diff --git a/delegate/opaque/CMakeLists.txt b/delegate/opaque/CMakeLists.txt
index 897263d..faeabf1 100644
--- a/delegate/opaque/CMakeLists.txt
+++ b/delegate/opaque/CMakeLists.txt
@@ -34,8 +34,10 @@
         src/Shape.hpp
         src/SharedFunctions.cpp
         src/SharedFunctions.hpp
+        src/Slice.hpp
         src/Softmax.hpp
         src/SpaceDepth.hpp
+        src/StridedSlice.hpp
         src/Transpose.hpp
         src/Unpack.hpp)
 
diff --git a/delegate/opaque/src/Shape.hpp b/delegate/opaque/src/Shape.hpp
index ecc545d..4c37c38 100644
--- a/delegate/opaque/src/Shape.hpp
+++ b/delegate/opaque/src/Shape.hpp
@@ -31,8 +31,7 @@
         return kTfLiteError;
     }
 
-    const TfLiteOpaqueTensor* tfLiteInputTensor =
-            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
+    const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
     if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
     {
         return kTfLiteError;
@@ -50,8 +49,7 @@
         return kTfLiteError;
     }
 
-    const TfLiteOpaqueTensor* tfLiteOutputTensor =
-            TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+    const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
     if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
     {
         return kTfLiteError;
diff --git a/delegate/opaque/src/Slice.hpp b/delegate/opaque/src/Slice.hpp
index e169697..2064b2e 100644
--- a/delegate/opaque/src/Slice.hpp
+++ b/delegate/opaque/src/Slice.hpp
@@ -2,3 +2,159 @@
 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus VisitSliceOperator(DelegateData& delegateData,
+                                TfLiteOpaqueContext* tfLiteContext,
+                                TfLiteOpaqueNode* tfLiteNode,
+                                int nodeIndex,
+                                int32_t tfLiteSliceOperatorCode)
+{
+
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 3, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    // Read inputs [input, begin, size]
+    // Gather input indices and use to get input tensor.
+    const int* inputTensors;
+    int numInputs;
+    if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
+                nodeIndex);
+        return kTfLiteError;
+    }
+
+    std::vector<const TfLiteOpaqueTensor*> tfLiteInputTensors;
+    tfLiteInputTensors.reserve(numInputs);
+    for (int i = 0; i < numInputs; i++)
+    {
+        const TfLiteOpaqueTensor* inputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[i]);
+        tfLiteInputTensors.push_back(inputTensor);
+        if (!IsValid(tfLiteContext, inputTensor, tfLiteSliceOperatorCode, nodeIndex))
+        {
+            return kTfLiteError;
+        }
+    }
+
+    const armnn::TensorInfo& inputTensorInfo  = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensors[0]);
+
+    // We save the begin and size tensors in our descriptor. Therefore we have to read those values from inputs
+    unsigned int inputRank = inputTensorInfo.GetNumDimensions();
+    auto ReadInt32Input = [&](int inputIndex, std::vector<uint32_t>& outputData) ->  TfLiteStatus
+    {
+        if (TfLiteOpaqueTensorType(tfLiteInputTensors[inputIndex]) != kTfLiteInt32)
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLiteArmnnOpaqueDelegate: The Begin- and Size-Tensors of the Slice operation need to "
+                    "be of type int32. Operator: #%d node #%d: ",
+                    tfLiteSliceOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+        uint32_t rank = TfLiteOpaqueTensorNumDims(tfLiteInputTensors[inputIndex]);
+        if (rank != 1)
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLiteArmnnOpaqueDelegate: The Begin- and Size-Tensors of the Slice operation need to "
+                    "be a 1D-Tensor. Operator: #%d node #%d: ",
+                    tfLiteSliceOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+        uint32_t numValues = TfLiteOpaqueTensorDim(tfLiteInputTensors[inputIndex], 0);
+        if (numValues != inputRank)
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLiteArmnnOpaqueDelegate: The number of values in the Begin- and Size-Tensors of the "
+                    "Slice operation need to be equal to the rank of the Input-Tensor. Operator: #%d node #%d: ",
+                    tfLiteSliceOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+        // return tensor data
+        auto* tensorDataPtr = static_cast<uint32_t*>(TfLiteOpaqueTensorData(tfLiteInputTensors[inputIndex]));
+        outputData.assign(tensorDataPtr, tensorDataPtr + numValues);
+        return kTfLiteOk;
+    };
+
+    std::vector<uint32_t> begin;
+    if (ReadInt32Input(1, begin) != kTfLiteOk)
+        return kTfLiteError;
+    std::vector<uint32_t> size;
+    if (ReadInt32Input(2, size) != kTfLiteOk)
+        return kTfLiteError;
+
+    // Write all data to the descriptor
+    armnn::SliceDescriptor descriptor(begin, size);
+
+    // Validate output
+    // Gather output indices and use to get output tensor.
+    const int* outputTensors;
+    int numOutputs;
+    if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
+                nodeIndex);
+        return kTfLiteError;
+    }
+
+    const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+    if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteSliceOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+    bool isSupported = false;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("SLICE",
+                                          tfLiteContext,
+                                          IsSliceSupported,
+                                          delegateData.m_Backends,
+                                          isSupported,
+                                          setBackend,
+                                          inputTensorInfo,
+                                          outInfo,
+                                          descriptor);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    // Add a Slice layer
+    armnn::IConnectableLayer* layer = delegateData.m_Network->AddSliceLayer(descriptor);
+    layer->SetBackendId(setBackend);
+    ARMNN_ASSERT(layer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    // Connect
+    return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate
+
diff --git a/delegate/opaque/src/StridedSlice.hpp b/delegate/opaque/src/StridedSlice.hpp
index e169697..9ac3342 100644
--- a/delegate/opaque/src/StridedSlice.hpp
+++ b/delegate/opaque/src/StridedSlice.hpp
@@ -2,3 +2,173 @@
 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus VisitStridedSliceOperator(DelegateData& delegateData,
+                                       TfLiteOpaqueContext* tfLiteContext,
+                                       TfLiteOpaqueNode* tfLiteNode,
+                                       int nodeIndex,
+                                       int32_t tfLiteStridedSliceOperatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 4, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    // Read inputs [input, begin, end, strides]
+    // Gather input indices and use to get input tensor.
+    const int* inputTensors;
+    int numInputs;
+    if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
+                nodeIndex);
+        return kTfLiteError;
+    }
+
+    std::vector<const TfLiteOpaqueTensor*> tfLiteInputTensors;
+    tfLiteInputTensors.reserve(numInputs);
+    for (int i = 0; i < numInputs; i++)
+    {
+        const TfLiteOpaqueTensor* inputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[i]);
+        tfLiteInputTensors.push_back(inputTensor);
+        if (!IsValid(tfLiteContext, inputTensor, tfLiteStridedSliceOperatorCode, nodeIndex))
+        {
+            return kTfLiteError;
+        }
+    }
+
+    const armnn::TensorInfo& inputTensorInfo  = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensors[0]);
+
+    // We save the begin, end and strides tensors in our descriptor. Therefore we have to read those values from inputs
+    unsigned int inputRank = inputTensorInfo.GetNumDimensions();
+    auto ReadInt32Input = [&](int inputIndex, std::vector<int32_t>& outputData) ->  TfLiteStatus
+    {
+        if (TfLiteOpaqueTensorType(tfLiteInputTensors[inputIndex]) != kTfLiteInt32)
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLitearmnnOpaqueDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need"
+                    " to be of type int32. Operator: #%d node #%d: ",
+                    tfLiteStridedSliceOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+        uint32_t rank = TfLiteOpaqueTensorNumDims(tfLiteInputTensors[inputIndex]);
+        if (rank != 1)
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                    tfLiteContext,
+                    "TfLitearmnnOpaqueDelegate: The Begin-, End- and Stride-Tensors of the StridedSlice operation need"
+                    " to be a 1D-Tensor. Operator: #%d node #%d: ",
+                    tfLiteStridedSliceOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+        uint32_t numValues = TfLiteOpaqueTensorDim(tfLiteInputTensors[inputIndex], 0);
+        if (numValues != inputRank)
+        {
+            TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                   tfLiteContext,
+                   "TfLitearmnnOpaqueDelegate: The number of values in the Begin-, End- and Stride-Tensors of the "
+                   "StridedSlice operation need to be equal to the rank of the Input-Tensor. Operator: #%d node #%d: ",
+                   tfLiteStridedSliceOperatorCode, nodeIndex);
+            return kTfLiteError;
+        }
+        // return tensor data
+        auto* tensorDataPtr = static_cast<uint32_t*>(TfLiteOpaqueTensorData(tfLiteInputTensors[inputIndex]));
+        outputData.assign(tensorDataPtr, tensorDataPtr + numValues);
+        return kTfLiteOk;
+    };
+
+    std::vector<int32_t> beginData;
+    if (ReadInt32Input(1, beginData) != kTfLiteOk)
+        return kTfLiteError;
+    std::vector<int32_t> endData;
+    if (ReadInt32Input(2, endData) != kTfLiteOk)
+        return kTfLiteError;
+    std::vector<int32_t> strideData;
+    if (ReadInt32Input(3, strideData) != kTfLiteOk)
+        return kTfLiteError;
+
+    // parse built in options
+    auto* nodeParameters = reinterpret_cast<TfLiteStridedSliceParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+
+    // Write all data to the descriptor
+    armnn::StridedSliceDescriptor descriptor;
+    descriptor.m_Begin          = std::move(beginData);
+    descriptor.m_End            = std::move(endData);
+    descriptor.m_Stride         = std::move(strideData);
+    descriptor.m_BeginMask      = nodeParameters->begin_mask;
+    descriptor.m_EllipsisMask   = nodeParameters->ellipsis_mask;
+    descriptor.m_EndMask        = nodeParameters->end_mask;
+    descriptor.m_NewAxisMask    = nodeParameters->new_axis_mask;
+    descriptor.m_ShrinkAxisMask = nodeParameters->shrink_axis_mask;
+    descriptor.m_DataLayout     = armnn::DataLayout::NHWC;
+
+    // Validate output
+    // Gather output indices and use to get output tensor.
+    const int* outputTensors;
+    int numOutputs;
+    if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
+    {
+        TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+                tfLiteContext,
+                "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
+                nodeIndex);
+        return kTfLiteError;
+    }
+
+    const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+    if (!IsValid(tfLiteContext, tfLiteOutputTensor, tfLiteStridedSliceOperatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor);
+
+    bool isSupported = false;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("STRIDED_SLICE",
+                                          tfLiteContext,
+                                          IsStridedSliceSupported,
+                                          delegateData.m_Backends,
+                                          isSupported,
+                                          setBackend,
+                                          inputTensorInfo,
+                                          outInfo,
+                                          descriptor);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    // Add a StridedSlice layer
+    armnn::IConnectableLayer* layer = delegateData.m_Network->AddStridedSliceLayer(descriptor);
+    layer->SetBackendId(setBackend);
+    ARMNN_ASSERT(layer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = layer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(layer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    // Connect
+    return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate
+
diff --git a/delegate/opaque/src/armnn_delegate.cpp b/delegate/opaque/src/armnn_delegate.cpp
index 936e75a..c96f75d 100644
--- a/delegate/opaque/src/armnn_delegate.cpp
+++ b/delegate/opaque/src/armnn_delegate.cpp
@@ -1034,6 +1034,12 @@
                                                  nodeIndex,
                                                  kTfLiteBuiltinSin,
                                                  armnn::UnaryOperation::Sin);
+        case kTfLiteBuiltinSlice:
+            return VisitSliceOperator(delegateData,
+                                      tfLiteContext,
+                                      tfLiteNode,
+                                      nodeIndex,
+                                      kTfLiteBuiltinSlice);
         case kTfLiteBuiltinSoftmax:
             return VisitSoftmaxOperator(delegateData,
                                         tfLiteContext,
@@ -1065,6 +1071,12 @@
                                                  nodeIndex,
                                                  kTfLiteBuiltinSqrt,
                                                  armnn::UnaryOperation::Sqrt);
+        case kTfLiteBuiltinStridedSlice:
+            return VisitStridedSliceOperator(delegateData,
+                                             tfLiteContext,
+                                             tfLiteNode,
+                                             nodeIndex,
+                                             kTfLiteBuiltinStridedSlice);
         case kTfLiteBuiltinSum:
             return VisitReduceOperator(delegateData,
                                        tfLiteContext,