Layered stable (multivariate) distributions and processes are defined and studied. A layered stable process combines stable trends of two different indices, one of them possibly Gaussian. More precisely, over short intervals it is close to a stable process, while over long intervals it approximates another stable (possibly Gaussian) process. The absolute continuity of a layered stable process with respect to its short-range limiting stable process is also investigated. A series representation of layered stable processes is derived, giving insights into the structure both of the sample paths and of the short- and long-range behaviours of the process. This series representation is further used for simulation of sample paths.