A cuckoo filter is a space-efficient approximate membership query data structure, widely used in network systems for applications such as network routing, network measurement, and network caching. However, the traditional design of cuckoo filters has not adequately considered the scenario in network systems where some or all queries in the collection are known, and these queries come with associated costs. This limitation results in the suboptimal performance of existing cuckoo filters in such situations. To address this, the variable hashing-fingerprint cuckoo filter (VHCF) has been developed. VHCF introduces variable fingerprint hashing technology, taking into account the known query collection and their associated costs. By searching for the optimal fingerprint hash function for each hash bucket, the overall cost of false positives is significantly reduced. In addition, this study proposes a single-hash technology to reduce the additional computational overhead caused by the variable-hash technology. A theoretical analysis of the operational complexity and false positive rate of VHCF is also provided. Finally, experimental and theoretical results both demonstrate that VHCF achieves a significantly lower false positive rate than existing cuckoo filters and their variants while ensuring comparable query throughput. Specifically, VHCF only needs to allocate 1–2 bits for each hash index unit, which can reduce the false positive rate to 12.5%–50% of the original.