 Measurement-based quantum computing, MBQC, has been shown to provide a provable advantage over classical computers for certain restricted computational tasks. In particular, it has been demonstrated that non-adaptive MBQC requires contextuality or the ability to measure multiple properties of a single system simultaneously in order to perform certain tasks. This paper further explores the power of MBQC by identifying which Boolean functions can be computed in this model and how many qubits are needed to do so. The authors show that certain functions require fewer qubits than previously thought, while others require more. These findings suggest that MBQC is capable of performing more complex tasks than previously believed, but also highlights the need for further research into the limitations of this model. This article was authored by Marcus Friends, Sam Roberts, Earl T. Campbell, and others.