diff --git a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
index 35f4ff451cdb..8fdc5944fb91 100644
--- a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
@@ -2047,3 +2047,36 @@ def convert_broadcast_to(node, **kwargs):
     )
 
     return [tensor_node, expand_node]
+
+
+@mx_op.register("topk")
+def convert_topk(node, **kwargs):
+    """Map MXNet's topk operator attributes to onnx's TopK operator
+    and return the created node.
+    """
+    name, input_nodes, attrs = get_inputs(node, kwargs)
+
+    axis = int(attrs.get('axis', '-1'))
+    k = int(attrs.get('k', '1'))
+    ret_type = attrs.get('ret_typ')
+    dtype = attrs.get('dtype')
+    outputs = [name + '_output0']
+
+    if ret_type and ret_type == 'both':
+        if dtype and dtype == 'int64':
+            outputs.append(name + '_output1')
+        else:
+            raise NotImplementedError("ONNX expects indices to be of type int64")
+    else:
+        raise NotImplementedError("ONNX expects both value and indices as output")
+
+    topk_node = onnx.helper.make_node(
+        "TopK",
+        input_nodes,
+        outputs,
+        axis=axis,
+        k=k,
+        name=name
+    )
+
+    return [topk_node]
diff --git a/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py b/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
index cf95bfef09a3..bd48d26ef6ba 100644
--- a/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
+++ b/python/mxnet/contrib/onnx/onnx2mx/_import_helper.py
@@ -23,7 +23,7 @@
 from ._op_translations import tanh, arccos, arcsin, arctan, _cos, _sin, _tan
 from ._op_translations import softplus, shape, gather, lp_pooling, size
 from ._op_translations import ceil, floor, hardsigmoid, global_lppooling
-from ._op_translations import concat, hardmax
+from ._op_translations import concat, hardmax, topk
 from ._op_translations import leaky_relu, _elu, _prelu, _selu, softmax, fully_connected
 from ._op_translations import global_avgpooling, global_maxpooling, linalg_gemm
 from ._op_translations import sigmoid, pad, relu, matrix_multiplication, batch_norm
@@ -147,5 +147,6 @@
     'DepthToSpace'      : depthtospace,
     'SpaceToDepth'      : spacetodepth,
     'Hardmax'           : hardmax,
-    'LpNormalization'   : lpnormalization
+    'LpNormalization'   : lpnormalization,
+    'TopK'              : topk
 }
diff --git a/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py b/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
index 734b438581a5..627181d6ae21 100644
--- a/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/onnx2mx/_op_translations.py
@@ -779,3 +779,11 @@ def lpnormalization(attrs, inputs, proto_obj):
     axis = int(attrs.get("axis", -1))
     new_attrs.update(axis=axis)
     return 'norm', new_attrs, inputs
+
+
+def topk(attrs, inputs, proto_obj):
+    """Returns the top k elements in an input array along the given axis."""
+    new_attrs = translation_utils._add_extra_attributes(attrs,
+                                                        {'ret_typ': 'both',
+                                                         'dtype': 'int64'})
+    return 'topk', new_attrs, inputs
diff --git a/tests/python-pytest/onnx/test_cases.py b/tests/python-pytest/onnx/test_cases.py
index 89b60d15e84f..eb6b71896e28 100644
--- a/tests/python-pytest/onnx/test_cases.py
+++ b/tests/python-pytest/onnx/test_cases.py
@@ -78,7 +78,8 @@
              'test_max_',
              'test_softplus',
              'test_reduce_',
-             'test_split_equal'
+             'test_split_equal',
+             'test_top_k'
              ],
     'import': ['test_gather',
                'test_softsign',