diff --git a/src/armnnTfLiteParser/test/Conv3D.cpp b/src/armnnTfLiteParser/test/Conv3D.cpp
new file mode 100644
index 0000000..32cd6fe
--- /dev/null
+++ b/src/armnnTfLiteParser/test/Conv3D.cpp
@@ -0,0 +1,286 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ParserFlatbuffersFixture.hpp"
+#include <sstream>
+
+TEST_SUITE("TensorflowLiteParser_Conv3D")
+{
+struct SimpleConv3DFixture : public ParserFlatbuffersFixture
+{
+    explicit SimpleConv3DFixture()
+    {
+        m_JsonString = R"(
+            {
+                "version": 3,
+                "operator_codes": [ { "builtin_code": "CONV_3D" } ],
+                "subgraphs": [ {
+                    "tensors": [
+                        {
+                            "shape": [ 1, 2, 3, 3, 1 ],
+                            "type": "UINT8",
+                            "buffer": 0,
+                            "name": "inputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                            "shape": [ 1, 1, 1, 1, 1 ],
+                            "type": "UINT8",
+                            "buffer": 1,
+                            "name": "outputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 511.0 ],
+                                "scale": [ 2.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                            "shape": [ 2, 3, 3, 1, 1 ],
+                            "type": "UINT8",
+                            "buffer": 2,
+                            "name": "filterTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        }
+                    ],
+                    "inputs": [ 0 ],
+                    "outputs": [ 1 ],
+                    "operators": [
+                        {
+                            "opcode_index": 0,
+                            "inputs": [ 0, 2 ],
+                            "outputs": [ 1 ],
+                            "builtin_options_type": "Conv3DOptions",
+                            "builtin_options": {
+                                "padding": "VALID",
+                                "stride_d": 1,
+                                "stride_w": 1,
+                                "stride_h": 1,
+                                "fused_activation_function": "NONE"
+                            },
+                            "custom_options_format": "FLEXBUFFERS"
+                        }
+                    ],
+                } ],
+                "buffers" : [
+                    { },
+                    { },
+                    { "data": [ 2,1,0,  6,2,1, 4,1,2,
+                                1,2,1,  2,0,2, 2,1,1 ], },
+                    { },
+                ]
+            }
+        )";
+        SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+    }
+};
+
+TEST_CASE_FIXTURE(SimpleConv3DFixture, "ParseSimpleConv3D")
+{
+    RunTest<5, armnn::DataType::QAsymmU8>(
+        0,
+        {
+            1, 2, 3,
+            4, 5, 6,
+            7, 8, 9,
+
+            10, 11, 12,
+            13, 14, 15,
+            16, 17, 18,
+        },
+        // Due to the output scaling we need to half the values.
+        {
+            (1*2 + 2*1 + 3*0 +
+             4*6 + 5*2 + 6*1 +
+             7*4 + 8*1 + 9*2 +
+
+             10*1 + 11*2 + 12*1 +
+             13*2 + 14*0 + 15*2 +
+             16*2 + 17*1 + 18*1) /2
+        });
+}
+struct Conv3DWithBiasesFixture : public ParserFlatbuffersFixture
+{
+    explicit Conv3DWithBiasesFixture(const std::string& inputShape,
+                                     const std::string& outputShape,
+                                     const std::string& filterShape,
+                                     const std::string& filterData,
+                                     const std::string& biasShape,
+                                     const std::string& biasData,
+                                     const std::string& strides,
+                                     const std::string& activation="NONE",
+                                     const std::string& filterScale="1.0",
+                                     const std::string& filterZeroPoint="0",
+                                     const std::string& outputScale="1.0",
+                                     const std::string& outputZeroPoint="0")
+    {
+        m_JsonString = R"(
+            {
+                "version": 3,
+                "operator_codes": [ { "builtin_code": "CONV_3D" } ],
+                "subgraphs": [ {
+                    "tensors": [
+                        {
+                            "shape": )" + inputShape + R"(,
+                            "type": "UINT8",
+                            "buffer": 0,
+                            "name": "inputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        },
+                        {
+                            "shape": )" + outputShape + R"(,
+                            "type": "UINT8",
+                            "buffer": 1,
+                            "name": "outputTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 511.0 ],
+                                "scale": [ )" + outputScale + R"( ],
+                                "zero_point": [ )" + outputZeroPoint + R"( ],
+                            }
+                        },
+                        {
+                            "shape": )" + filterShape + R"( ,
+                            "type": "UINT8",
+                            "buffer": 2,
+                            "name": "filterTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ )" + filterScale + R"( ],
+                                "zero_point": [ )" + filterZeroPoint + R"( ],
+                            }
+                        },
+                        {
+                            "shape": )" + biasShape + R"( ,
+                            "type": "INT32",
+                            "buffer": 3,
+                            "name": "biasTensor",
+                            "quantization": {
+                                "min": [ 0.0 ],
+                                "max": [ 255.0 ],
+                                "scale": [ 1.0 ],
+                                "zero_point": [ 0 ],
+                            }
+                        }
+                    ],
+                    "inputs": [ 0 ],
+                    "outputs": [ 1 ],
+                    "operators": [
+                        {
+                            "opcode_index": 0,
+                            "inputs": [ 0, 2, 3 ],
+                            "outputs": [ 1 ],
+                            "builtin_options_type": "Conv3DOptions",
+                            "builtin_options": {
+                                "padding": "SAME",
+                                "stride_d": )" + strides + R"(,
+                                "stride_w": )" + strides + R"(,
+                                "stride_h": )" + strides + R"(,
+                                "fused_activation_function": )" + activation + R"(
+                            },
+                            "custom_options_format": "FLEXBUFFERS"
+                        }
+                    ],
+                } ],
+                "buffers" : [
+                    { },
+                    { },
+                    { "data": )" + filterData + R"(, },
+                    { "data": )" + biasData + R"(, },
+                ]
+            }
+        )";
+        SetupSingleInputSingleOutput("inputTensor", "outputTensor");
+    }
+};
+
+struct SimpleConv3DWithBiasesFixture : Conv3DWithBiasesFixture
+{
+    SimpleConv3DWithBiasesFixture()
+    : Conv3DWithBiasesFixture("[ 1, 2, 2, 2, 1 ]",      // inputShape
+                              "[ 1, 2, 2, 2, 1 ]",      // outputShape
+                              "[ 2, 2, 2, 1, 1 ]",      // filterShape
+                              "[ 2,1, 1,0, 0,1, 1,1 ]", // filterData
+                              "[ 1 ]",                  // biasShape
+                              "[ 5, 0, 0, 0 ]",         // biasData
+                              "1")                      // stride d, w and h
+    {}
+};
+
+TEST_CASE_FIXTURE(SimpleConv3DWithBiasesFixture, "ParseConv3DWithBias")
+{
+    RunTest<5,
+            armnn::DataType::QAsymmU8>(0,
+                                       { 1, 2, 3, 4, 5, 6, 7, 8 },
+                                       { 33, 21, 23, 13, 28, 25, 27, 21 });
+}
+
+TEST_CASE_FIXTURE(SimpleConv3DWithBiasesFixture, "ParseDynamicConv3DWithBias")
+{
+    RunTest<5,
+            armnn::DataType::QAsymmU8,
+            armnn::DataType::QAsymmU8>(0,
+                                       { { "inputTensor", { 2, 4, 6, 8, 10, 12, 14, 16 } } },
+                                       { { "outputTensor", {  61, 37, 41, 21, 51, 45, 49, 37 } } },
+                                       true);
+}
+
+struct Relu6Conv3DWithBiasesFixture : Conv3DWithBiasesFixture
+{
+    Relu6Conv3DWithBiasesFixture()
+    : Conv3DWithBiasesFixture("[ 1, 2, 2, 2, 1 ]",       // inputShape
+                              "[ 1, 2, 2, 2, 1 ]",       // outputShape
+                              "[ 2, 2, 2, 1, 1 ]",       // filterShape
+                              "[ 2,1, 1,0, 0,1, 1,1 ]",  // filterData
+                              "[ 1 ]",                   // biasShape
+                              "[ 0, 0, 0, 0 ]",          // biasData
+                              "1",                       // stride d, w, and h
+                              "RELU6",                   // activation
+                              "1.0",                     // filter scale
+                              "0",                       // filter zero point
+                              "2.0",                     // output scale
+                              "0")                       // output zero point
+    {}
+};
+
+TEST_CASE_FIXTURE(Relu6Conv3DWithBiasesFixture, "ParseConv3DAndRelu6WithBias")
+{
+    uint8_t relu6Min = 6 / 2; // Divide by output scale
+
+    RunTest<5, armnn::DataType::QAsymmU8>(
+        0,
+        {
+           1, 2, 3, 4, 5, 6, 7, 8
+        },
+        // RELU6 cuts output values at +6
+        {
+            std::min(relu6Min, static_cast<uint8_t>((1*2 + 2*1 + 3*1 + 4*0 + 5*0 + 6*1 + 7*1 + 8*1)/2)),
+            std::min(relu6Min, static_cast<uint8_t>((2*2 + 0*1 + 0*1 + 0*0 + 0*0 + 0*1 + 8*1 + 0*1)/2)),
+            std::min(relu6Min, static_cast<uint8_t>((3*2 + 0*1 + 0*1 + 0*0 + 0*0 + 8*1 + 0*1 + 0*1)/2)),
+            std::min(relu6Min, static_cast<uint8_t>((4*2 + 0*1 + 0*1 + 0*0 + 8*0 + 0*1 + 0*1 + 0*1)/2)),
+            std::min(relu6Min, static_cast<uint8_t>((5*2 + 0*1 + 0*1 + 8*0 + 0*0 + 0*1 + 0*1 + 0*1)/2)),
+            std::min(relu6Min, static_cast<uint8_t>((6*2 + 0*1 + 8*1 + 0*0 + 0*0 + 0*1 + 0*1 + 0*1)/2)),
+            std::min(relu6Min, static_cast<uint8_t>((7*2 + 8*1 + 0*1 + 0*0 + 0*0 + 0*1 + 0*1 + 0*1)/2)),
+            std::min(relu6Min, static_cast<uint8_t>((8*2 + 0*1 + 0*1 + 0*0 + 0*0 + 0*1 + 0*1 + 0*1)/2))
+        });
+}
+
+}