Zero-knowledge virtual machine (zkVM) is a powerful infrastructure for proving the correctness of a program execution with a succinct proof, attracting significant interest from researchers, developers, and users. It has been widely used in applications such as blockchain rollups, privacy-preserving machine learning, and off-chain computation. As the field grows, a wide range of zkVMs have been proposed. However, they adopt different choices in instruction formats, trace layouts, and proving backends, which results in a highly heterogeneous design landscape and makes it difficult to understand the relations among these systems.To bridge this gap, we provide a comprehensive study of zkVMs that covers both their theoretical foundations and practical implementations. We decompose zkVMs into three layers: (1) the ISA layer, which defines instruction semantics and determines the structure of the execution trace, (2) the VM layer, which captures program execution and organizes constraints through modular circuit components, and (3) the proving layer, which converts execution traces into algebraic constraints and generates the final proofs. This decomposition allows us to isolate the role of each layer while also examining how they interact in real systems. To give readers a more direct understanding of how these design choices affect performance, scalability, and usability, we conduct a comprehensive experimental evaluation of representative zkVMs following this layered framework. Finally, we conclude the paper by summarizing the main observations from our analysis and outlining several potential directions for zkVM design and implementation.

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive that enables a prover to convince a verifier that something is true without leaking the private witness. Current zkSNARKs face significant computational costs in generating proofs, which restricts their use in areas like private payments, confidential smart contracts, and anonymous credentials. Private delegation offers a practical solution by outsourcing the heavy computation to powerful external workers without leaking any private information. In this work, we propose HyperSiniel, an efficient private delegation framework for general zkSNARKs that achieves a new feature called guaranteed output delivery (GOD). HyperSiniel is designed to be compatible with any universal zkSNARKs constructed from a polynomial interactive oracle proof (PIOP) and a polynomial commitment scheme (PCS). It enables a computationally limited delegator to outsource proof generation to several workers in a fully non-interactive and privacy-preserving manner. Compared to the most state-of-the-art frameworks (e.g., Siniel [NDSS'25]), HyperSiniel ensures that the delegator always receives a correct proof, regardless of malicious worker behavior. We implement HyperSiniel and compare the performance with Siniel across varying bandwidths and circuit sizes. Under low-bandwidth conditions (10MBps), HyperSiniel incurs only an additional 25% overhead compared with Siniel, while the total running time of HyperSiniel is almost identical to Siniel under high-bandwidth settings (1000MBps). These results show that the strong robustness guarantee of GOD in HyperSiniel comes almost for free, making it a practical and secure solution for real-world zkSNARK delegation.