Ethereum’s Quiet Shift to ZK Proofs Puts New Pressure on Home Validators

Ethereum is quietly testing a fundamental change to how its core protocol validates blocks. Instead of every validator re-executing every transaction, a new pathway is being prototyped where some validators can simply verify zero-knowledge (ZK) proofs of execution. On paper, this could make it dramatically easier for home validators to stay in the game as network throughput increases. In practice, the current reality of GPU-heavy proving raises a new centralization risk that Ethereum’s roadmap must confront.

From re-execution to proof verification

Ethereum researcher ladislaus.eth recently published a technical walkthrough of how Ethereum could move from today’s model—every full node re-executes every transaction—to a future where many validators verify succinct execution proofs instead. The post emphasizes that this is not “adding ZK” as a bolt-on feature, but designing an alternative validation path at layer 1.

The mechanism is being formalized in EIP-8025, “Optional Execution Proofs,” which describes how blocks can be accompanied by proofs and how validators may rely on those proofs instead of locally re-running all transactions. Crucially, the EIP is drafted to be backward compatible and explicitly not a hard fork requirement: nodes can continue to re-execute blocks exactly as they do today.

Under the proposed architecture, the execution layer produces an ExecutionWitness for each block—a self-contained package with all the data needed to validate that block’s state transition without holding the full chain state. A standardized guest program then consumes this witness to check that the transition is valid. A zkVM runs that program, and a prover produces a proof that the execution was correct. The consensus layer client can then verify that proof instead of calling back to the execution client for replay.

The Ethereum Foundation’s zkEVM team has laid out a concrete roadmap for this work through 2026. Six workstreams are in focus: standardizing execution witnesses and guest programs, defining zkVM–guest APIs, integrating proofs into the consensus layer, building prover infrastructure, establishing benchmarks and metrics, and hardening security via formal verification. The first dedicated L1-zkEVM breakout call is scheduled for Feb. 11, signaling that this is now an implementation program, not just a research sketch.

Inside EIP-8025 and the role of ePBS

EIP-8025 introduces two operational modes for validators: proof-generating and stateless validation. Proof-generating actors run the zk pipeline to produce execution proofs and gossip them across the consensus-layer peer-to-peer (P2P) network on a dedicated topic. Stateless validators, by contrast, can validate blocks by verifying these proofs without maintaining full execution state.

This design leans heavily on a key dependency: enshrined Proposer-Builder Separation (ePBS), targeted for the upcoming Glamsterdam hard fork. Today, without ePBS pipelining, the available window to produce a proof for a new block is on the order of 1–2 seconds. That is too tight for current proving systems, which—according to an Ethereum Research post from Feb. 2—take roughly 7 seconds and about 12 GPUs to fully prove a block.

With ePBS, block production is pipelined and the proving window can expand to approximately 6–9 seconds. A chart shared in the research materials highlights how this extended window makes “real-time” or near-real-time proving feasible relative to current performance. In other words, ePBS is not just a MEV and proposer/builder separation reform; it becomes core infrastructure for proof-based validation at layer 1.

Even so, EIP-8025’s authors stress caution. The proposal states that upgrades cannot yet be based on the proof path, and the functionality is explicitly optional. For node operators, this means the re-execution path remains the canonical safety net while the proof path matures through testing, standardization, and monitoring.

Home validators vs a 12-GPU proving reality

On its face, proof-based validation sounds like a win for decentralization: if you can verify a small proof instead of maintaining full state and re-executing every transaction, more home validators could participate with lighter hardware. It also opens up political space to raise gas limits, because validation cost no longer has to scale linearly with execution complexity.

But the proving side tells a different story. According to the Feb. 2 Ethereum Research post, generating a proof for a full Ethereum block currently takes about 7 seconds and requires on the order of 12 GPUs. That is well beyond what most home validators can justify running, both in up-front cost and operational complexity.

This raises a clear centralization risk: if only a small number of well-capitalized actors—block builders, specialized prover networks, or data-center-level operators—can produce proofs, Ethereum risks shifting from a world where “everyone re-executes” toward one where “few prove, many verify.” The security model still works in theory, because a single honest prover is enough to keep the chain live, but the control points concentrate. Outages, censorship, and regulatory pressure on a handful of prover operators become more systemically important.

EIP-8025 tries to preserve a crucial decentralization property: client diversity. The working assumption is a three-of-five threshold—an attester treats a block’s execution as valid once it has verified three proofs produced by five independent execution client implementations. That spreads risk across multiple software stacks, so a bug in any one client is less likely to become a consensus failure.

However, this does not address the underlying hardware question. If all five proving stacks require large GPU clusters, the barrier simply moves up the stack. Today’s constraint for would-be validators is “can you afford to run an execution client and store state?” Tomorrow’s could look more like “can you access GPU capacity or a prover network you trust?” Ethereum’s bet is that verifying proofs can be commoditized more easily than storing and replaying the entire state, but whether proving itself can be made sufficiently accessible is still an open problem.

Stateless validation and the L1 scaling unlock

Ethereum’s most recent roadmap update, dated Feb. 5, lists “Statelessness” as a major theme: enabling nodes to verify blocks without storing large portions of the state. Optional execution proofs and standardized witnesses are the concrete tools that make this idea operational.

In a stateless configuration, a validator would only need a consensus client and the ability to verify proofs during payload processing. Syncing the chain would reduce to downloading proofs for recent blocks since the last finalization checkpoint rather than replaying a long transaction history while reconstructing state. For node operators, this promises lower storage requirements, faster sync times, and a less intimidating hardware profile.

This has direct implications for gas limits. Today, increasing the gas limit raises both bandwidth and computation requirements for full nodes; higher throughput comes at the cost of making it harder for home validators to keep up. If proof verification replaces full re-execution for many validators, verification cost becomes largely independent of how many transactions a block includes, so long as the proof remains succinct and cheap to check.

The 2026 roadmap explicitly calls out benchmarking and repricing work that will map gas usage to proving cycles and proving time. If those curves stabilize and can be reliably modeled, Ethereum gains a new lever: raising throughput without proportionally increasing the cost of running a validating node. For developers and protocol researchers, this becomes the basis for evidence-driven decisions on gas limit changes and potential gas repricing to favor ZK-friendlier execution patterns.

Shared proof infrastructure and shifting L2 value

Layer-2 blockchains also sit directly in the blast radius of this architectural shift. In a recent post, Ethereum co-founder Vitalik Buterin argued that rollups and other L2s will increasingly need to differentiate on more than raw scaling, especially as base-layer fees have already fallen and may fall further if L1 throughput increases.

The logic is straightforward: if all validators eventually verify execution proofs for L1 blocks, those same proofs can be reused via a native EXECUTE-style precompile for “native rollups.” In that world, the proving infrastructure that L1 needs to scale—zkEVM, witness formats, proof verification logic—becomes shared infrastructure that rollups can tap into rather than duplicating from scratch.

If that happens, L2s can no longer lean solely on the argument that “Ethereum can’t handle the load.” The differentiation axes shift toward specialized virtual machines, application-specific execution environments, ultra-low latency and pre-confirmations, custom fee and privacy models, and novel composability structures—such as fast-proving or synchronously composable designs that build on but are not limited to L1’s guarantees.

A plausible long-term allocation of roles emerges: Ethereum layer 1 becomes a high-throughput, low-verification-cost execution and settlement layer, while L2s become specialization labs and interoperability hubs. But this future assumes two things: Ethereum must successfully deliver proof-based verification at scale, and L2 teams must clearly articulate what they provide that a more scalable L1 cannot.

Three scenarios to watch—and what they signal

The roadmap outlined by Ethereum researchers points to three broad paths, each with distinct technical preconditions and decentralization trade-offs.

1. Proof-first validation becomes common. In this optimistic scenario, ExecutionWitness and guest program standards converge, zkVM–guest APIs stabilize, and consensus-layer proof verification becomes a reliable path. Proofs propagate robustly on P2P, and multi-proof thresholds like the proposed three-of-five model are well understood and implemented. Home validators can attest without maintaining full execution state, sync times fall to the span of a few finalized epochs, and gas-limit increases become politically and technically easier because verification cost is largely detached from execution complexity.

2. Prover centralization becomes the choke point. Here, proving remains GPU-intensive, and the market consolidates around a few sophisticated operators—large builders or dedicated prover networks. Validators still verify cheaply, but the decentralization battleground shifts from validator hardware to prover market structure. Liveness increasingly depends on a small number of actors consistently producing proofs. In this case, Ethereum’s theoretical execution scalability is bounded in practice by prover capacity and the economics of high-end hardware.

3. L1 proof verification becomes shared infrastructure. In this outcome, consensus-layer integration “hardens,” ePBS ships in Glamsterdam and provides workable proving windows, and standardized interfaces allow L1 proofs to be reused by native rollups and other higher-layer constructs. The benefit is reduced duplication of proving effort, more predictable verification costs, and a clearer path to higher L1 throughput without pricing out validators. The trade-off is increased cross-domain coupling: if L1’s proving infrastructure is stressed or attacked, rollup verification paths may also suffer.

For developers, node operators, and investors, the practical “what to watch” list includes: the maturity of consensus-spec integrations; the standardization progress of ExecutionWitness and guest programs; benchmark data mapping gas to proving time; the rollout of ePBS in Glamsterdam; and the outcomes of the L1-zkEVM breakout calls as they converge—if they do—on minimum viable proof distribution semantics.

Importantly, Ethereum is not imminently switching to proof-based validation. EIP-8025 underlines that the protocol cannot yet rely on this path for upgrades. Instead, the system is being designed as optional and testable. Yet the presence of a 2026 roadmap, concrete EIP drafts, and scheduled working-group calls shows that this transformation has crossed from theoretical possibility into planned delivery.

The shift is quiet because it doesn’t revolve around tokenomics or obvious user-facing features. It is fundamental because it aims to decouple execution complexity from validation cost. If Ethereum succeeds, layer 1 no longer serves as the hard constraint that pushes “everything interesting” to layer 2. If it also turns proof verification into shared infrastructure, the harder question for the ecosystem becomes: what can higher layers build that a more scalable, proof-verified Ethereum cannot do on its own?