fourth scientific and technological revolution, which has been improved enough to readily surpass the human beings in certain specific classes of regions, including image classification and GAMIN (generative adversarial multiple imputation network). [1] It should be pointed out that the realization of AI requires efficient processing and storage of vast amounts of complex information between physically separated memory and processing units. However, the traditional computing hardwares and memories limited by the transfer speed and large power consumption of the data movement are no more physically nor economically feasible due to processing speed saturation and the von Neumann bottleneck. [2] Recently, the high-precision neuromorphic computing system emulating spiking neural networks of the human brain, as an efficient and energy-saving information processor, has been extremely considered a promising candidate to combat the intractable problem. [3] To date, the major ingre dients of neural processors, the memristors, have shown their potential for future electronic applications beyond physical dimension limitations along with their high scalability, simple architecture, rapid writing/reading/ erasing speed, ultralow power consumption, and high-datarate density. [4] Importantly, the memristors with the natural co-location of memory and compute are fully compatibleThe rapid development of artificial intelligence (AI) requires processing vast amounts of complex information, which has accelerated the exploration of neuromorphic computing systems. Artificial neuromorphic synapses based on memristors of organic-inorganic halide perovskites (OHPs) potentially exploit a niche area for brain-inspired neuromorphic computing, which can be operated as biological synapses to realize signal processing. Here, MAPbI 3 -based memristors with reliable resistance states triggered by electric fields or photons are reported. A model for resistive switching (RS) originated from conductive filaments (CFs) based on intrinsic defect migrations is proposed. Importantly, the unique photoresponsive characteristic provides the opportunity to enhance the RS through multifunctional photo-coupling. Enhanced by monochromatic illumination, memristors exhibit RS with remarkable characteristics such as ultralow operating voltage, high ON/OFF ratio (4.3 × 10 3 ), small HRS/LRS variation coefficient (29.91%/13.82%), stable endurance (10 4 cycles), long retention time (10 5 s), and ultralow power consumption. Moreover, photons can modulate the nonvolatile devices to maintain a great ON/OFF ratio over 9 days under ambient conditions without any encapsulation. The research presents plausible applications of memristors in coupling ions, electrons, and photons, thus contributing to applicability for multifunctional optoelectronics and optogenetics tunable neuromorphic systems.