Emerging memristors offer the ability to both store and process data in memory, eliminating the overhead of data transfer between memory and processing unit. For data-intensive applications, developing efficient in-memory computing methods is under investigation. Stochastic computing (SC), a paradigm offering simple execution of complex operations, has been used for reliable and efficient multiplication of data in-memory. The data is converted from binary to bit-stream representation and multiplied by bit-wise ANDing of bit-streams. The current SC-based in-memory methods are incapable of producing accurate results. This work, to the best authors’ knowledge, develops the first accurate SC-based in-memory multiplier. We exploit the recent progress in the idea of SC, deterministic and accurate computation with bit-streams. For logical operations, we use Memristor-Aided Logic (MAGIC), and to generate bit-streams, we propose a method which takes advantage of the intrinsic properties of memristors. The proposed design improves the speed and reduces the memory usage and energy consumption compared to the state-of-the-art accurate in-memory fixed-point and off-memory SC multipliers