Why Cloud Proving Services Centralize by Default

Generating ZK proofs is a computationally intensive race. Specialized hardware (GPUs, FPGAs, ASICs) provides a 10-100x speedup over commodity hardware. This creates a massive capital barrier to entry, centralizing proving power with entities that can afford the capex.

• Winner-Take-Most Economics: The fastest prover wins the block and the fees.
• Economies of Scale: Large providers amortize hardware costs over thousands of proofs, driving per-proof cost below decentralized competitors.

A prover needs immediate, low-latency access to the full state data of the chain it's proving. Running this at scale requires co-locating provers with high-performance archival nodes, a setup native to centralized cloud providers like AWS and GCP.

• Network Bottleneck: Decentralized provers suffer from ~100ms+ latency fetching state, making them non-competitive.
• Infrastructure Lock-in: The proving stack (hardware, data layer, networking) is optimized for a single cloud region, not a global P2P network.

Services like RiscZero, Succinct, and Espresso Systems create a reinforcing cycle. They attract developers with easy APIs, capture proving fees, reinvest in better hardware/software, and further outpace decentralized alternatives.

• Developer Capture: Teams choose convenience and reliability over ideological decentralization.
• Vertical Integration: PaaS providers control the entire stack from compiler to hardware, creating unbeatable efficiency and creating a new centralization vector for $10B+ TVL rollups.

ZK-proving is computationally intensive, creating a natural monopoly for operators with specialized hardware (e.g., AWS Nitro, Bare Metal). This centralizes trust in a handful of cloud providers and creates a single point of censorship and failure.

• Economic Barrier: $1M+ capital for competitive GPU/FPGA clusters.
• Vendor Lock-in: Proving networks become dependent on AWS, GCP, Azure.

By compiling to a RISC-V instruction set, these frameworks make proofs hardware-agnostic. This breaks the hardware monopoly by allowing proofs to be generated on any machine, from a laptop to a data center, enabling a truly decentralized prover network.

• Vendor Escape: No dependency on specific cloud GPU instances.
• Permissionless Participation: Lowers barrier for independent provers.

Platforms like Succinct and Espresso Systems treat proving as a commodity service within a marketplace. They separate the proof generation layer from the sequencer/validator layer, using proof aggregation and incentive mechanisms to distribute work.

• Market Dynamics: Provers compete on cost and latency.
• Fault Tolerance: Redundant provers prevent single-provider downtime.

Leverages Ethereum's economic security to slash and penalize malicious or lazy centralized provers. By requiring provers to restake ETH or LSTs, the system aligns incentives and creates a cryptoeconomic cost to centralization failures.

• Trust Minimization: Security backed by $15B+ in restaked ETH.
• Enforceable SLAs: Financial penalties for downtime or censorship.

Generating ZK proofs requires specialized, expensive hardware (GPUs, FPGAs). This creates a capital-intensive moat that centralizes the proving market around a few well-funded operators like EigenLayer AVSs or large node providers.

• Barrier to Entry: $500k+ for a competitive proving rig.
• Economies of Scale: Marginal cost per proof plummets for large operators, squeezing out smaller players.

To minimize proof generation time and win users, services must co-locate with high-performance cloud infrastructure (AWS, GCP). This geographically centralizes provers into the same data centers, creating a single point of failure.

• Network Effect: Provers cluster to be closest to sequencers/validators on Ethereum or Solana.
• Vendor Lock-in: Dependence on cloud APIs and proprietary hardware accelerators (e.g., AWS Nitro).

Most proving networks (e.g., RiscZero, Succinct) rely on a centralized coordinator to assign proof jobs and aggregate results. This creates a single liveness and censorship point, negating the decentralization of the underlying prover set.

• Protocol Risk: The entire system's security reduces to the coordinator's honesty.
• MEV Potential: Coordinator can see and order all proving requests, creating a new MEV vector.

Provers are paid per proof, incentivizing them to run the cheapest hardware on the most centralized cloud. Decentralization and censorship-resistance provide no direct economic reward, leading to a tragedy of the commons in security assumptions.

• Profit Motive: Drives consolidation to lowest-cost, centralized providers.
• No Staking Slash: Faulty proofs may only result in lost fees, not slashed capital, reducing security guarantees.

ZK rollups and validiums using cloud provers are only as decentralized as their data availability layer. If the prover is centralized, it can withhold proof publication even if data is on Celestia or EigenDA, effectively halting the chain.

• Gatekeeper Role: Centralized prover controls the finality lever.
• False Security: DA decentralization is irrelevant if the prover is a single entity.

The counter-model requires proof-of-stake for provers, distributed job markets (like Espresso Systems for sequencing), and cryptographic proof aggregation to break the centralization feedback loop.

• Staked Provers: EigenLayer restakers can provide security bonds for proving.
• Peer-to-Peer Networks: Architectures like Nebra aim to create a distributed proving layer without a central coordinator.