SoK: Zero-Knowledge Proof Systems — An Empirical and Theoretical Comparison of SNARKs and STARKs

Abstract

Zero-knowledge proofs (ZKPs) play a critical role in mitigating modern digital threats by enabling verification without disclosure, a key requirement for secure computation in adversarial environments. Among existing constructions, zk-SNARKs and zk-STARKs represent two dominant paradigms with contrasting security, trust, and performance characteristics. While their theoretical foundations are well studied, practical performance under real-world conditions remains less understood. In this work, we present a systematic, implementation-level comparison of zk-SNARKs (Groth16) and zk-STARKs using publicly available reference implementations on a consumer-grade ARM platform. Our empirical evaluation covers proof generation time, verification latency, proof size, and CPU profiling. Results show that zk-SNARKs generate proofs 68x faster with 123x smaller proof size, but verify slower and require trusted setup, whereas zk-STARKs, despite larger proofs and slower generation, verify faster and remain transparent and post-quantum secure. Profiling further identifies distinct computational bottlenecks across the two systems, underscoring how execution models and implementation details significantly affect real-world performance. These findings provide actionable insights for developers, protocol designers, and researchers in selecting and optimizing proof systems for applications such as privacy-preserving transactions, verifiable computation, and scalable rollups.