ZK-Optimized Execution: The Real Scaling Bottleneck

introduction

THE REAL COST

Introduction: The Proving Cost Mirage

The primary bottleneck for ZK-Rollups is not proof generation speed, but the prohibitive cost of proving general-purpose execution.

Proving cost dominates TCO. The industry's focus on proving time is a distraction; the real barrier to scaling is the computational overhead of the prover, which dictates the final fee paid by users. This overhead is intrinsic to proving arbitrary EVM opcodes.

ZK-EVMs are inefficient by design. A general-purpose ZK-EVM like Scroll or Polygon zkEVM must prove every step of a standard EVM execution, creating massive proving costs. This is the fundamental trade-off for full bytecode compatibility.

ZK-optimized VMs are the answer. Architectures like zkSync Era's custom VM or Starknet's Cairo avoid this cost by natively compiling high-level languages to ZK-friendly instructions, bypassing the need to prove the EVM's inefficiencies.

Evidence: A simple ETH transfer on a general-purpose ZK-EVM costs ~10x more in proving compute than on a ZK-optimized VM. This cost differential scales non-linearly with transaction complexity, making DeFi on vanilla ZK-EVMs economically unviable at scale.

thesis-statement

THE COST FUNCTION

Thesis: Execution Efficiency Dictates Proving Economics

The viability of a ZK-rollup is determined by its execution environment's cost to prove, not its theoretical throughput.

Proving cost is the bottleneck. A ZK-rollup's economics are defined by the cost to generate a validity proof, not by its peak TPS. Inefficient execution, like heavy storage writes or complex opcodes, directly increases prover time and hardware cost, making the chain economically unsustainable.

EVM equivalence is a tax. Chains like Scroll and Polygon zkEVM pay a substantial proving overhead for bytecode-level compatibility. Optimized environments like Starknet's Cairo or zkSync's LLVM-based compiler trade general compatibility for radically cheaper proof generation by design.

The metric is gas-per-proof-cycle. The critical benchmark is not L2 gas fees, but the L1 gas cost amortized per proof. A chain with inefficient execution, even with high TPS, will have a higher cost floor, forcing unsustainable subsidies or high user fees.

Evidence: StarkEx applications demonstrate this. dYdX's order book, with its highly optimized, application-specific circuit, achieved sub-cent fees. A general-purpose EVM rollup proving the same volume would incur costs orders of magnitude higher, making the business model impossible.

key-trends

FROM RETROFITS TO FIRST PRINCIPLES

Key Trends: The Shift to ZK-Native Design

ZK-native architectures are moving beyond EVM compatibility to unlock new design spaces and performance frontiers.

The Problem: EVM's Opcode Tax

Retrofitting ZKPs onto the EVM imposes massive overhead. Every SLOAD and SHA3 requires thousands of constraints, bloating proof times and costs.\n- EVM-compatible ZK-Rollups like zkSync and Scroll pay a ~100x constraint penalty for compatibility.\n- This creates a hard ceiling on TPS and keeps transaction fees an order of magnitude above theoretical limits.

~100x

Constraint Penalty

> $0.10

Min TX Cost

The Solution: ZK-CPU & Custom ISAs

Projects like RISC Zero and Succinct Labs are building ZK-optimized instruction set architectures (ISAs). These treat the prover as a first-class hardware target.\n- RISC-V based ZK-VMs reduce constraint counts by 10-100x versus EVM equivalents.\n- Enables native execution of Rust, C++, and Go smart contracts with efficient proving.

10-100x

Efficiency Gain

< 5 sec

Proof Time Goal

The Problem: Monolithic Proof Bottlenecks

Generating a single proof for an entire block execution is slow and limits decentralization. Provers become centralized, high-cost hardware clusters.\n- zkEVM block proofs can take minutes to generate, creating long finality delays.\n- This centralization reintroduces the trust assumptions ZKPs were meant to eliminate.

> 3 min

Proof Gen Time

Major Provers

The Solution: Parallel & Recursive Proof Systems

ZK-native designs like Nova and Proto-danksharding's data blobs enable parallel proof generation and recursive aggregation.\n- Nova's incremental verifiable computation allows proofs to be built step-by-step, enabling parallel proving of transactions.\n- Recursive proofs (proof-of-proofs) from Succinct allow many small proofs to be aggregated into one, distributing prover workload.

Sub-second

Incremental Proofs

1000x

Scalability Boost

The Problem: Opaque State & Interop Friction

In EVM-based ZK rollups, state is hidden inside proofs, making light client verification heavy and cross-chain messaging complex.\n- Bridges like LayerZero and Axelar must trust relayers or committees for state updates from ZK-chains.\n- This creates a verification gap and negates the cryptographic security of ZK proofs for interoperability.

~7 days

Challenge Periods

Trusted

Relayers

The Solution: Proof-Carrying State & Shared Provers

ZK-native chains like Polygon zkEVM's 'validium' mode and Avail's data availability layer enable proof-carrying state. Projects like Electron Labs are building shared ZK-prover networks for cross-chain settlement.\n- Every state transition carries a proof, enabling trust-minimized light clients.\n- A shared prover marketplace (e.g., Risc0's Bonsai) can settle proofs for multiple chains, creating a ZK-security hub.

~3 sec

State Finality

1-to-N

Prover Model

ZK-OPTIMIZED ARCHITECTURES

The Proof Cost Multiplier: Execution vs. Proving

Comparing the cost and performance characteristics of different approaches to integrating zero-knowledge proofs with execution environments.

Metric / Capability	General-Purpose ZKVM (e.g., zkEVM)	ZK-Optimized Execution (e.g., RISC Zero, SP1)	ZK-Coprocessor (e.g., Axiom, Brevis)
Proving Cost per Tx (Est.)	$0.50 - $2.00	$0.05 - $0.20	$0.01 - $0.10
Proving Latency (On-chain)	~10 minutes	< 1 minute	< 10 seconds
Developer Experience	Solidity/Vyper	Rust/C++/Custom DSL	Solidity + On-chain Calls
State Access Model	Full chain state	Deterministic input tape	Trust-minimized historical query
Primary Use Case	L1 → L2 scaling	High-frequency on-chain logic	Off-chain computation & proofs
Hardware Acceleration	GPU (FPGA emerging)	CPU (GPU/FPGA optimized)	CPU (Cloud proving)
Proof Recursion Support
Example Protocols	Scroll, Polygon zkEVM	RISC Zero, SP1, Lasso	Axiom, Brevis, Herodotus

deep-dive

THE EXECUTION

Deep Dive: The Anatomy of a ZK-Optimized VM

ZK-Optimized VMs prioritize prover efficiency over raw execution speed, creating a fundamental architectural divergence from EVM-equivalent chains.

Prover efficiency is the primary constraint. A ZK-Optimized VM, like zkSync's zkEVM or StarkWare's Cairo VM, designs its instruction set and state model to minimize the computational cost of generating a validity proof. This often requires sacrificing the direct compatibility of EVM-equivalent models like Scroll or Polygon zkEVM.

The trade-off is developer friction versus finality speed. A custom VM like Cairo forces developers to use a new language, but its air-based proving system generates proofs orders of magnitude faster. EVM-equivalent chains lower the adoption barrier but inherit the EVM's prover-hostile opcodes, requiring complex circuit compilation and slower proving times.

The benchmark is proof generation time, not TPS. The true scalability metric for a ZK-rollup is how quickly a proof for a block of transactions can be generated and verified on L1. StarkEx demonstrates this with sub-minute proof times for applications like dYdX, enabling high-throughput finality that is impossible with optimistic rollups.

protocol-spotlight

ZK-EXECUTION FRONTIERS

Protocol Spotlight: Execution Layer Strategies

Zero-Knowledge proofs are moving from settlement into execution, forcing a fundamental redesign of the EVM stack.

The Problem: EVM Opcodes Are ZK-Unfriendly

Standard EVM operations like KECCAK, SSTORE, and state lookups are cryptographic nightmares for ZK circuits. Proving them natively creates 100-1000x overhead versus optimized alternatives.

Key Benefit 1: Specialized ZK-EVMs (zkSync Era, Polygon zkEVM) use custom circuits for these ops, but sacrifice full equivalence.
Key Benefit 2: True performance requires abandoning equivalence, as seen with Starknet's Cairo VM and zkRollup architectures that treat the EVM as a compilation target.

1000x

Overhead

~5 ops

ZK-Hostile

The Solution: Parallel Proof Generation

Sequential proof generation is the final boss of blockchain latency. The real innovation is proving execution while it happens, not after.

Key Benefit 1: RISC Zero's continuations and Succinct's SP1 enable breaking programs into parallel provable chunks, turning a 10-hour proof into 10 minutes.
Key Benefit 2: This architecture enables real-time proving for on-chain games and high-frequency DeFi, moving ZK from a settlement bottleneck to an execution primitive.

60x

Faster Proofs

Real-Time

Target

The Trade-Off: Prover Centralization vs. Throughput

High-performance ZK proving is computationally intensive, creating a centralization pressure similar to early PoW mining. The prover network becomes the new critical trust layer.

Key Benefit 1: Projects like Espresso Systems with Tiramisu and Risc0 are building decentralized prover markets to commoditize compute.
Key Benefit 2: Without this, ZK-rollups risk trading validator decentralization for prover oligopolies, undermining the security model for the sake of 10k+ TPS.

10k+

TPS Cost

New Layer

Trust

zkSync's Boojum: The Aggregation Layer

Matter Labs' Boojum upgrade isn't just a new prover; it's a strategic pivot to an aggregation-of-proofs model. It treats individual transaction proofs as a primitive to be recursively combined.

Key Benefit 1: Reduces hardware requirements from ~1TB RAM to ~16GB, enabling consumer-grade proving and decentralizing the prover set.
Key Benefit 2: Creates a clear path to proof aggregation marketplaces, where specialized provers compete on cost and latency for different proof types.

~16GB

RAM Needed

Aggregation

Model

The Endgame: ZK as a Universal Coprocessor

The final evolution is not a ZK-EVM, but a ZK-Coprocessor. Execution happens off-chain, with a succinct proof posted on-chain for verification—this is the EigenLayer AVS and Risc0 Bonsai model.

Key Benefit 1: Unlocks intractably complex computations (AI inference, physics simulations) for on-chain apps, impossible in gas-constrained EVM.
Key Benefit 2: Separates the cost of execution from the cost of verification, enabling a new design space for on-chain gaming and DeFi derivatives.

Unlimited

Compute Scale

~$0.01

Verify Cost

Starknet's App-Chain Play: The Madara Sequencer

StarkWare's Madara is a modular sequencer built on Substrate, allowing any app-chain to use Cairo VM and STARK proofs. This bypasses EVM limitations entirely.

Key Benefit 1: Developers get a highly optimized ZK-native execution environment (Cairo) without fighting the EVM's architecture.
Key Benefit 2: Creates a sovereign execution layer that can settle to any L1 (Ethereum, Celestia, Bitcoin), making the settlement layer a commodity.

ZK-Native

Sovereign

Execution

counter-argument

THE PERFORMANCE REALITY

Counter-Argument: The EVM Compatibility Trap

EVM compatibility is a market entry strategy, not a performance ceiling, and ZK-optimized execution layers prove it.

EVM compatibility is a tax. It forces new chains to inherit the EVM's sequential processing model, which is the primary bottleneck for scaling. This legacy architecture prevents the parallel execution and custom state models that ZK-Rollups need for maximal throughput.

ZK-optimized VMs are inevitable. Projects like Starknet with Cairo and zkSync with its LLVM-based ZK Stack demonstrate that abandoning EVM bytecode unlocks order-of-magnitude gains. They compile high-level code directly to ZK circuits, bypassing the inefficient EVM interpreter loop entirely.

The market is voting with its feet. Developers building complex, high-frequency DeFi or gaming applications are choosing ZK-native environments for deterministic finality and lower costs. The trade-off is temporary tooling friction for permanent architectural superiority.

Evidence: Starknet's transaction throughput under load is constrained by its sequencer, not its prover, demonstrating that execution, not proof generation, is the new bottleneck. This flips the scaling narrative and makes an optimized VM the critical path.

risk-analysis

ZK-EXECUTION PITFALLS

Risk Analysis: What Could Go Wrong?

Separating the architectural promise of ZK-optimized execution from the operational and economic realities on the ground.

The Prover Monopoly Risk

Centralized proving services like zkSync's Boojum or Polygon zkEVM's Plonky2 create a single point of failure and censorship. The economic model for decentralized proving (e.g., RiscZero, Succinct) is unproven at scale.

Centralized Sequencing: Prover controls transaction ordering, a core MEV vector.
Cost Concentration: A single entity bears the ~$0.01 - $0.10 per tx proving cost, creating unsustainable subsidies.
Liveness Dependency: Network halts if the dominant prover fails.

1-2

Dominant Provers

>99%

Uptime Reliance

The Data Availability Time Bomb

ZK-rollups like StarkNet and zkSync Era rely on Layer 1 (e.g., Ethereum) for data availability, which constitutes ~80-95% of their transaction cost. This creates a fundamental cost ceiling.

Blob Fee Volatility: Costs are tied to EIP-4844 blob demand, not ZK efficiency.
No Long-Term Scaling: Throughput is capped by L1 blob space, not proof generation speed.
Validity Proof ≠ Data: A verified proof is useless if the input data is unavailable for reconstruction.

80-95%

Cost is L1 Data

~$0.02

Min Blob Cost/Tx

The Cross-Chain Fragmentation Trap

ZK-optimized execution environments (e.g., Polygon zkEVM, Scroll) are not natively interoperable. Bridging assets via LayerZero or Axelar reintroduces the very trust assumptions and latency ZK promised to solve.

Liquidity Silos: Capital is trapped in high-performance islands.
Bridge Risk Reimported: Users face Wormhole, Nomad-style bridge hacks, negating ZK security.
Complexity Stack: The "ZK-verified state" benefit is lost when exiting via a non-ZK bridge.

7-14 Days

Challenge Periods

$2B+

Bridge Hack Losses

The Specialized Hardware Arms Race

Achieving sub-second proof times for general compute requires FPGA/ASIC provers, creating a mining-like centralization dynamic seen in projects like Miden. This undermines decentralization.

Capital Barrier: $10k+ per prover rig prices out individuals.
Algorithmic Risk: Proof systems (e.g., STARKs, Plonk) can be optimized out by new hardware, rendering existing investments obsolete.
Geopolitical Risk: Proving farm concentration mirrors Bitcoin mining, inviting regulatory scrutiny.

$10k+

Prover Hardware

<1s

Proof Target

The Complexity Attack Surface

ZK-circuits for EVM equivalence (e.g., Scroll's zkEVM) are ~200,000 lines of non-standard cryptography. A single bug in the circuit logic or trusted setup (e.g., Perpetual Powers of Tau) breaks all security guarantees.

Un-auditable Code: Few teams can audit Rust/C++/Circom circuit implementations.
Upgrade Dangers: Protocol upgrades to improve performance (like StarkNet's Cairo 1.0) introduce new, unproven cryptographic assumptions.
Verifier Bugs: A bug in the on-chain verifier contract is a total network failure.

200k+

Lines of Circuit Code

Expert Audit Teams

The Economic Model Mirage

Current $0.01-0.05 transaction fees are subsidized by token emissions and venture capital. Sustainable fees must cover prover hardware, L1 data, and R&D amortization, likely settling 10-50x higher than optimistic rollups like Arbitrum or Optimism.

Token Drain: $100M+ in token incentives to bootstrap prover networks.
No Native Revenue: Proving is a cost center; MEV capture is limited by centralized sequencing.
Investor Exit Pressure: Subsidies end when tokens vest, causing fee spikes and user exodus.

10-50x

Potential Fee Premium

$100M+

Token Incentives

future-outlook

THE ZK REALITY CHECK

Future Outlook: The 2025 Execution Layer War

The 2025 execution layer competition will be defined by the practical integration of zero-knowledge proofs, separating viable architectures from theoretical ones.

ZK-optimized execution is the new moat. Chains like zkSync, Starknet, and Polygon zkEVM that build native ZK-VMs (e.g., zkEVM, Cairo) will outperform EVM-equivalent rollups that retrofit proofs. Native architectures generate proofs 10-100x faster, which is the primary bottleneck for user experience and cost.

The war is about proving, not consensus. The 2025 battle shifts from L1 security to L1 data availability costs and prover economics. Rollups using Celestia or EigenDA for cheap data must still compete on proving latency and cost, where specialized hardware (ASICs, GPUs) creates a centralization risk.

Proof aggregation becomes the critical middleware. Standalone rollups are inefficient. Protocols like EigenLayer and AltLayer will win by aggregating proofs from hundreds of application-specific chains into a single L1 settlement proof, collapsing the cost structure for the entire ecosystem.

Evidence: Starknet's upcoming 'Stwo' prover targets a 10x speed-up using custom hardware, while Arbitrum's BoLD fraud proof system remains untested at scale against sophisticated attacks, highlighting the architectural divergence.

takeaways

ZK-EXECUTION FRONTIER

Key Takeaways for Builders and Investors

Zero-knowledge proofs are moving from a settlement novelty to an execution necessity. Here's what matters.

The Problem: The L2 Bottleneck is the EVM Itself

Ethereum L2s like Arbitrum and Optimism are hitting a wall. Their core architecture—a sequential, single-threaded EVM—cannot be parallelized, capping throughput at ~100-200 TPS. This is the real scaling ceiling, not data availability.

Sequential EVM prevents horizontal scaling.
Proving Overhead for this bloated state is immense.
Result: Diminishing returns on further optimization.

~200 TPS

EVM Ceiling

>10s

Prove Time

The Solution: ZK-Native VMs (Starknet, zkSync)

Architect from first principles for proving, not compatibility. Cairo (Starknet) and Boojum (zkSync Era) are ZK-Instruction Set Architectures (ZK-ISAs) designed for parallel proving.

Parallel Execution: Native support unlocks 10-100x throughput potential.
Efficient Proofs: Instruction sets map directly to proof circuits, reducing overhead.
Trade-off: Requires developers to learn new toolchains, breaking EVM equivalence.

10-100x

Throughput Gain

<1s

Target Prove

The Investment Lens: Follow the Prover Economics

The winning stack will be decided by prover cost and decentralization. RISC Zero, SP1, and Lasso are competing to be the ZK-CPU for general-purpose provable computation.

Hardware Acceleration: ASICs/GPUs for MSM and FFT operations are non-negotiable for scale.
Market Shift: Value accrual moves from sequencers to prover networks.
Key Metric: Cost per million gas proven, trending toward <$0.01.

<$0.01

Target Cost/Gas

ASIC/GPU

Hardware Req

The Builder's Dilemma: EVM Compatibility vs. Performance

You cannot have both optimal ZK-performance and full EVM equivalence. Polygon zkEVM and Scroll choose compatibility, accepting higher proving costs. zkSync Era and Starknet choose performance, accepting a fragmented dev ecosystem.

Strategic Choice: Market reach (EVM) vs. long-term technical ceiling (ZK-VM).
Tooling Gap: ZK-VM debuggers and profilers are 2-3 years behind EVM tools.
Winner: The chain that best bridges this gap.

2-3 yrs

Tooling Lag

50%+

Cost Premium

The Endgame: Autonomous Worlds & On-Chain AI

ZK-optimized execution isn't for swapping tokens. It's the substrate for fully on-chain games (e.g., Dark Forest) and verifiable AI inference. These applications require deterministic, provable state transitions at sub-second intervals, impossible with today's L2s.

Use Case Shift: From DeFi to Continuous World Computers.
Requirement: <100ms proof times for real-time interactivity.
Pioneers: MUD Engine, Argus, Modulus.

<100ms

Proof Latency

AW/On-Chain AI

Killer Apps

The Risk: Centralized Provers & Oracle Problems

ZK-rollups today rely on a single, trusted prover. This recreates the validator centralization problem. The security model shifts from crypto-economic (PoS) to audit-based (is their hardware honest?).

Critical Weakness: A malicious prover can censor or stall the chain indefinitely.
Solution Path: Proof Market designs like Espresso Systems or shared sequencer/prover networks.
Due Diligence: Audit the prover decentralization roadmap, not just the TVL.

Active Prover

Audit-Based

Security Model

Why ZK-Optimized Execution Separates Hype from Reality

Introduction: The Proving Cost Mirage

Thesis: Execution Efficiency Dictates Proving Economics

Key Trends: The Shift to ZK-Native Design

The Problem: EVM's Opcode Tax

The Solution: ZK-CPU & Custom ISAs

The Problem: Monolithic Proof Bottlenecks

The Solution: Parallel & Recursive Proof Systems

The Problem: Opaque State & Interop Friction

The Solution: Proof-Carrying State & Shared Provers

The Proof Cost Multiplier: Execution vs. Proving

Deep Dive: The Anatomy of a ZK-Optimized VM

Protocol Spotlight: Execution Layer Strategies

The Problem: EVM Opcodes Are ZK-Unfriendly

The Solution: Parallel Proof Generation

The Trade-Off: Prover Centralization vs. Throughput

zkSync's Boojum: The Aggregation Layer

The Endgame: ZK as a Universal Coprocessor

Starknet's App-Chain Play: The Madara Sequencer

Counter-Argument: The EVM Compatibility Trap

Risk Analysis: What Could Go Wrong?

The Prover Monopoly Risk

The Data Availability Time Bomb

The Cross-Chain Fragmentation Trap

The Specialized Hardware Arms Race

The Complexity Attack Surface

The Economic Model Mirage

Future Outlook: The 2025 Execution Layer War

Key Takeaways for Builders and Investors

The Problem: The L2 Bottleneck is the EVM Itself

The Solution: ZK-Native VMs (Starknet, zkSync)

The Investment Lens: Follow the Prover Economics

The Builder's Dilemma: EVM Compatibility vs. Performance

The Endgame: Autonomous Worlds & On-Chain AI

The Risk: Centralized Provers & Oracle Problems

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Why ZK-Optimized Execution Separates Hype from Reality

Introduction: The Proving Cost Mirage

Thesis: Execution Efficiency Dictates Proving Economics

Key Trends: The Shift to ZK-Native Design

The Problem: EVM's Opcode Tax

The Solution: ZK-CPU & Custom ISAs

The Problem: Monolithic Proof Bottlenecks

The Solution: Parallel & Recursive Proof Systems

The Problem: Opaque State & Interop Friction

The Solution: Proof-Carrying State & Shared Provers

The Proof Cost Multiplier: Execution vs. Proving

Deep Dive: The Anatomy of a ZK-Optimized VM

Protocol Spotlight: Execution Layer Strategies

The Problem: EVM Opcodes Are ZK-Unfriendly

The Solution: Parallel Proof Generation

The Trade-Off: Prover Centralization vs. Throughput

zkSync's Boojum: The Aggregation Layer

The Endgame: ZK as a Universal Coprocessor

Starknet's App-Chain Play: The Madara Sequencer

Counter-Argument: The EVM Compatibility Trap

Risk Analysis: What Could Go Wrong?

The Prover Monopoly Risk

The Data Availability Time Bomb

The Cross-Chain Fragmentation Trap

The Specialized Hardware Arms Race

The Complexity Attack Surface

The Economic Model Mirage

Future Outlook: The 2025 Execution Layer War

Key Takeaways for Builders and Investors

The Problem: The L2 Bottleneck is the EVM Itself

The Solution: ZK-Native VMs (Starknet, zkSync)

The Investment Lens: Follow the Prover Economics

The Builder's Dilemma: EVM Compatibility vs. Performance

The Endgame: Autonomous Worlds & On-Chain AI

The Risk: Centralized Provers & Oracle Problems

Get In Touch today.

Get In Touch
today.