diff --git a/src/tim/vx/ops/stack_test.cc b/src/tim/vx/ops/stack_test.cc
new file mode 100644
index 0000000..a17575b
--- /dev/null
+++ b/src/tim/vx/ops/stack_test.cc
@@ -0,0 +1,181 @@
+/****************************************************************************
+*
+*    Copyright (c) 2021 Vivante Corporation
+*
+*    Permission is hereby granted, free of charge, to any person obtaining a
+*    copy of this software and associated documentation files (the "Software"),
+*    to deal in the Software without restriction, including without limitation
+*    the rights to use, copy, modify, merge, publish, distribute, sublicense,
+*    and/or sell copies of the Software, and to permit persons to whom the
+*    Software is furnished to do so, subject to the following conditions:
+*
+*    The above copyright notice and this permission notice shall be included in
+*    all copies or substantial portions of the Software.
+*
+*    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+*    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+*    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+*    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+*    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+*    FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
+*    DEALINGS IN THE SOFTWARE.
+*
+*****************************************************************************/
+#include "tim/vx/context.h"
+#include "tim/vx/graph.h"
+#include "tim/vx/ops/stack.h"
+
+#include "gtest/gtest.h"
+
+TEST(Stack, shape_2_3_axis_2) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType input_shape({2,3});
+    tim::vx::ShapeType output_shape({2,3,2});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+        input_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
+        output_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = {
+        1,4,
+        2,5,
+        3,6
+    };
+    std::vector<float> in_data2 = {
+        1,4,
+        2,5,
+        3,6
+    };
+    std::vector<float> golden = {
+        1,4,
+        2,5,
+        3,6,
+
+        1,4,
+        2,5,
+        3,6
+        };
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(
+        in_data1.data(), in_data1.size() * sizeof(float)));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(
+        in_data2.data(), in_data2.size() * sizeof(float)));
+    auto op = graph->CreateOperation<tim::vx::ops::Stack>(2, 2);
+    (*op).BindInputs({input_tensor1,input_tensor2}).BindOutputs(
+        {output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    std::vector<float> output(golden.size());
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+
+TEST(Stack, shape_2_3_axis_1) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType input_shape({2,3});
+    tim::vx::ShapeType output_shape({2,3,2});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+        input_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
+        output_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = {
+        1,4,
+        2,5,
+        3,6
+    };
+    std::vector<float> in_data2 = {
+        1,4,
+        2,5,
+        3,6
+    };
+    std::vector<float> golden = {
+        1,4,
+        1,4,
+        2,5,
+
+        2,5,
+        3,6,
+        3,6,
+        };
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(
+        in_data1.data(), in_data1.size() * sizeof(float)));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(
+        in_data2.data(), in_data2.size() * sizeof(float)));
+    auto op = graph->CreateOperation<tim::vx::ops::Stack>(1, 2);
+    (*op).BindInputs({input_tensor1,input_tensor2}).BindOutputs(
+        {output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    std::vector<float> output(golden.size());
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}
+
+TEST(Stack, shape_2_3_axis_0) {
+    auto ctx = tim::vx::Context::Create();
+    auto graph = ctx->CreateGraph();
+
+    tim::vx::ShapeType input_shape({2,3});
+    tim::vx::ShapeType output_shape({2,3,2});
+    tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32,
+        input_shape, tim::vx::TensorAttribute::INPUT);
+    tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32,
+        output_shape, tim::vx::TensorAttribute::OUTPUT);
+
+    auto input_tensor1 = graph->CreateTensor(input_spec);
+    auto input_tensor2 = graph->CreateTensor(input_spec);
+    auto output_tensor = graph->CreateTensor(output_spec);
+
+    std::vector<float> in_data1 = {
+        1,4,
+        2,5,
+        3,6
+    };
+    std::vector<float> in_data2 = {
+        1,4,
+        2,5,
+        3,6
+    };
+    std::vector<float> golden = {
+        1, 1,
+        4, 4,
+        2, 2,
+
+        5, 5,
+        3, 3,
+        6, 6
+        };
+
+    EXPECT_TRUE(input_tensor1->CopyDataToTensor(
+        in_data1.data(), in_data1.size() * sizeof(float)));
+    EXPECT_TRUE(input_tensor2->CopyDataToTensor(
+        in_data2.data(), in_data2.size() * sizeof(float)));
+    auto op = graph->CreateOperation<tim::vx::ops::Stack>(0, 2);
+    (*op).BindInputs({input_tensor1,input_tensor2}).BindOutputs(
+        {output_tensor});
+
+    EXPECT_TRUE(graph->Compile());
+    EXPECT_TRUE(graph->Run());
+
+    std::vector<float> output(golden.size());
+    EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+    EXPECT_EQ(golden, output);
+}