A computing scheme that can solve complex tasks is necessary as the big data field proliferates. Probabilistic computing (p-computing) paves the way to efficiently handle problems based on stochastic units called probabilistic bits (p-bits). In this talk, p-computing based on the threshold switching (TS) behavior of a Cu_0.1Te_0.9/HfO₂/Pt (CTHP) memristor is presented. The theoretical background of the p-computing resembling the Hopfield network structure is introduced to explain the p-computing system. The p-bits are realized by the stochastic TS behavior of CTHP diffusive memristors, and they are connected to form the p-computing network. The memristor-based p-bit is likely to be ‘0’ and ‘1’, of which the probability is controlled by an input voltage. The memristor-based p-computing enables all 16 Boolean logic operations in both forward and inverted operations, showing the possibility of expanding its uses for complex operations, such as full adder and factorization.