We introduce probabilistic extensions of classical deterministic measures of algebraic complexity of a tensor, such as the rank and the border rank. We show that these probabilistic extensions satisfy various natural and algorithmically serendipitous properties, such as submultiplicativity under taking of Kronecker products. Furthermore, the probabilistic extensions enable improvements over their deterministic counterparts for specific tensors of interest, starting from the tensor 2, 2, 2 that represents 2 × 2 matrix multiplication. While it is well known that the (deterministic) tensor rank and border rank satisfy rk 2, 2, 2 = 7 and rk 2, 2, 2 = 7 * The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007(FP/ -2013) / ERC Grant Agreement 338077 "Theory and Practice of Advanced Search and Enumeration". We gratefully acknowledge the use of computational resources provided by the Aalto Science-IT project at Aalto University.