If you're exploring the potential of verifiable off-chain computation to enhance blockchain scalability, you're likely facing a common challenge: selecting the right zero-knowledge (ZK) toolkit for your project. With multiple zkVM options now available, understanding the essential characteristics of an effective system is crucial.
This guide covers the core features to evaluate, explains why they matter, and provides insights into the current zkVM landscape—helping you make an informed decision for your development needs.
Why Choose a zkVM?
Just two years ago, ZK development primarily involved manually writing circuits using tools like Circom. This process was labor-intensive: circuits were difficult to write, update, audit, and maintain. Bringing a circuit-based ZK project to market often took around two years and cost approximately $100 million.
The introduction of zkVMs has transformed this landscape. By allowing developers to write applications in high-level languages like Rust or C++, zkVMs have made ZK technology accessible to ordinary developers. Complex applications that once took years to develop can now be prototyped in a single weekend.
The key breakthrough came in early 2022 when developers unlocked the ability to prove the correct execution of regular Rust code—including popular Rust crates. Suddenly, ZK builders could focus on building actual applications while leveraging the mature tools available in the Rust ecosystem.
Essential zkVM Features for Development Success
To build anything substantial with a zkVM, you absolutely need four critical characteristics:
- Support for importing libraries and packages
- Support for on-chain proof verification
- Support for unbounded computation without verification cost explosions
- Support for proof composition
These four features are essential for advancing the ZK ecosystem. Let's examine each in detail, including why they matter, why they're challenging to implement, and how different toolkits address them.
Feature 1: Library Support
Why It Matters
Without support for importing libraries, software development becomes unnecessarily difficult. The ability to import established libraries is essential for any complex application, as it prevents developers from having to reinvent basic functionality.
Implementation Challenges
Just a few years ago, ZK systems were inefficient and difficult to build, making support for mature languages like Rust or C++ seem technically impossible. The current trend in zkVM development has shifted from custom instruction sets toward standard instruction sets like RISC-V, MIPS, and WASM.
Current Approaches
In April 2022, the first zkVM capable of proving execution of high-level languages like Rust or C++ was released. Today, some zkVMs test compatibility with the top Rust libraries, with many achieving significant compatibility rates right out of the box. 👉 Explore compatible development tools
Feature 2: On-Chain Verification
Why It Matters
On-chain verification is fundamental to blockchain ZK applications. The basic workflow involves:
- Proving computation off-chain
- Verifying the computation on-chain
Without efficient on-chain verification, ZK proofs cannot be practically utilized in blockchain environments.
Implementation Challenges
Proof system design involves fundamental trade-offs between prover complexity and verifier complexity. The current trend utilizes STARKs for efficient proving combined with elliptic curve-based SNARKs for better on-chain verification costs. Modern zkVMs often incorporate hybrid proof systems to achieve the best of both worlds.
Current Approaches
Some zkVMs use STARKs for efficient proving, then verify the STARK proof within a SNARK circuit to "convert" the STARK to a SNARK. This approach enables support for on-chain verification contracts that can be used for various zkVM applications.
Feature 3: Unbounded Computation with Constant Verification Cost
Why It Matters
If you need to prove the correct construction of Ethereum blocks or OP Stack blocks, you'll need to verify extremely large computations. Without support for unbounded computation size, these use cases become impractical.
Implementation Challenges
Simple approaches to proving large computations don't scale well—doubling the computation size increases complexity by more than double. Achieving unbounded computation size without compromising on-chain verification requires two components, each representing a significant technical achievement:
- The ability to break large computations into chunks that can be proven separately
- The ability to aggregate these "segment proofs" into a single succinct proof
Current Approaches
Some solutions introduce continuations to address the problem of generating proofs for unbounded computations. By proving each segment independently and using recursion to aggregate segment proofs, these systems can achieve linear time proving with constant verification costs.
Feature 4: Proof Composition
Why It Matters
Proof composition (also known as proving proofs) enables numerous use cases, including more complex privacy applications, more modular zkVM applications, and proof aggregation (including proofs from different systems).
Implementation Challenges
Making proof composition efficient is challenging enough that the concept remains unrealized in many systems. Unlocking this feature requires not only solving recursion problems but also building an API that allows developers to call recursive provers from within the zkVM.
Current Approaches
Advanced zkVMs allow users to access proof composition through specific verification functions. This relatively new feature enables developers to verify proofs within the zkVM environment itself, opening up new possibilities for complex applications.
The Technical Challenge of Recursion
These three key features (on-chain verification, unbounded computation, and proof composition) all rely on recursion. In the ZK world, recursion refers to the ability to prove the correct verification of a proof. In simpler terms, you're running the verifier inside the prover.
While this might sound straightforward, building recursive circuits is exceptionally complex. Some zkVMs maintain three related but separate ZK circuits for compatibility. The engineering required to support this functionality is substantial and represents a significant achievement in the field.
How to Compare zkVMs Today
Performance might seem like the most natural comparison standard, but ZK project benchmarking is still in its early stages. While some benchmark projects exist, developing a robust "apples-to-apples" comparison framework remains challenging.
Before comparing performance, ensure you're comparing capabilities directly. When new entrants claim significant speed advantages, carefully examine whether they're achieving those gains by sacrificing other essential characteristics like proof size or verification efficiency.
The most mature zkVMs focus on delivering a feature-complete system ready for production use. Once audits, trust setup ceremonies, and mainnet deployments are complete, users can expect significant performance improvements.
Additional Important Features
Beyond the four essential features, several other characteristics deserve mention:
Deterministic Builds
The ability to natively prove correct execution of a given binary is valuable, but for most use cases, developers will want to prove correct execution of a Rust program (or other high-level language). Some toolkits address this through specialized build tools.
Accelerator Circuit Support
When you identify performance bottlenecks in zkVM applications, the ability to modify the zkVM to provide acceleration for specific use cases becomes valuable. For example, adding a Keccak accelerator could support efficient proof of Ethereum block construction. Some zkVMs currently offer acceleration for large integer operations and SHA hashing.
Proof Aggregation Support
Proof aggregation refers to the ability to combine multiple proofs into a single proof. This feature is essential for affordable on-chain verification. Proof composition enables this functionality, though other systems might offer proof aggregation solutions without fully solving proof composition.
Frequently Asked Questions
What is a zkVM?
A zkVM (zero-knowledge virtual machine) is a virtual machine that can generate cryptographic proofs attesting to the correct execution of programs. These proofs allow third parties to verify computation without re-executing the entire program.
Why is library support important for zkVMs?
Library support enables developers to leverage existing code rather than rewriting basic functionality from scratch. This significantly accelerates development and allows builders to focus on application logic rather than底层infrastructure.
How does on-chain verification work?
On-chain verification involves generating a proof of computation off-chain, then submitting that proof to a smart contract that verifies its validity. The verification process is typically much faster than the original computation.
What makes unbounded computation challenging?
Without special techniques, proving large computations becomes exponentially more difficult as size increases. Solutions like continuations and recursion allow systems to break large computations into manageable pieces while maintaining reasonable verification costs.
Why is proof composition valuable?
Proof composition enables complex applications where proofs can verify other proofs. This capability is essential for privacy applications, modular design patterns, and efficiently aggregating multiple proofs into a single verification.
How do I get started with zkVM development?
Begin by exploring documentation and starter guides for various zkVMs. 👉 Access development resources and tools Most platforms provide examples, tutorials, and community support to help newcomers navigate the learning curve.