We have constructed a Beowulf cluster of networked PCs that is dedicated to solving chemistry problems using standard software packages such as Gaussian and GAMESS. We describe the economic and performance trade-offs in the design of the cluster, and present some some selected benchmark results for a parallel version of GAMESS. We believe that the Beowulf we have constructed offers the best price/performance ratio for our chemistry applications, and that commodity clusters can now provide dedicated supercomputer performance within the budget of most university departments.