Graphs offer a way to naturally represent data from different sources, such as social networks, road networks, the web and many others. Over the last few years, a lot of these networks have grown significantly in size, requiring the development of efficient algorithms that partition the networks into smaller, easier comprehensible blocks. We develop highly efficient algorithms for the problem of finding all minimum cutsand finding all near-minimum cuts. Using several data reduction techniques, we are able to reduce a given input graph by orders of magnitude. We then implement optimized versions of some existing algorithms, which allows us to solve both problems on huge graphs in a few minutes.