diff --git a/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp b/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp
index 32e69ca..06a0bde 100644
--- a/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp
+++ b/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.cpp
@@ -60,12 +60,11 @@
 Status validate_matmul_kernel_info(const MatMulKernelInfo &matmul_kernel_info)
 {
     const bool adj_lhs = matmul_kernel_info.adj_lhs;
-    const bool adj_rhs = matmul_kernel_info.adj_rhs;
-    const int  m0      = matmul_kernel_info.m0;
-    const int  n0      = matmul_kernel_info.n0;
-    const int  k0      = matmul_kernel_info.k0;
+    const int m0 = matmul_kernel_info.m0;
+    const int n0 = matmul_kernel_info.n0;
+    const int k0 = matmul_kernel_info.k0;
 
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG((adj_lhs || adj_rhs), "adj_lhs and adj_rhs are not supported yet");
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG((adj_lhs), "adj_lhs is not supported yet");
 
     // Validate M0
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(m0 < 1, "Only positive integers are supported for M0");
@@ -84,7 +83,7 @@
 {
     ARM_COMPUTE_UNUSED(matmul_kernel_info);
     const size_t lhs_k = lhs_shape.x();
-    const size_t rhs_k = rhs_shape.y();
+    const size_t rhs_k = matmul_kernel_info.adj_rhs ? rhs_shape.x() : rhs_shape.y();
 
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(lhs_k != rhs_k, "K dimension in Lhs and Rhs matrices must match.");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG_VAR((lhs_k % mmul_k0) != 0, "K dimension must be a multiple of %d", mmul_k0);
@@ -177,9 +176,11 @@
 
     const int m = dst->dimension(1);
     const int n = dst->dimension(0);
-    const int k = lhs->tensor_shape().x();
-    _m          = m;
-    _n          = n;
+    const int k = matmul_kernel_info.adj_lhs ? lhs->tensor_shape().y() : lhs->tensor_shape().x();
+
+    _m = m;
+    _n = n;
+    _k = k;
 
     int m0{};
     int n0{};
@@ -199,15 +200,15 @@
     build_opts.add_option_if(lhs->data_type() == DataType::F16, "-DHALF_PRECISION");
     build_opts.add_option("-DM0=" + support::cpp11::to_string(m0));
     build_opts.add_option("-DN0=" + support::cpp11::to_string(n0));
-    build_opts.add_option("-DK0=" + support::cpp11::to_string(matmul_kernel_info.k0));
     build_opts.add_option("-DM0_LEFTOVER=" + support::cpp11::to_string(m0_leftover));
     build_opts.add_option("-DN0_LEFTOVER=" + support::cpp11::to_string(n0_leftover));
     build_opts.add_option("-DMMUL_M0=" + support::cpp11::to_string(mmul_m0));
     build_opts.add_option("-DMMUL_N0=" + support::cpp11::to_string(mmul_n0));
     build_opts.add_option("-DMMUL_K0=" + support::cpp11::to_string(mmul_k0));
-    build_opts.add_option("-DK=" + support::cpp11::to_string(k));
 
-    std::string kernel_name("mat_mul_native_mmul_nt_nt");
+    std::string kernel_name("mat_mul_native_mmul");
+    kernel_name += matmul_kernel_info.adj_lhs ? "_t" : "_nt";
+    kernel_name += matmul_kernel_info.adj_rhs ? "_t" : "_nt";
 
     // A macro guard to compile ONLY the kernel of interest
     build_opts.add_option("-D" + upper_string(kernel_name));
@@ -250,6 +251,7 @@
     // Pass m and n at runtime as signed ints, to ensure results of any subtractions they could be operand in, would still be signed.
     _kernel.setArg<cl_int>(idx++, _m);
     _kernel.setArg<cl_int>(idx++, _n);
+    _kernel.setArg<cl_int>(idx++, _k);
 
     // LWS_x should be multiple of 16 at least. (32, 2) has been chosen to have more work-items on a single core
     // LWS also enforces the order of execution of the work items which improves cache utilization
diff --git a/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.h b/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.h
index 26fe08c..79f675d 100644
--- a/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.h
+++ b/src/gpu/cl/kernels/ClMatMulNativeMMULKernel.h
@@ -86,6 +86,7 @@
 private:
     int _m{ 1 };
     int _n{ 1 };
+    int _k{ 1 };
 };
 } // namespace kernels
 } // namespace opencl