<p>This paper investigates the design of a fuzzy reduced-order filter for nonlinear systems with switching event-triggered communication and quantization effects. With the increasing complexity of nonlinear systems, filtering techniques ensure accurate state estimation under the limited communication conditions. The upper and lower membership functions of the interval type-2 fuzzy model are utilized to capture the uncertainties and nonlinear dynamics. It is developed for a switching membership function-dependent reduced-order fuzzy filtering approach to achieve accurate estimation and reduce computational complexity. The filter employs a switching event-triggered scheme with a logarithmic quantizer to coordinate the interaction between communication and quantization. The stability of the resulting error system is established through Lyapunov–Krasovskii functional. Finally, the example of a tunnel diode circuit is evaluated by the proposed approach to demonstrate the merits and advantages.</p>