Executive Summary
This report provides a comprehensive comparison of Midnight Network's Compact and Starknet's Cairo, two distinct smart contract languages engineered for the evolving landscape of zero-knowledge proof (ZKP) technology. Compact, leveraging zk-SNARKs, prioritizes privacy and off-chain computational enforcement, strategically positioning Midnight for sensitive financial and enterprise applications. Cairo, built upon zk-STARKs, emphasizes computational efficiency and scalability for verifiable computation, forming the backbone of Starknet's Layer 2 solution. While both languages aim to enhance blockchain capabilities beyond the limitations of traditional transparent execution, their fundamental design philosophies, underlying ZKP mechanisms, and execution models lead to unique trade-offs. The analysis further reveals that migrating existing Solidity smart contracts to either Compact or Cairo is not a simple porting exercise. Instead, it necessitates a profound re-architecture of contract logic, state management, and developer paradigms due to significant differences in virtual machine architectures, language constructs, and the very nature of on-chain versus off-chain verifiable computation.
1. Introduction to Zero-Knowledge Smart Contracts
1.1 The Paradigm Shift: ZKPs for Scalability and Privacy in Web3
Traditional blockchain smart contracts, particularly those operating on the Ethereum Virtual Machine (EVM), are characterized by their public execution and transparent data. This inherent transparency, while fostering trust in permissionless environments, presents considerable limitations concerning scalability and data confidentiality. The computational burden of re-executing every transaction on-chain restricts throughput, and the public nature of data prevents their application in use cases demanding privacy. Zero-Knowledge Proofs (ZKPs) offer a transformative solution by enabling the verification of computational integrity without revealing the underlying sensitive data, thereby addressing both scalability and privacy challenges in Web3.
ZKPs allow smart contracts to verify transactions without exposing sensitive data, making them particularly suitable for financial applications where confidentiality is paramount, and significantly enhancing user trust. This technology is pivotal for blockchain scalability, especially through Layer 2 solutions, and is fundamental to building privacy-preserving applications. The conventional method of verifying a program's execution involves re-executing it, a process that is both inefficient and requires access to all inputs, rendering it unsuitable for scalable or privacy-preserving applications. ZKP systems, such as STARKs, introduce an asymmetric paradigm where a "prover" demonstrates correctness and a "verifier" checks the proof, with verification being computationally negligible compared to the proving process itself.
The integration of ZKPs signifies a profound shift from a "trustless execution" model, where all participants re-execute transactions, to a "provable execution" model, where a single proof suffices for collective verification. This architectural evolution allows for the offloading of complex computations from the main blockchain, thereby alleviating network congestion and reducing transaction costs. Crucially, ZKPs enable a new class of decentralized applications that can handle sensitive information, previously impossible on public blockchains, by achieving both verifiable integrity and data confidentiality—qualities often considered mutually exclusive.
The inherent public-by-default nature of most current smart contract platforms has historically limited their adoption in sectors such as traditional finance, healthcare, and sensitive enterprise applications. By enabling verification without data disclosure , ZKPs directly address this limitation. This capability unlocks new application possibilities such as private asset transfers, confidential voting, and verifiable identity systems. The broader implication of this advancement is that ZKPs expand the total addressable market for Web3 solutions beyond purely transparent, public-good applications. This paves the way for wider enterprise and institutional adoption where data privacy and compliance are non-negotiable requirements.
Furthermore, the integration of ZKPs is subtly redefining the very concept of "on-chain" logic. Traditionally, a smart contract has been understood as code that executes directly on the blockchain. However, ZKP-enabled contracts, particularly Compact, define rules that are enforced
off-chain through proofs , and Cairo also emphasizes offloading complex computations. This indicates a fundamental redefinition of where the actual "computation" occurs within a blockchain system. The blockchain's role is evolving from a direct computational engine to primarily a "proof verification layer" and a "state commitment layer." This architectural shift has significant implications for network design, transaction throughput, and gas cost models, as the heavy computational lifting is moved off-chain while maintaining on-chain integrity guarantees.
1.2 Overview of zk-SNARKs and zk-STARKs
Within the landscape of Zero-Knowledge Proofs, zk-SNARKs and zk-STARKs stand out as the most prominent protocols. While both achieve the core ZKP properties of completeness (if the statement is true, an honest prover can convince the verifier), soundness (if the statement is false, no cheating prover can convince the verifier), and zero-knowledge (the verifier learns nothing beyond the truth of the statement) , they differ significantly in their underlying cryptographic assumptions, performance characteristics, and trust models. Understanding these distinctions is paramount for evaluating their suitability in various smart contract contexts.
zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge):
zk-SNARKs are a form of ZKP that is both succinct, meaning they produce small proof sizes, and non-interactive, implying that no back-and-forth communication is required between the prover and the verifier after the initial proof is generated. A defining characteristic of zk-SNARKs is their requirement for a "trusted setup" phase. During this phase, an initial set of parameters, often referred to as a Common Reference String (CRS) or Structured Reference String (SRS), is generated. A critical security concern arises here: if the secret used in this setup is exposed, the security of all subsequent proofs created with that setup is compromised. Generally, zk-SNARKs exhibit smaller proof sizes and faster verification times compared to zk-STARKs. This often translates to greater gas efficiency on-chain due to reduced data storage and computation for verification. They are widely used in Ethereum for privacy-preserving transactions , with Groth16 being a popular protocol known for its efficiency and compact proof size. However, their post-quantum security is limited due to their reliance on Elliptic Curve Cryptography (ECC), which is theoretically vulnerable to quantum attacks.
zk-STARKs (Zero-Knowledge Scalable Transparent Argument of Knowledge):
In contrast, zk-STARKs are designed to be scalable and "transparent," meaning they do not require a trusted setup phase. Their proofs are generated using public randomness, thereby eliminating the concept of "toxic waste" associated with trusted setups. A significant advantage of zk-STARKs is their strong belief in security against quantum attacks, as their security relies on hash functions rather than elliptic curve cryptography. While generally resulting in larger proof sizes and longer verification times compared to zk-SNARKs, these trade-offs can be mitigated with specific optimizations. zk-STARKs offer high scalability, particularly for very large computations, with performance benefits becoming more pronounced as complexity increases. Their transparency and absence of a trusted setup also provide greater flexibility, as the setup does not need to be redone for each new application or use case.
The selection between zk-SNARKs and zk-STARKs for a blockchain ecosystem is a foundational design choice that reflects the platform's priorities. SNARKs offer immediate efficiency in terms of on-chain footprint and verification speed, but at the cost of a trusted setup and potential long-term quantum vulnerability. STARKs, conversely, prioritize transparency and quantum resistance, providing superior scalability for massive computations, albeit with larger proofs and potentially higher immediate verification costs for smaller tasks. This inherent trade-off significantly influences the economic viability, security posture, and target applications of the underlying blockchain.
The necessity of a trusted setup for zk-SNARKs introduces a critical trust assumption and a potential single point of failure. If the secret parameters generated during this setup, often referred to as "toxic waste," are not securely discarded, the integrity of all subsequent proofs could be compromised. This risk has historically led to the development of complex multi-party computation (MPC) ceremonies designed to distribute and mitigate this trust. In stark contrast, zk-STARKs inherently eliminate this requirement , offering a more "trustless" cryptographic foundation that aligns more closely with the decentralized ethos of public blockchains. This transparency advantage of STARKs could drive their long-term adoption, particularly for public, permissionless networks where trust minimization is a paramount design goal, even if it entails a trade-off in immediate proof efficiency for smaller computations.
Furthermore, a nuanced understanding of scalability versus proof size is essential. While zk-SNARKs are lauded for their smaller proof sizes and faster verification times , zk-STARKs are specifically highlighted as "more scalable for larger computations". This distinction is crucial: for simple, frequent transactions, the smaller proof size of SNARKs might indeed lead to lower on-chain gas costs for verification. However, for highly complex computations or the aggregation of a vast number of transactions, which is common in rollup solutions, STARKs' scalability benefits become more pronounced. This is because their proof size grows quasi-logarithmically with the computation size, whereas SNARKs' proof size is constant but the proving time can be higher for large circuits. This suggests that the "optimal" ZKP choice is highly dependent on the specific application's computational profile and the volume of operations it needs to prove, rather than a universal superiority of one over the other.
2. Compact: The zk-SNARK Powered Language of Midnight Network
2.1 Core Design Principles: Privacy-First, Off-Chain Logic, and Selective Disclosure
Compact is positioned as the foundational smart contract language for Midnight Network, explicitly designed with privacy and regulatory compliance at its core. This is achieved through an innovative architectural model that separates contract logic definition from its direct on-chain execution, leveraging zk-SNARKs for verifiable off-chain enforcement.
Compact is Midnight's dedicated smart contract programming language, purpose-built for creating secure, efficient, and adaptable decentralized applications. Midnight is engineered as a privacy-first platform with compliance in mind, which necessitates its smart contracts to actively protect private data, enable selective disclosure, and maintain security and trust even in adversarial environments. A key architectural divergence from traditional blockchains is that Midnight utilizes smart contracts to define rules that are enforced off-chain through zero-knowledge proofs, rather than executing code directly on-chain. Consequently, Compact contracts define the logic that
needs to be proven, rather than dictating the execution environment itself. These defined rules then serve as the foundation for generating a zero-knowledge proof. In this model, the contract logic remains public, the data used during execution remains private, and only the outcome—for example, "the rules were followed"—is publicly verifiable via a succinct proof. Compact incorporates explicit disclosure mechanisms, allowing developers to precisely define which data elements are revealed, and to whom, providing granular control over on-chain visibility. Practical use cases enabled by this design include voting systems where only the final outcome is public, access control systems that verify user attributes without revealing identities, and token transfers where amounts or senders can be hidden while still allowing public verification of validity. Compact specifically utilizes zk-SNARKs to achieve privacy in smart contracts and blockchain transactions, particularly within permissioned networks, making it a suitable foundation for "Finternet" (financial internet) applications.
Compact's design philosophy is a direct and strategic response to the inherent transparency limitations of public-by-default blockchains, especially for sensitive data. By shifting computation and proof generation off-chain, it fundamentally redefines the role of a smart contract. The contract on-chain acts less as an executor and more as a "rule enforcer" via cryptographically verifiable proofs. This "privacy-first" approach, coupled with fine-grained selective disclosure, strategically positions Midnight and Compact for enterprise-grade and regulated financial use cases where data confidentiality and compliance are paramount.
This approach introduces a "proof-of-logic" paradigm. Unlike conventional smart contracts that execute all logic directly on the blockchain, Compact defines the logic to be proven off-chain. This is a subtle yet critical distinction. It implies that the blockchain does not need to re-execute the entire computation; instead, it only needs to verify a succinct proof that the computation adhered to the contract's predefined rules, even when using private inputs. This paradigm shifts the primary computational burden and potential privacy leakage from the public ledger to private, off-chain environments, while still maintaining on-chain integrity guarantees. This architectural choice is a direct architectural evolution aimed at enabling privacy-preserving applications.
The explicit disclosure feature in Compact, allowing developers to define what data is revealed and to whom , represents a significant advancement in privacy control for smart contracts. In traditional public blockchains, data is often all-or-nothing: either fully public or entirely off-chain and unverifiable. Compact's approach provides a middle ground, enabling a spectrum of privacy levels that can be tailored to specific compliance requirements (e.g., KYC/AML in finance) or user preferences. This fine-grained control over data visibility is crucial for bridging the gap between the transparency demands of blockchain and the confidentiality needs of real-world applications, particularly in regulated industries. This capability expands the utility of smart contracts into domains previously inaccessible due to privacy concerns.
2.2 Language Features and zk-SNARK Integration
Compact is a high-level, statically typed programming language designed for writing smart contracts on the Midnight network. Its syntax is similar to TypeScript, aiming for ease of learning and use.
Compact is strongly statically typed, meaning every expression in a Compact program has a static type, and the compiler rejects programs that do not type check. Named circuits and witnesses require type annotations on their parameters and return types, while anonymous circuit expressions can have optional annotations. The language supports functional programming concepts, such as pure functions and immutable data structures, which facilitate writing composable and modular code that is easier to reason about.
Compact's primitive types are represented in TypeScript, including Boolean, Field, Uint (with runtime bounds checks), Tuples (mapped to TypeScript tuple or array types with runtime length checks), Bytes (Uint8Array with runtime length checks), and Opaque types for strings and Uint8Arrays. Structure declarations have named fields with type annotations, and subtyping rules are defined reflexively, for Uint types (e.g.,
Uint<0..n> is a subtype of Uint<0..m> if n < m), and for tuple types of the same length where corresponding elements are subtypes. Default values are specified for primitive types (e.g.,
false for Boolean, 0 for Uint/Field) and composite types.
Compact's architecture is built around a three-part structure for contracts:
Ledger: The public, on-chain state of the contract.
Circuits: Off-chain logic that can manipulate data, produce proofs, and interact with the ledger. These circuits do not execute logic directly on the blockchain like traditional EVM contract functions.
Witnesses: Privately held data, known only to the entity executing the contract. These are JavaScript functions that have access to the private state, but their results are not seen on-chain unless explicitly revealed.
The Compact compiler translates Compact smart contract code into executable bytecode and proof-generating circuits. This compiler handles details like maximum Field value changes, trailing commas/semicolons, and fixes for arithmetic overflows and common subexpression elimination. The integration of zk-SNARKs allows for secure transactions by verifying transactions without exposing sensitive data, making them ideal for financial applications and increasing user trust.
The functional programming paradigm and static typing in Compact are not merely stylistic choices; they are foundational to building provably correct and secure zero-knowledge circuits. Functional programming, with its emphasis on pure functions and immutable data, naturally lends itself to creating deterministic computations that are easier to translate into algebraic circuits required for ZKPs. Static typing further enhances this by preventing type-related errors at compile time, reducing the attack surface for vulnerabilities that could arise from unexpected data types during off-chain proof generation or on-chain verification. This combination significantly contributes to the reliability and auditability of privacy-preserving smart contracts.
The separation of Ledger, Circuits, and Witnesses in Compact's contract structure is a sophisticated architectural pattern that directly addresses the challenges of privacy and verifiable computation. The
Ledger maintains the publicly verifiable state, while Circuits encapsulate the complex, privacy-preserving logic that operates on private Witness data. This design ensures that the heavy computational and sensitive data handling occurs off-chain, where privacy can be maintained, and only a succinct zk-SNARK proof of the correct execution of the Circuits is submitted to the Ledger for verification. This modularity allows for highly optimized and specialized components, leading to greater efficiency and enhanced privacy guarantees than a monolithic on-chain execution model. This architectural separation is a core enabler for Midnight's privacy-first approach.
3. Cairo: The zk-STARK Powered Language of Starknet
3.1 Core Design Principles: Efficiency for Proving, Algebraic RISC, and Unique Memory Model
Cairo is the native smart contract language for Starknet, a Layer 2 scaling solution for Ethereum. Its design principles are deeply intertwined with the underlying zk-STARK proof system, prioritizing efficiency in proof generation and verification.
Cairo's core design principles include:
Efficiency for Proving: The instruction set is specifically chosen to make the corresponding Algebraic Intermediate Representation (AIR) as efficient as possible, minimizing the number of trace cells (variables in polynomial equations) used. For instance, Cairo's AIR requires only 51 variables per cycle, significantly fewer than other constructions.
Practicality: Cairo supports essential programming constructs like conditional branches, memory, function calls, and recursion, making it practical for real-world applications.
Production-Grade: Cairo serves as the foundation for multiple cryptocurrency systems operating on the Ethereum blockchain, with proofs for Cairo programs being frequently generated and verified by on-chain contracts.
Algebraic RISC (Reduced Instruction Set Computer): Cairo employs a small, simple, yet expressive instruction set. Operations are primarily field operations (e.g., addition and multiplication over a fixed prime field), rather than complex 64-bit integer arithmetic. This design choice allows for a highly efficient AIR with only 51 trace cells per step.
Nondeterministic Programming: Cairo allows programmers to leverage nondeterministic programming, where the prover can perform additional work not part of the proven computation, and only the correctness of "guessed" values is asserted within the proof. This significantly improves efficiency for tasks like square root computation.
Unique Memory Model (Nondeterministic Read-Only Random-Access Memory): Unlike conventional read-write memory, Cairo uses a restricted memory model where the prover chooses all memory values, and the memory is immutable during execution. This allows for a very efficient AIR implementation, requiring only 5 trace cells per memory access, and is sufficient for most programming tasks, with full read-write memory being simulatable when necessary.
Builtins: To mitigate overhead, builtins are introduced as predefined, optimized low-level execution units that enforce specific constraints on Cairo memory, such as range checks and cryptographic primitives like hash functions. These reduce performance overhead by allowing direct implementation as a set of equations.
Efficient Public Memory: Cairo's memory implementation allows for efficient verification of public memory addresses and values, with a verification cost of only 4 arithmetic operations per entry (excluding Fiat-Shamir hash). This is beneficial for handling large logs of on-chain data.
Nondeterministic von Neumann Advantages: This architecture, combined with nondeterminism, enables proving programs where only the hash (not the full code) is known to the verifier, and proving multiple different programs in a single proof to reduce amortized verification costs.
Cairo's emphasis on an Algebraic RISC architecture and its unique memory model is a direct consequence of its foundational goal: optimizing for STARK proof generation. By restricting operations to field elements and employing a single-assignment memory model, Cairo simplifies the arithmetization process, making it significantly easier and more efficient to translate programs into polynomial constraints required by STARKs. This design choice, while potentially imposing a different programming paradigm on developers, yields substantial benefits in terms of proving efficiency and scalability for verifiable computation. The architectural decision directly supports the high throughput and low cost aspirations of a Layer 2 solution like Starknet.
The concept of "nondeterministic programming" and the use of "hints" in Cairo represent a powerful abstraction for offloading complex or computationally intensive parts of a program from the provable execution trace. This means that certain computations, which might be difficult or expensive to prove within the STARK framework, can be performed by the prover "off-chain" (or outside the strict provable computation) and then simply asserted as correct within the proof. This significantly enhances the practicality and efficiency of Cairo for real-world applications by allowing developers to balance provability with computational flexibility. It enables the creation of privacy-focused applications by allowing private inputs to influence the program's execution without being explicitly proven on-chain.
3.2 Language Features and zk-STARK Integration
Cairo, particularly its latest version, offers a Rust-like syntax and aims for an ergonomic developer experience, moving beyond its initial iteration, CairoZero.
Syntax Features (Cairo Assembly and High-Level):
While the Cairo whitepaper provides examples of Cairo assembly syntax, the higher-level Cairo language is designed for smart contract development on Starknet. Cairo smart contracts are stateful and can be deployed and interacted with, similar to Solidity contracts, existing within chained blocks.
Key syntax elements and contract structure include:
Data Types: The primitive data type is felt (field element), an integer within a large prime range. Cairo 1.0 introduces native uint256, regular integer division, and overflow protection for relevant types. It supports tuples, structs, and arrays. Pointers are used extensively for memory access, with
[x] for value at address x and &x for memory address.
Memory Access: In assembly, [x] refers to memory value at address x, which can be a register (ap, fp) or a register with offset (e.g., [ap + 5]). Double dereferencing is supported (e.g., [[fp + 4]).
Registers: ap (allocation pointer), fp (frame pointer), pc (program counter) are used for low-level memory access. Instructions like
ap++ or ap += advance the allocation pointer.
Assert Equal: = ensures equality, rejecting execution otherwise.
Jumps: jmp abs
, jmp rel for unconditional jumps; jmp rel if != 0 for conditional jumps.Functions:
Constructors: Named constructor, annotated with #[constructor], execute once on deployment to initialize state, and must take self by reference (ref self: TContractState).
Public Functions: Accessible from outside, usually in impl blocks with #[abi(embed_v0)] or standalone with #[external(v0)]. Must take self as the first argument.
External Functions: self passed by reference (ref self: TContractState) allowing read and write access to storage.
View Functions: self passed as snapshot (self: @TContractState) allowing only read access. While the compiler marks them as view, their read-only property is not enforced on Starknet, meaning transactions targeting them could still change state.
Private Functions (Internal): Callable only from within the contract, not exposed externally. Can be grouped in impl blocks with #[generate_trait] or as free functions.
Contract Storage: Supports Storage Mappings and Storage Vecs for persistent data.
Events: Essential for logging actions and data on the blockchain.
Composability: Cairo champions composition over inheritance, allowing logical units (components) with their own storage, events, and ABIs to be embedded in contracts.
zk-STARK Integration in Detail:
Cairo is designed to generate proofs of computational integrity using the STARK protocol, representing the Cairo machine as an Algebraic Intermediate Representation (AIR).
AIR as Foundation: The STARK proof system is based on AIRs, which are systems of polynomial constraints on a "trace" (witness) table. A STARK proof demonstrates that a trace exists satisfying these constraints.
Cairo AIR: The Cairo machine is implemented as an AIR, where constraints are satisfiable if and only if the Cairo machine outputs "accept," allowing a STARK prover to convince a verifier of acceptance.
Randomized AIR with Preprocessing (RAP): Cairo's AIR is a RAP, allowing an additional interaction step between prover and verifier, where constraints can involve "interaction variables" and trace columns are split before and after interaction.
Quadratic Constraints: Most Cairo AIR constraints are quadratic (degree 2). Higher-degree constraints are reduced to degree 2 by allocating additional trace cells.
Proof Generation Process: Involves writing Cairo code, compiling to Cairo bytecode, running with Cairo Runner to get execution trace, and then using a STARK prover for the Cairo AIR to generate a proof. The STARK proof's correctness implies the original statement's correctness.
The distinction between "External Functions" and "View Functions" in Cairo, particularly the note that "read-only property is not enforced on Starknet" for view functions , carries significant implications for contract security and developer assumptions. In Solidity,
view and pure functions are strictly enforced as non-state-modifying at the EVM level. Cairo's current implementation means that a developer cannot implicitly trust that calling a view function on another contract will not alter state. This necessitates a more cautious and thorough approach to contract interaction and security auditing, requiring developers to explicitly verify the behavior of called functions rather than relying solely on their view annotation. This difference impacts the mental model for security and interaction design.
Cairo's embrace of "composition over inheritance" is a modern software engineering principle that offers distinct advantages over Solidity's inheritance model. While Solidity's inheritance can lead to complex dependency graphs and issues like "diamond problems," Cairo's component-based approach allows for more modular, reusable, and testable code units. Components can have their own storage, events, and ABIs, and can be embedded into any contract that wishes to use them, allowing for dependency injection and flexible behavior modification. This design fosters a more robust and maintainable smart contract ecosystem, potentially reducing common vulnerabilities associated with complex inheritance hierarchies and promoting clearer separation of concerns.
- Comparison of Compact and Cairo Feature/Aspect
Compact (Midnight Network)
Cairo (Starknet)
Underlying ZKP Technology
zk-SNARKs
zk-STARKs
Trusted Setup
Required
Not required (Transparent)
Proof Size
Smaller, more gas-efficient
Generally larger, but scalable for large computations
Verification Time
Faster
Generally longer, but efficient for large computations
Quantum Resistance
Limited (relies on ECC)
Strong (relies on hash functions)
Core Design Philosophy
Privacy-first, off-chain logic, selective disclosure, compliance-focused
Efficiency for proving, algebraic RISC, verifiable computation, scalability
Execution Model
Defines rules for off-chain enforcement via ZKPs; logic is proven, not directly executed on-chain
Programs compiled to CairoVM's CASM; execution trace is proven via STARKs on CairoVM, a STARK-friendly zkVM
Language Paradigm
High-level, statically typed, TypeScript-like syntax, functional programming concepts
High-level, Rust-based syntax, statically typed, algebraic RISC principles, emphasizes composition
Primitive Data Types
Boolean, Field, Uint, Tuple, Vector, Bytes, Opaque, Struct, Enum
felt (field element), supports tuples, structs, arrays; Cairo 1.0 adds uint256
Memory Model
Three-part structure: Ledger (public on-chain), Circuits (off-chain logic), Witnesses (private data)
Nondeterministic Read-Only Random-Access Memory; single-write memory cells; uses ap, fp, pc registers; recursion often used instead of loops
State Management
Ledger for public on-chain state; private data in Witnesses
Stateful contracts; account abstraction model (no EOAs); state variables persist on-chain
Developer Tooling
Compact compiler, Midnight.js, VS Code Extension
Scarb (package manager), Starknet Foundry, Cairo profiler, Starknet Devnet, Starknet Remix plugin, Open Zeppelin Contract Wizard
The choice between Compact and Cairo, and by extension their underlying ZKP technologies, reveals a fundamental divergence in strategic priorities for blockchain development. Compact's reliance on zk-SNARKs and its privacy-first, off-chain execution model positions Midnight Network as a solution for highly sensitive, often regulated, financial (Finternet) applications where data confidentiality is paramount. The smaller proof sizes of SNARKs align with minimizing on-chain footprint for these private transactions. Conversely, Cairo's use of zk-STARKs and its focus on efficiency for proving make Starknet a powerful platform for general-purpose, scalable computation, particularly for Layer 2 rollups where aggregating large numbers of transactions and achieving high throughput are critical. The transparency and quantum resistance of STARKs provide long-term security assurances for a public scaling solution. This illustrates that the "best" ZKP-enabled smart contract language is not universally superior but rather context-dependent, tailored to specific application requirements and network design goals.
The differing memory models—Compact's three-part structure of Ledger, Circuits, and Witnesses versus Cairo's nondeterministic read-only memory —reflect distinct approaches to managing public and private state in a ZKP context. Compact explicitly segregates public and private data, with witnesses holding private information and circuits operating off-chain to generate proofs for ledger updates. This design inherently enforces privacy by keeping sensitive data off the public chain. Cairo, while supporting private inputs and hints , primarily focuses on optimizing the provability of its unique memory model for STARKs, which is immutable during execution. This means that while Cairo can be used for private computation, its core memory model is optimized for efficient proof generation of
any computation, rather than being inherently privacy-preserving at the data layer like Compact. This difference impacts how developers conceptualize and implement privacy features within their contracts.
- Challenges of Migrating Solidity Smart Contracts Migrating smart contracts written in Solidity to a ZKP-native language like Compact or Cairo presents significant challenges that extend far beyond simple syntax translation. It necessitates a fundamental re-architecture due to profound differences in virtual machine architectures, language paradigms, and state management models.
5.1 Virtual Machine and Execution Model Differences
Solidity smart contracts are designed to run on the Ethereum Virtual Machine (EVM), a stack-based machine that processes bytecode composed of opcodes. The EVM operates as a collection of networked nodes that synchronize their state, with Solidity code compiling directly into bytecode that the EVM interprets. This model involves direct on-chain execution of all logic and data.
In contrast:
Cairo: Targets the CairoVM, a completely different virtual machine with a distinct instruction set (CASM) and memory model. The CairoVM is specifically optimized for generating STARK proofs, allowing for complex computations to be offloaded from the main blockchain, enhancing scalability and reducing on-chain congestion. Programs are compiled to an intermediate representation called Sierra before reaching CASM.
Compact: Operates on a fundamentally different premise. Instead of executing logic directly on-chain, Compact contracts define rules that are enforced off-chain through zero-knowledge proofs. The contract logic is public, but the data used during execution is private, and only the outcome is publicly verifiable via a proof. This means there isn't a direct "virtual machine" in the traditional sense that executes the entire Compact program on-chain; rather, it's a proof-generating and verification system.
The shift from the EVM's direct, public execution model to Cairo's STARK-optimized CairoVM or Compact's off-chain proof generation model represents a fundamental paradigm shift for developers. In Solidity, every operation and piece of data stored on the blockchain incurs gas costs, making inefficiency expensive. Developers are accustomed to optimizing for EVM gas costs and understanding its stack-based operations. Moving to Cairo requires understanding a new VM architecture optimized for provability, which prioritizes different computational efficiencies and memory access patterns. For Compact, the mental model shifts even further, from "what executes on-chain?" to "what must be proven off-chain, and what is committed to the ledger?" This requires a complete re-evaluation of how logic is structured and where computation occurs, moving from a direct execution mindset to a verifiable computation mindset.
5.2 Language Paradigm and State Management Differences
Beyond the virtual machine, the linguistic and state management paradigms of Solidity, Compact, and Cairo diverge significantly, posing substantial migration hurdles.
5.2.1 Data Types and Memory Models
Solidity: Employs a rich set of built-in data types including signed and unsigned integers (e.g., uint256), booleans, addresses, fixed-size byte arrays, literals, enums, fixed/dynamic arrays, structs, and mappings. It uses a flat storage model where all state variables reside in a single, continuous block of memory.
Cairo: The primitive data type is felt (field element), an integer within a specific prime range. While Cairo 1.0 introduces uint256 and overflow protection, developers must be mindful of felt's behavior, which differs from standard integer arithmetic (e.g., division is inverse of multiplication, not truncation). Cairo's memory model is read-only and non-deterministic, meaning each memory cell can only be written once, and recursion is often used instead of loops due to this single-write property.
Compact: Is strongly statically typed with primitive types like Boolean, Field, Uint, and various composite types (tuples, vectors, bytes, opaque types, structs, enumerations). Its memory model is conceptualized through the Ledger (public state), Circuits (off-chain logic), and Witnesses (private data), fundamentally separating on-chain and off-chain data concerns.
The fundamental differences in primitive data types and memory models between Solidity, Cairo, and Compact necessitate a complete re-evaluation of data structures and algorithms during migration. Solidity's uint256 and conventional integer arithmetic are familiar to many developers, but Cairo's felt and its unique arithmetic properties require a new mental model for handling numbers, especially concerning overflow behavior. Similarly, Solidity's mutable, flat storage model contrasts sharply with Cairo's single-write, read-only memory , which often mandates the use of recursion over traditional loops. Compact's tripartite data model forces developers to explicitly distinguish between public, private, and computational data, a distinction often implicit or non-existent in Solidity. These deep-seated differences mean that Solidity code cannot be simply "transpiled"; rather, it must be re-architected to fit the new data and memory paradigms, potentially leading to significant refactoring and a steep learning curve for developers.
5.2.2 State Management and Access Control
Solidity: Each contract deployed at an address has its own storage, and access control often relies on msg.sender and explicit permission checks within functions. Functions have explicit visibility (public, private, internal, external).
Cairo: Contracts are stateful, with state variables persisting on the blockchain. Starknet uses an account abstraction model, meaning there are no Externally Owned Accounts (EOAs) in the Solidity sense, only contract addresses. This allows for highly customizable account logic, such as multicalls. Cairo does not have a notion of inheritance but champions composability, allowing "components" with their own storage and events to be embedded. Visibility of functions is managed through attributes like
[constructor], #[external(v0)], #[abi(embed_v0)], and #[generate_trait]. While Cairo has
view functions, their read-only property is not currently enforced on Starknet.
Compact: Defines Ledger as the public, on-chain state. Access control is implicitly managed by the off-chain proof generation, where rules define who can interact with private data (
Witnesses) and how that data affects the public Ledger. Explicit disclosure mechanisms allow fine-grained control over what data is revealed and to whom.
The shift in state management and access control models from Solidity to Cairo or Compact requires a significant conceptual adjustment for developers. Solidity's msg.sender and contract-owned storage are intuitive for object-oriented programming. In Cairo, the absence of EOAs and the reliance on account abstraction fundamentally changes how user interactions and permissions are designed. Instead of a simple
msg.sender check, developers must consider the logic within the calling account contract. Furthermore, Cairo's emphasis on composition over inheritance means that design patterns for code reuse and modularity must be re-thought, moving away from Solidity's familiar inheritance trees. For Compact, the very notion of state management is distributed across on-chain (Ledger) and off-chain (Witnesses, Circuits) components, demanding a new approach to structuring data flow and access permissions, where privacy is built-in rather than an afterthought. These differences necessitate not just code changes but a re-imagining of contract architecture and security models.
5.2.3 Language Paradigms and Control Flow
Solidity: Is an object-oriented, high-level, statically typed language with ECMAScript-like syntax, supporting features like inheritance, libraries, and complex user-defined types. It supports common control flow structures like
for, while, and do-while loops.
Cairo: Has a Rust-like syntax and offers a better developer experience than its predecessor. It is designed to be efficiently provable and integrates with the fastest prover. Cairo 1.0 introduces simplified syntax, including
for loops and boolean expressions, addressing earlier pain points where recursion was often necessary.
Compact: Is a high-level, typed programming language with a syntax similar to TypeScript. It supports functional programming concepts, such as pure functions and immutable data structures.
The differing language paradigms and control flow mechanisms present another layer of complexity for migration. Solidity's object-oriented nature and familiar C-like control flow provide a comfortable environment for many developers. While Cairo 1.0 has introduced
for loops, its historical reliance on recursion due to its memory model and its Rust-inspired syntax still require a shift in programming style and problem-solving. Compact's functional programming emphasis also necessitates a different approach to state changes and side effects, which are central to object-oriented Solidity. This means that direct translation of complex Solidity logic, especially that relying heavily on mutable state and traditional loop constructs, is not feasible. Developers must adapt their algorithmic thinking to leverage the strengths and accommodate the constraints of the target ZKP-native language, which can be a significant learning curve.
- Conclusions The analysis reveals that Midnight Network's Compact and Starknet's Cairo represent distinct, yet equally innovative, approaches to smart contract development within the zero-knowledge proof paradigm. Compact, with its foundation in zk-SNARKs, is meticulously designed for privacy-first applications, emphasizing off-chain logic enforcement and granular selective data disclosure. This strategic focus positions Midnight as a compelling platform for sensitive enterprise and financial use cases where confidentiality and compliance are paramount. Conversely, Cairo, powered by zk-STARKs, prioritizes computational efficiency and scalability for verifiable computation. Its unique Algebraic RISC architecture and memory model are optimized for generating proofs for large-scale computations, making it ideal for Layer 2 scaling solutions like Starknet. The choice between these languages is not about inherent superiority but rather a strategic alignment with specific application requirements, network design priorities, and desired trade-offs between proof efficiency, transparency, and quantum resistance.
The transition from Solidity to either Compact or Cairo is not a straightforward migration but a fundamental re-engineering effort. The core challenges stem from deep-seated differences across virtual machine architectures, language paradigms, and state management models. Solidity's EVM-centric, object-oriented, and public-by-default execution model contrasts sharply with Cairo's STARK-optimized CairoVM and its unique felt data type and single-write memory, or Compact's off-chain proof generation model with its explicit separation of public and private data. Developers must adapt to new ways of handling data types, managing state, structuring control flow, and conceptualizing security and privacy. This necessitates a significant investment in re-skilling and a complete re-architecture of existing contract logic, moving from a direct on-chain execution mindset to one focused on verifiable computation and cryptographic proof generation. The implications extend to development tooling, testing methodologies, and security auditing, demanding a comprehensive shift in the entire smart contract development lifecycle.
Top comments (1)
Really enjoyed reading this! Midnight’s approach to privacy and off chain execution with ZK proofs is super interesting, especially how Compact separates logic from execution. I’ve been looking into similar ideas and came across Oasis Sapphire which also focuses on privacy first smart contracts but uses a confidential EVM where data stays hidden by default. Kind of a different take, but the goal feels similar: letting devs prove things without exposing sensitive data. Cool to see different chains solving for privacy in their own way.