diff --git a/Tests/Backend/CNTK/CNTKBackendTest.cs b/Tests/Backend/CNTK/CNTKBackendTest.cs
index cc5c30b..d45fbfb 100644
--- a/Tests/Backend/CNTK/CNTKBackendTest.cs
+++ b/Tests/Backend/CNTK/CNTKBackendTest.cs
@@ -299,6 +299,61 @@ public void cntk_sum_test()
             }
         }
 
+        [Test]
+        public void cntk_sum_test_direct_api()
+        {
+            double[][] r;
+
+            r = sum(null); // first, a sanity check to verify that values are being read correctly
+            double[,] d = new double[2, 3]; // result will be { 0, 1, 2, 3, 4, 5, 6 }
+            Buffer.BlockCopy(r[0], 0, d, 0, sizeof(double) * d.Length);
+            Assert.AreEqual(new[,] { { 1, 2, 3 }, { 4, 5, 6 } }, d); // ok
+
+            r = sum(0, 1); // sum over all axes
+            double a = r[0][0]; // result will be { 21 }
+            Assert.AreEqual(21, a); // ok
+
+            r = sum(0); // sum over first axis
+            double[] b = r[0]; // result will be { 3, 7, 11 }
+            Assert.AreEqual(new[] { 5.0, 7.0, 9.0 }, b); // fails
+
+            r = sum(1); // sum over second axis
+            double[] c = r[0]; // result will be { 9, 12 }
+            Assert.AreEqual(new[] { 6.0, 15.0 }, b);  // fails
+        }
+
+        private static double[][] sum(params int[] axes)
+        {
+            var arr = new[]
+            {
+                /*                            total:
+                /*       */ 1.0, 2.0, 3.0, /*  6.0 */
+                /*       */ 4.0, 5.0, 6.0, /* 15.0 */
+                /* total:   5.0, 7.0, 9.0     21.0 */ 
+            };
+
+            var shape = NDShape.CreateNDShape(new[] { 2, 3 });
+            Value vx = Value.CreateBatch(shape, arr, DeviceDescriptor.CPUDevice, readOnly: true);
+            Variable x = Variable.InputVariable(shape, CNTK.DataType.Double, name: "input");
+
+            CNTK.Function f;
+            if (axes == null)
+            {
+                f = CNTKLib.Alias(x);
+            }
+            else
+            {
+                var axisVector = new AxisVector(axes.Select(ax => new Axis(ax)).ToArray());
+                f = CNTKLib.ReduceSum(x, axis: axisVector);
+            }
+
+            var inputs = new Dictionary<Variable, Value>() { { x, vx } };
+            var outputs = new Dictionary<Variable, Value>() { { f, null } };
+            f.Evaluate(inputs, outputs, DeviceDescriptor.CPUDevice);
+            var r = outputs[f].GetDenseData<double>((Variable)f);
+            return r.Select(ri => ri.ToArray()).ToArray();
+        }
+
         [Test]
         public void cntk_mean_test()
         {