#dusk $DUSK @Dusk
There are a lot of projects in the market that claim ZK compatibility at the drop of a hat. But once you take the time to dig into the execution-layer details, you can see that most of them are just superficial. They treat ZK as an add-on patch rather than a native capability of the underlying system. Many people only compare the time to generate ZK proofs, but they rarely pay attention to the additional gas overhead and call latency incurred when smart contracts invoke ZK logic—these hidden costs in the execution environment directly determine whether privacy-focused financial applications can scale.
Most public chains take an “external” approach for ZK verification. They either rely on precompiled contracts, or push all the heavy proof computation off-chain. This path has a low barrier and goes live quickly, but the drawbacks are very clear: for every ZK verification, the contract must initiate cross-module calls. Each extra interaction adds another round of gas cost. In real tests, the additional gas overhead for a single call often starts at tens of thousands. If the off-chain service gets congested, the latency of sending proof results back on-chain can also directly block on-chain business. Failure points become scattered; the longer the route, the higher the probability of errors. In essence, ZK is merely a “cherry on top” function with a lower priority than the chain’s core logic.
Dusk’s virtual machine architecture takes the exact opposite approach: instead of bolting ZK verification on top, it pushes the entire cryptographic verification capability down into the runtime layer. Mainstream zero-knowledge proof verification logic, hashing algorithms, and aggregated signature components are all encapsulated into native host functions of the system. Smart contracts can call them directly, eliminating the overhead of cross-precompile jumps and off-chain communication round trips. Under the same ZK verification logic, gas consumption at the contract layer can be reduced by nearly 30%, and call latency is brought down to the millisecond level.
At the底层, it does not reuse the EVM memory model. Instead, it redesigns the memory layout based on WASM. The native EVM memory model is optimized for typical smart contracts; when performing ZK computations, frequent reads and writes generate a large number of redundant memory copies. In some complex proof scenarios, memory usage can jump several-fold. WASM’s memory granularity is more flexible and can better fit the characteristics of ZK workloads such as large numbers of loop-based hashes and polynomial operations. Memory usage can drop by as much as 40%, and execution efficiency improves significantly.
More importantly, everything is fully integrated. ZK capability is not an isolated component. The contract interfaces and on-chain privacy transaction primitives are unified. Proof verification, asset transfer, and privacy logic can be closed in a single transaction path, without having to stitch together multiple separate systems.
There are a lot of projects in the market that claim ZK compatibility at the drop of a hat. But once you take the time to dig into the execution-layer details, you can see that most of them are just superficial. They treat ZK as an add-on patch rather than a native capability of the underlying system. Many people only compare the time to generate ZK proofs, but they rarely pay attention to the additional gas overhead and call latency incurred when smart contracts invoke ZK logic—these hidden costs in the execution environment directly determine whether privacy-focused financial applications can scale.
Most public chains take an “external” approach for ZK verification. They either rely on precompiled contracts, or push all the heavy proof computation off-chain. This path has a low barrier and goes live quickly, but the drawbacks are very clear: for every ZK verification, the contract must initiate cross-module calls. Each extra interaction adds another round of gas cost. In real tests, the additional gas overhead for a single call often starts at tens of thousands. If the off-chain service gets congested, the latency of sending proof results back on-chain can also directly block on-chain business. Failure points become scattered; the longer the route, the higher the probability of errors. In essence, ZK is merely a “cherry on top” function with a lower priority than the chain’s core logic.
Dusk’s virtual machine architecture takes the exact opposite approach: instead of bolting ZK verification on top, it pushes the entire cryptographic verification capability down into the runtime layer. Mainstream zero-knowledge proof verification logic, hashing algorithms, and aggregated signature components are all encapsulated into native host functions of the system. Smart contracts can call them directly, eliminating the overhead of cross-precompile jumps and off-chain communication round trips. Under the same ZK verification logic, gas consumption at the contract layer can be reduced by nearly 30%, and call latency is brought down to the millisecond level.
At the底层, it does not reuse the EVM memory model. Instead, it redesigns the memory layout based on WASM. The native EVM memory model is optimized for typical smart contracts; when performing ZK computations, frequent reads and writes generate a large number of redundant memory copies. In some complex proof scenarios, memory usage can jump several-fold. WASM’s memory granularity is more flexible and can better fit the characteristics of ZK workloads such as large numbers of loop-based hashes and polynomial operations. Memory usage can drop by as much as 40%, and execution efficiency improves significantly.
More importantly, everything is fully integrated. ZK capability is not an isolated component. The contract interfaces and on-chain privacy transaction primitives are unified. Proof verification, asset transfer, and privacy logic can be closed in a single transaction path, without having to stitch together multiple separate systems.