layer2

Last week, Ethereum researcher ladislaus.eth published a detailed analysis outlining a proposed shift in Ethereum’s validation model: moving from full transaction re-execution toward verification via zero-knowledge (ZK) execution proofs.
He described it as a “quiet but foundational transition.” That characterization appears accurate — not because development is secretive, but because its architectural implications only become clear when viewed holistically.
This is not simply Ethereum “adding ZK” as a feature. Instead, the network is experimenting with an alternative validation pathway in which some validators may verify blocks by checking a succinct execution proof rather than re-running every transaction locally.
If successful, this could gradually redefine the role of Ethereum’s layer-1 from primarily a settlement and data availability layer for rollups into a high-throughput execution layer where verification costs remain low enough for individual validators to participate.
What Is Being Built?
At the center of this effort is EIP-8025: Optional Execution Proofs, currently in draft form. The proposal outlines a technical mechanism enabling validators to choose between traditional re-execution and stateless proof verification.
Execution proofs would be propagated via a dedicated gossip channel within the consensus layer’s peer-to-peer network. Validators could operate in two new modes:
Proof generation mode (acting as provers)
Stateless validation mode (verifying proofs instead of re-executing blocks)
Importantly, the proposal emphasizes backward compatibility. It does not require an immediate hard fork, and nodes may continue operating under the current re-execution model.
On January 26, the Ethereum Foundation’s zkEVM team published a 2026 implementation roadmap, outlining six primary tracks:
Standardization of ExecutionWitness and guest programs
Standardization of the zkVM–guest interface API
Integration with the consensus layer
Prover infrastructure development
Benchmarking and measurement systems
Security analysis and formal verification
A dedicated L1-zkEVM breakout call is scheduled to coordinate development efforts, indicating that the initiative has moved beyond theoretical research into structured implementation planning.
How the End-to-End Pipeline Works
The proposed pipeline operates as follows:
The execution client produces an ExecutionWitness — a self-contained data package containing sufficient information to validate state transitions without storing the full global state.
A standardized guest program uses this witness to verify state transitions.
A zkVM executes the guest program.
A prover generates a cryptographic proof that execution was correct.
The consensus client verifies the proof instead of requiring the execution client to re-run the entire block.
A key dependency is ePBS (Enshrined Proposer-Builder Separation), expected in the upcoming Glamsterdam hard fork.
Without ePBS, proof generation time would be constrained to roughly 1–2 seconds — insufficient for real-time ZK proof creation. With block pipelining enabled by ePBS, this window may extend to approximately 6–9 seconds.
Current research suggests generating a proof for an Ethereum block takes about 7 seconds and requires roughly 12 GPUs on average, underscoring the hardware considerations involved.
Decentralization: A Shift in the Battlefield
If execution proofs and witnesses mature, many individual validators could participate without maintaining the full execution-layer state.
This has significant economic and political implications. Raising the gas limit has historically increased node operation costs, as validators must store more state and process more computation. If validators only verify succinct proofs, verification cost may no longer scale linearly with execution complexity.
However, proof generation introduces new centralization concerns.
Recent research indicates proof creation currently requires substantial GPU resources. The design assumes a 3-of-5 threshold model, where an attester accepts a block once it has verified three independent proofs from different client implementations. This preserves client diversity at the protocol level but does not fully resolve hardware accessibility questions.
In essence, Ethereum may shift its decentralization battleground from:
Today: “Can you afford to run a full execution client?”
Tomorrow: “Can you access a competitive GPU cluster or prover network?”
The underlying bet is that proof verification will be easier to decentralize than full state storage and re-execution — but this remains an open question.
Unlocking Layer-1 Scalability
Ethereum’s February 5 upgrade roadmap identifies statelessness as a core theme: verifying blocks without storing large state datasets.
Optional execution proofs and witnesses represent concrete mechanisms for enabling stateless validation. A stateless node would require only a consensus client and proof verification capability when processing execution payloads.
Synchronization could also become simpler, requiring only recent block proofs since the last checkpoint.
The most consequential implication lies in the gas limit.
Today, increasing gas limits directly increases validator hardware requirements. If validators verify proofs instead of re-executing transactions, verification cost may decouple from execution complexity.
Provided benchmarking demonstrates stable relationships between gas consumption and proof cycles, Ethereum could theoretically increase throughput without proportionally increasing validator operating costs.
Implications for Layer-2
Vitalik Buterin recently suggested that layer-2 solutions must differentiate beyond “just scaling.” He also connected the idea of native rollup precompiles to the zkEVM infrastructure Ethereum needs for its own layer-1.
The logic is straightforward:
If all validators verify execution proofs at layer-1, similar proofs could be reused for rollups via precompiles such as an EXECUTE-style interface. In that scenario, layer-1 proof infrastructure becomes shared infrastructure.
If Ethereum layer-1 achieves higher throughput while maintaining low verification costs, rollups cannot rely solely on the argument that “Ethereum cannot process enough load.”
Instead, new competitive axes for layer-2 may include:
Specialized virtual machines
Ultra-low latency environments
Preconfirmations
Novel composability models
In this model, layer-1 becomes a high-throughput execution and settlement layer with efficient verification, while layer-2 networks function as experimentation layers for feature innovation and latency optimization.
Three Possible Future Scenarios
1. Proof-Based Validation Becomes Common
If witness formats and guest standards stabilize, more individual validators may participate without storing full execution state. Gas limits could increase without proportional increases in verification cost.
2. Provers Become a Centralization Bottleneck
If proof generation remains GPU-intensive and concentrated among a limited number of builder/prover networks, Ethereum could shift centralization risk from validators to prover markets.
3. Layer-1 Proof Verification Becomes Shared Infrastructure
If ePBS deployment proceeds smoothly and proof pipelines function reliably, layer-1 proof systems could serve rollups as well. Layer-2 networks would then compete on latency, specialized execution environments, and new composability designs rather than simply “scaling Ethereum.”
The Bigger Picture
EIP-8025 explicitly notes that Ethereum cannot yet rely on this mechanism for protocol upgrades, underscoring its experimental status.
However, the Ethereum Foundation’s 2026 roadmap, structured working groups, and formal EIP draft suggest a transition from theoretical exploration to coordinated implementation.
This shift is subtle because it does not directly impact tokenomics or introduce immediate user-facing features. Yet it may fundamentally redefine the relationship between execution complexity and verification cost.
If Ethereum successfully decouples these two variables, layer-1 may no longer be the bottleneck that forces innovation upward to layer-2.
And if layer-1 proof verification becomes shared infrastructure, the broader layer-2 ecosystem may face a more difficult question:
What are you building that layer-1 cannot do natively?
This article is for informational purposes only and does not constitute investment advice. Readers should conduct their own research before making financial decisions.
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