Quantum computing can solve complex problems that are beyond the reach of classical computers. Despite its vast potential, the field of quantum computing is currently hindered by significant challenges, particularly when it comes to scaling up the size of quantum devices. One of the major limitations of current quantum computers is the restricted number of qubits they can effectively utilize. Distributed quantum computing offers a promising solution to this problem by aggregating the computational power of multiple deficient quantum computers. Two techniques for distributed quantum computing that have shown great promise in this domain are gate teleportation and gate cutting. However, both techniques have drawbacks. Gate teleportation requires shared entanglement and gate cutting incurs a sampling overhead. This thesis aims to explore how these techniques can be combined potentially mitigating their drawbacks. In this thesis, we investigate the error that non-maximally entangled (NME) resource states cause in the gate teleportation of controlled gates. We present different mathematical decompositions of the error, which facilitate gate cuts. Using these gate cuts we demonstrate that NME states can reduce the sampling overhead of the cuts. The result is a trade-off between the degree of entanglement of the resource states and the sampling overhead of the cuts.