In situ visualization is increasingly necessary to address I/O limitations on supercomputers. However, in situ visualization can take on multiple forms. In this research we consider two popular forms: in-line and in-transit in situ. With the increasing heterogeneity of supercomputer design, efficient and cost effective use of resources is extremely difficult for in situ visualization routines. This is further compounded by in situ's multiple forms, and the unknown performance of various visualization algorithms performed in situ at large scale. In this work, we present a time and cost analysis of two different classes of common visualization algorithms both in-line and in-transit. We explore a high computation and low communication algorithm, as well as a low computation and medium communication algorithm, and compare their performance at scale with a running simulation. Finally, we show that contrary to community belief, in-transit in situ has the potential to be both faster and more cost efficient than in-line in situ. We term this discovery a Visualization Cost Efficiency Factor (VCEF) which is a measure of how much more performant in-transit in situ is on a smaller subset of nodes than in-line in situ is at the full scale of a simulation.