diff --git a/src/gpu/cl/kernels/ClGemmLowpOffsetContributionKernel.cpp b/src/gpu/cl/kernels/ClGemmLowpOffsetContributionKernel.cpp
new file mode 100644
index 0000000..5d2561d
--- /dev/null
+++ b/src/gpu/cl/kernels/ClGemmLowpOffsetContributionKernel.cpp
@@ -0,0 +1,212 @@
+/*
+ * Copyright (c) 2017-2021 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * 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 "src/gpu/cl/kernels/ClGemmLowpOffsetContributionKernel.h"
+
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+
+#include "src/core/helpers/WindowHelpers.h"
+
+#include "support/Cast.h"
+#include "support/StringSupport.h"
+
+namespace arm_compute
+{
+namespace opencl
+{
+namespace kernels
+{
+namespace
+{
+Status validate_arguments(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, const ITensorInfo *bias,
+                          int32_t a_offset, int32_t b_offset)
+{
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32);
+
+    if(bias != nullptr)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(bias, 1, DataType::S32);
+        ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1);
+        ARM_COMPUTE_RETURN_ERROR_ON(mm_result->dimension(0) != bias->dimension(0));
+    }
+
+    // If a_offset == 0, vector_sum_col can be a nullptr
+    if(a_offset != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32);
+        ARM_COMPUTE_RETURN_ERROR_ON(vector_sum_col->dimension(0) != mm_result->dimension(0));
+    }
+
+    // If b_offset == 0, vector_sum_row can be a nullptr
+    if(b_offset != 0)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32);
+
+        // Check if input is a 3D reinterpretation
+        const bool reinterpret_as_3d = mm_result->num_dimensions() > 1 && mm_result->tensor_shape().y() != vector_sum_row->tensor_shape().x();
+
+        // Validate input
+        ARM_COMPUTE_RETURN_ERROR_ON(reinterpret_as_3d && vector_sum_row->dimension(0) != (mm_result->dimension(1) * mm_result->dimension(2)));
+        ARM_COMPUTE_RETURN_ERROR_ON(!reinterpret_as_3d && vector_sum_row->dimension(0) != mm_result->dimension(1));
+
+        TensorShape output_shape = mm_result->tensor_shape();
+        if(output_shape.num_dimensions() > 1)
+        {
+            const unsigned int output_batch_idx = reinterpret_as_3d ? 3 : 2;
+
+            TensorShape vector_sum_row_shape = vector_sum_row->tensor_shape();
+            vector_sum_row_shape.collapse_from(1);
+            output_shape.collapse_from(output_batch_idx);
+
+            ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[output_batch_idx],
+                                            "mm_result tensor must have the same number of batches of output tensor");
+
+            if(a_offset != 0)
+            {
+                TensorShape vector_sum_col_shape = vector_sum_col->tensor_shape();
+                vector_sum_col_shape.collapse_from(1);
+
+                ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_col_shape[1] != 1 && vector_sum_col_shape[1] != vector_sum_row_shape[1],
+                                                "vector_sum_col tensor must have the same number of batches of vector_sum_row_shape or the number of batches must be set to 1");
+            }
+        }
+    }
+
+    return Status{};
+}
+} // namespace
+
+ClGemmLowpOffsetContributionKernel::ClGemmLowpOffsetContributionKernel()
+{
+    _type = CLKernelType::ELEMENTWISE;
+}
+
+void ClGemmLowpOffsetContributionKernel::configure(const CLCompileContext &compile_context,
+                                                   const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, const ITensorInfo *bias,
+                                                   int32_t k, int32_t a_offset, int32_t b_offset)
+{
+    // Perform validate step
+    ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result);
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result, vector_sum_col, vector_sum_row, bias, a_offset, b_offset));
+
+    auto padding_info = get_padding_info({ mm_result, vector_sum_col, vector_sum_row, bias });
+
+    // Check if input is a 3D reinterpretation
+    const bool reinterpret_as_3d = vector_sum_row != nullptr
+                                   && mm_result->num_dimensions() > 1
+                                   && mm_result->tensor_shape().y() != vector_sum_row->tensor_shape().x();
+
+    const unsigned int num_elems_processed_per_iteration = adjust_vec_size(4, mm_result->dimension(0));
+
+    // Set the arguments to pass at compile time
+    CLBuildOptions build_opts;
+    build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration));
+    build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(mm_result->dimension(0) % num_elems_processed_per_iteration));
+
+    // If a_offset == 0, vector_sum_col can be a nullptr
+    if(a_offset != 0)
+    {
+        build_opts.add_option("-DA_OFFSET=" + support::cpp11::to_string(a_offset));
+        build_opts.add_option_if(vector_sum_col->tensor_shape().num_dimensions() > 1, "-DSUM_COL_HAS_BATCHES");
+    }
+    // If b_offset == 0, vector_sum_row can be a nullptr
+    build_opts.add_option_if(b_offset != 0, "-DB_OFFSET=" + support::cpp11::to_string(b_offset));
+    build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(a_offset * b_offset * k));
+    build_opts.add_option_if(reinterpret_as_3d, "-DHEIGHT_INPUT3D=" + support::cpp11::to_string(mm_result->dimension(1)));
+    build_opts.add_option_if(reinterpret_as_3d, "-DDEPTH_INPUT3D=" + support::cpp11::to_string(mm_result->dimension(2)));
+    build_opts.add_option_if(bias != nullptr, "-DADD_BIAS");
+
+    std::string kernel_name("gemmlowp_offset_contribution");
+
+    // Create kernel
+    _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
+
+    // Configure kernel window
+    Window win = calculate_max_window(*mm_result, Steps(num_elems_processed_per_iteration));
+    IClKernel::configure_internal(win);
+
+    // Set config_id for enabling LWS tuning
+    _config_id = kernel_name + "_";
+    _config_id += support::cpp11::to_string(mm_result->dimension(0));
+    _config_id += "_";
+    _config_id += support::cpp11::to_string(mm_result->dimension(1));
+    _config_id += "_";
+    _config_id += support::cpp11::to_string(mm_result->dimension(2));
+
+    ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
+}
+
+Status ClGemmLowpOffsetContributionKernel::validate(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, const ITensorInfo *bias,
+                                                    int32_t a_offset, int32_t b_offset)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(mm_result, vector_sum_col, vector_sum_row, bias, a_offset, b_offset));
+    return Status{};
+}
+
+void ClGemmLowpOffsetContributionKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
+{
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IClKernel::window(), window);
+
+    const auto vector_sum_col = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_VEC_COL_SUM));
+    const auto vector_sum_row = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_VEC_ROW_SUM));
+    const auto bias           = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_BIAS));
+    const auto mm_result      = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_SRC_DST));
+
+    Window collapsed = window.collapse_if_possible(IClKernel::window(), Window::DimZ);
+    Window slice     = collapsed.first_slice_window_3D();
+
+    // Set window for vector_sum_col
+    Window win_vector_sum_col = slice;
+    win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0));
+    win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
+
+    // Set window for vector_sum_row
+    Window win_vector_sum_row = slice;
+    win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0));
+    win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0));
+    win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0));
+
+    Window biases_slice = slice;
+    biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1));
+    biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1));
+
+    do
+    {
+        unsigned int idx = 0;
+        add_3D_tensor_argument(idx, mm_result, slice);
+        add_2D_tensor_argument_if((vector_sum_col != nullptr), idx, vector_sum_col, win_vector_sum_col);
+        add_2D_tensor_argument_if((vector_sum_row != nullptr), idx, vector_sum_row, win_vector_sum_row);
+        add_1D_tensor_argument_if((bias != nullptr), idx, bias, biases_slice);
+
+        enqueue(queue, *this, slice, lws_hint());
+    }
+    while(collapsed.slide_window_slice_3D(slice));
+}
+} // namespace kernels
+} // namespace opencl
+} // namespace arm_compute