD_INFINITY;
+  ng::op::Quantize::RoundMode ng_round_mode;
+  string round_mode_string;
+  TF_RETURN_IF_ERROR(
+      GetNodeAttr(op->attrs(), "round_mode", &round_mode_string));
+  if (round_mode_string == "HALF_UP") {
+    ng_round_mode = ng::op::Quantize::RoundMode::ROUND_NEAREST_UPWARD;
+  } else if (round_mode_string == "HALF_TO_EVEN") {
+    ng_round_mode = ng::op::Quantize::RoundMode::ROUND_NEAREST_TOWARD_EVEN;
+  } else {
+    return errors::Internal("Tensorflow Rounding Mode not supported by Ngraph");
+  }
   auto ng_quant = ConstructNgNode<ng::op::Quantize>(
       op->name(), ng_input, ng_scale, ng_offset, ng_q_et, ng::AxisSet(),
       ng_round_mode);
@@ -3608,10 +3617,17 @@ static Status TranslateQuantizeV2Op(const Node* op,
   ng::element::Type ng_et;
   TF_RETURN_IF_ERROR(TFDataTypeToNGraphElementType(dtype, &ng_et));
 
-  // TODO: Only RoundMode = ROUND_NEAREST_TOWARD_EVEN is supported, for now.
-  // Support other modes later
-  ng::op::Quantize::RoundMode ng_round_mode =
-      ng::op::Quantize::RoundMode::ROUND_NEAREST_TOWARD_EVEN;
+  ng::op::Quantize::RoundMode ng_round_mode;
+  string round_mode_string;
+  TF_RETURN_IF_ERROR(
+      GetNodeAttr(op->attrs(), "round_mode", &round_mode_string));
+  if (round_mode_string == "HALF_UP") {
+    ng_round_mode = ng::op::Quantize::RoundMode::ROUND_NEAREST_UPWARD;
+  } else if (round_mode_string == "HALF_TO_EVEN") {
+    ng_round_mode = ng::op::Quantize::RoundMode::ROUND_NEAREST_TOWARD_EVEN;
+  } else {
+    return errors::Internal("Tensorflow Rounding Mode not supported by Ngraph");
+  }
 
   auto ng_node = ng::builder::ScaledQuantize(ng_input, ng_min, ng_max, ng_et,
                                              ng::AxisSet(), ng_round_mode);
diff --git a/test/test_array_ops.cpp b/test/test_array_ops.cpp
index 7bbdbbaa8..a07e26ec9 100644
--- a/test/test_array_ops.cpp
+++ b/test/test_array_ops.cpp
@@ -797,7 +797,61 @@ TEST(ArrayOps, QuantizeAndDequantizeV2x8xtruexfalse) {
                         output_datatypes, sess_run_fetchoutputs);
 
   opexecuter.RunTest();
-}  // end of test op QuantizeAndDequantizeV2x8xtruexfalse
+}
+
+TEST(ArrayOps, QuantizeAndDequantizeV2RoundingMode1) {
+  Scope root = Scope::NewRootScope();
+  int dim1 = 2;
+  int dim2 = 3;
+
+  Tensor A(DT_FLOAT, TensorShape({dim1, dim2}));
+  AssignInputValues<float>(A, {0.9, 3.4, 2.6, 5.4, 4.2, 4.5});
+
+  auto attrs = ops::QuantizeAndDequantizeV2::Attrs();
+  attrs.num_bits_ = 8;
+  attrs.range_given_ = true;
+  attrs.signed_input_ = true;
+  attrs.round_mode_ = "HALF_UP";
+
+  vector<int> static_input_indexes = {1, 2};
+  ops::QuantizeAndDequantizeV2 R =
+      ops::QuantizeAndDequantizeV2(root, A, 0.0f, 127.0f, attrs);
+
+  vector<DataType> output_datatypes = {DT_FLOAT};
+
+  std::vector<Output> sess_run_fetchoutputs = {R.output};
+  OpExecuter opexecuter(root, "QuantizeAndDequantizeV2", static_input_indexes,
+                        output_datatypes, sess_run_fetchoutputs);
+
+  opexecuter.RunTest();
+}
+
+TEST(ArrayOps, QuantizeAndDequantizeV2RoundingMode2) {
+  Scope root = Scope::NewRootScope();
+  int dim1 = 2;
+  int dim2 = 3;
+
+  Tensor A(DT_FLOAT, TensorShape({dim1, dim2}));
+  AssignInputValues<float>(A, {0.9, 3.4, 2.6, 5.4, 4.2, 4.5});
+
+  auto attrs = ops::QuantizeAndDequantizeV2::Attrs();
+  attrs.num_bits_ = 8;
+  attrs.range_given_ = true;
+  attrs.signed_input_ = true;
+  attrs.round_mode_ = "HALF_TO_EVEN";
+
+  vector<int> static_input_indexes = {1, 2};
+  ops::QuantizeAndDequantizeV2 R =
+      ops::QuantizeAndDequantizeV2(root, A, 0.0f, 127.0f, attrs);
+
+  vector<DataType> output_datatypes = {DT_FLOAT};
+
+  std::vector<Output> sess_run_fetchoutputs = {R.output};
+  OpExecuter opexecuter(root, "QuantizeAndDequantizeV2", static_input_indexes,
+                        output_datatypes, sess_run_fetchoutputs);
+
+  opexecuter.RunTest();
+}  // end of test op QuantizeAndDequantizeV2x8xtruextrue
 
 // CPU only supports QuantizedConcat with DT_QINT32 and DT_QUINT8
 TEST(ArrayOps, QuantizedConcat) {