General-purpose ZKMs are a commodity. They compete on a single, diminishing axis: proving cost. This is a race to the bottom where winners are determined by hardware access and capital, not protocol design.
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Why General-Purpose ZKMs Are a Venture Capital Trap
The crypto market is pouring billions into general-purpose ZK virtual machines (zkVMs). This is a strategic misallocation. We dissect the crippling performance overhead, the misalignment with market needs, and why specialized ZK coprocessors and application-specific circuits will dominate real adoption.
introduction
THE TRAP
Introduction
General-purpose ZKMs promise universal computation but create a capital-intensive commodity race with no moat.
The market demands specialized circuits. Real adoption requires application-specific ZKMs like zkEVMs (Scroll, Polygon zkEVM) for L2s or zkCPUs (RISC Zero) for verifiable compute. These create defensible products, not just cheaper proofs.
Venture capital misallocates to infrastructure. The $7.6B invested in ZK since 2022 fuels redundant proving networks, while the real value accrues to the applications built on top, like StarkNet's dApps or Aztec's private DeFi.
thesis-statement
THE ARCHITECTURAL TRAP
The Core Argument: The Universal Penalty
General-purpose ZKMs impose a universal performance penalty that makes them commercially unviable for most real-world applications.
General-purpose ZKMs are inefficient by design. They must handle arbitrary logic, forcing them to prove every possible instruction. This creates massive overhead versus specialized provers like zkEVMs or zkVMs optimized for a single domain.
The penalty manifests as cost and latency. A ZK proof for a simple Uniswap swap on a general-purpose system like RISC Zero costs 100x more and takes minutes versus seconds on a StarkNet or zkSync circuit built solely for EVM execution.
Venture capital misallocates towards generality. Funding flows to teams promising a 'ZK CPU' for all apps, ignoring that successful adoption in DeFi or Gaming requires hyper-optimized, application-specific proving stacks that sacrifice generality for performance.
key-trends
WHY VCS ARE BURNING CASH ON A FANTASY
The Three Fatal Flaws of the General-Purpose zkVM
General-purpose zkVMs promise a universal proving layer but are architecturally doomed to fail in production.
01
The Performance Tax of Universality
A single VM must support every possible opcode, creating massive proving overhead. Specialized zkEVMs like zkSync Era and Polygon zkEVM already sacrifice generality for ~5-10x faster proofs than a pure LLVM/CPU-targeting VM.
- Inefficient Circuits: Generic VMs force suboptimal constraint systems.
- Prover Bloat: Supporting unused features adds ~30-50% fixed cost to every proof.
5-10x
Slower Proofs
+30-50%
Fixed Cost
02
The Toolchain Desert
Developers don't write bytecode; they need compilers, debuggers, and oracles. A new general VM lacks the decade of tooling behind EVM or WASM, creating a barren dev experience.
- Missing Middleware: No equivalent to Hardhat, Foundry, or The Graph.
- Oracle Gap: No secure, low-latency price feeds or VRF services.
0
Mature Frameworks
10+ years
Tooling Debt
03
The Liquidity Vacuum
Blockchains are markets, not computers. A new VM cannot bootstrap the $10B+ in composable liquidity and user wallets that exist on EVM L2s like Arbitrum and Optimism.
- Fragmented Capital: No native bridge to major DeFi pools on Ethereum.
- Cold Start Problem: Requires rebuilding entire financial infrastructure from zero.
$0
Bridged Liquidity
100%
Re-build Required
ZK PROVING SYSTEMS
The Performance Tax: General-Purpose vs. Specialized
A first-principles comparison of proving system architectures, quantifying the trade-offs between flexibility and performance.
| Feature / Metric | General-Purpose ZKVM (e.g., RISC Zero, SP1) | Specialized ZK-EVM (e.g., Scroll, Polygon zkEVM) | Specialized App-Specific (e.g., zkSync Era, StarkEx) |
|---|---|---|---|
Proving Time for 1M EVM Gas |
| 2-5 sec (GPU-optimized) | < 1 sec (ASIC/FPGA pipeline) |
Prover Hardware Cost | $10-50 per proof (cloud CPU) | $1-5 per proof (commodity GPU) | < $0.50 per proof (custom hardware) |
Developer Experience | Write in any language (Rust, C++) | Solidity/Vyper, minor changes | Custom DSL/Circuit, high friction |
Proof Recursion / Aggregation | |||
On-chain Verification Cost | ~500k gas | ~200k gas | ~50k gas |
Time to First Proof (new circuit) | Minutes (compile from source) | Weeks (audit & integrate) | Months (design & audit) |
Trusted Setup Required | Perpetual (zk-SNARK) / Transparent (zk-STARK) | Perpetual (zk-SNARK) | Transparent (zk-STARK) or Perpetual |
deep-dive
THE VENTURE CAPITAL TRAP
Architecture vs. Market Fit: Why Builders Are Voting With Their Feet
General-purpose ZKMs are failing to capture developer mindshare because they prioritize theoretical flexibility over solving concrete, high-value problems.
General-purpose ZKMs lack product-market fit. Builders choose tools that solve immediate scaling or privacy bottlenecks, not abstract computation. Projects like zkSync Era and Starknet succeeded by focusing on a single, critical use case: scaling Ethereum L1 execution.
The venture capital trap is over-engineering. Funding fuels a race for maximal theoretical performance (e.g., recursive proof aggregation) before identifying a paying customer. This creates complex, generic VMs that few teams need, unlike the targeted design of Aztec for private smart contracts.
Evidence is in developer migration. The dominant ZK scaling activity is on application-specific chains and L2s using purpose-built stacks (e.g., Polygon CDK, Scroll). These frameworks provide a constrained, opinionated environment that accelerates time-to-market, which general-purpose VMs fail to deliver.
counter-argument
THE MISPLACED BET
Steelman: The Network Effect Defense (And Why It Fails)
The belief that general-purpose ZKMs will win through developer network effects is a flawed investment thesis.
General-purpose ZKMs lack a true network effect. A developer's choice of ZK proving system is a technical decision, not a social one. They choose based on proof speed, circuit language, and hardware compatibility, not because other developers are there.
The moat is in specialized verticals. The defensible network effect exists in application-specific ZK stacks like StarkEx for perps or Aztec for privacy. These create sticky ecosystems where liquidity and users accrue to the platform, not the underlying prover.
The market will commoditize the prover. The value accrues to the application layer and execution environment, not the proving backend. This is analogous to how AWS commoditized server hardware; the value migrated to the services built on top.
Evidence: Look at Polygon zkEVM and Scroll. Both use performant, general-purpose ZKMs but compete directly on execution layer features and Ethereum integration, not on their core proving technology. The prover is an implementation detail.
investment-thesis
WHY GENERAL-PURPOSE ZKMS ARE A VENTURE CAPITAL TRAP
The Alternative Investment Map
The promise of a universal ZK proving system is a siren song. Here's why capital is better deployed on specialized, application-specific infrastructure.
01
The Problem: The Universal Prover Fantasy
General-purpose ZKMs like zkSNARKs and zkSTARKs promise to prove any computation. In practice, they create a massive optimization gap for specific, high-value use cases.
- ~1000x performance delta between generic and custom circuits.
- Forces protocols to accept ~$0.10+ per proof costs that kill unit economics.
- Creates a middleware tax for every application layer.
~1000x
Performance Gap
$0.10+
Base Proof Cost
02
The Solution: Domain-Specific VMs
Invest in ZK Virtual Machines optimized for a single, massive market. zkEVMs (Scroll, Polygon zkEVM) and zkVMs for gaming (like L3s on Starknet) capture entire verticals.
- ~90% cheaper execution for target domain vs. a generic prover.
- Enables sub-cent transaction fees for specific applications.
- Creates unassailable moats in high-TVL sectors like DeFi and gaming.
-90%
Cost vs. Generic
<$0.01
Target TX Fee
03
The Problem: The 'Build It and They Will Come' Fallacy
General-purpose ZK infrastructure lacks a native distribution channel. It's a tool, not a product, relying on other protocols to adopt it. This leads to fierce, low-margin competition among Risc Zero, Succinct, and others.
- Zero direct protocol revenue capture.
- Commoditization risk as faster provers emerge.
- Sales cycles measured in years, not months.
0%
Direct Revenue
24+ mo.
Sales Cycle
04
The Solution: Application-Layer Primitives
Invest in ZK-powered applications that own the end-user. Private DeFi (Aztec), ZK-based identity (Worldcoin), and on-chain gaming are products first.
- Direct fee capture from user activity and TVL.
- Vertical integration controls the full stack from proof to UX.
- Network effects are defensible; proving speed is not.
$1B+
Protocol TVL
Direct
Revenue Model
05
The Problem: The Hardware End-Game Mirage
The thesis that specialized hardware (ASICs, FPGAs) will save general-purpose ZKMs ignores economic reality. Acceleration is a feature, not a business. It invites brutal, capital-intensive races won by the lowest-cost producer.
- $100M+ capex for competitive ASIC development.
- Margin collapse as hardware democratizes.
- Risk of obsolescence with each new proof system.
$100M+
Capex Required
High
Obsolescence Risk
06
The Solution: Algorithmic Moats
Back teams that innovate at the cryptographic layer for a specific use. Nova-style recursion for social graphs or Plonky2 for EVM are algorithmic breakthroughs that create lasting advantage.
- ~100x efficiency gains are locked in by math, not fab plants.
- Creates standards that entire ecosystems build upon.
- IP that scales with software, not hardware depreciation.
100x
Efficiency Gain
IP-Based
Moat Type
takeaways
WHY GENERAL-PURPOSE ZKMS ARE A VENTURE CAPITAL TRAP
TL;DR for Capital Allocators
General-purpose ZKMs promise a universal proving layer but fail to deliver economic viability for most applications, creating a capital-intensive mirage.
01
The Economic Mismatch
General-purpose ZKMs force all applications to pay for a monolithic proving stack, ignoring that 95% of dApps don't need full programmability. This creates a ~1000x cost overhead for simple operations like token transfers or signatures, making them commercially non-viable.
- Inefficient Cost Structure: Proving cost doesn't scale with application logic complexity.
- VC Subsidy Reliance: Sustainable unit economics are impossible without perpetual subsidization.
1000x
Cost Overhead
95%
Apps Overpaying
02
The Specialization Imperative
Real adoption is driven by application-specific ZKMs (AS-ZKMs) like zkEVMs (Scroll, Polygon zkEVM) for L2s or zkCoprocessors (Axiom, Herodotus) for on-chain data. These systems optimize the proof system for a singular task, achieving 10-100x better performance and cost efficiency.
- Vertical Integration: The stack is co-designed with the application logic.
- Proven Market Fit: Dominant ZK use-cases (L2s, privacy) are already specialized.
10-100x
Efficiency Gain
L2s & Coprocs
Winning Verticals
03
The Infrastructure Commoditization
The valuable layer is not the general prover, but the hardware acceleration (Ulvetanna, Ingonyama) and proof aggregation networks (Espresso, Succinct) that serve all ZK systems. These are defensible, high-margin businesses, unlike the application-layer proving service.
- Hardware Moats: ASICs/GPUs for proof generation create tangible barriers to entry.
- Network Effects: Aggregation layers benefit from scale and liquidity across all ZK chains.
ASICs/GPUs
Real Moats
Aggregation
Scalable Biz Model
04
The 'ZK-Everywhere' Fallacy
The narrative that every smart contract needs a ZK proof is architecturally naive. Most state transitions are efficiently verified by re-execution (the Ethereum model). ZK is only optimal for off-chain computation (validiums, coprocessors) or privacy (Aztec, Penumbra), not for replicating existing VM designs.
- Wrong Abstraction: Forces a complex solution (ZK) onto simple problems (consensus).
- Capital Misallocation: Billions flow to general frameworks while specialized tools are underfunded.
Off-Chain & Privacy
Real Use-Cases
Re-execution
Often Cheaper
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