Verkle Trees are a bandwidth solution. They replace Merkle Patricia Tries with vector commitments, collapsing proof sizes from ~3KB to ~150 bytes. This reduces the data a node must fetch to validate a block.
the-ethereum-roadmap-merge-surge-verge
Blog
Verkle Trees and Bandwidth-Driven Node Costs
The Verge's Verkle Trees promise stateless clients and lighter nodes, but they fundamentally change Ethereum's resource economics. This analysis breaks down the shift from storage-heavy to bandwidth-intensive node operations and what it means for infrastructure providers.
introduction
THE BANDWIDTH BOTTLENECK
Introduction
Verkle Trees are a cryptographic upgrade designed to solve Ethereum's state growth problem by dramatically reducing node bandwidth requirements.
This targets the real cost driver. Node operational expense is dominated by bandwidth consumption, not storage or compute. High-throughput L2s like Arbitrum and Optimism already push this limit.
The upgrade is non-negotiable for statelessness. Without Verkle Trees, the stateless client paradigm—where validators need no local state—is impossible. This is the prerequisite for scaling validator participation.
Evidence: Current Ethereum nodes process ~2TB of data monthly. Post-Verkle, this bandwidth load drops by ~90%, making home staking viable in high-throughput environments.
thesis-statement
THE BANDWIDTH BOTTLENECK
The Core Argument
Verkle Trees are a state management upgrade that shifts the primary node cost from storage to bandwidth, fundamentally altering infrastructure economics.
Verkle Trees shift costs from storage to bandwidth. The new data structure compresses state proofs, but this forces nodes to fetch witness data from peers for every transaction, unlike the self-contained Merkle-Patricia Trie.
The primary cost is now bandwidth. Node operators will pay for constant, high-volume data transfer, not just for initial sync. This creates a predictable operational expense that scales with network usage, unlike the one-time storage cost of the current model.
This mirrors L2 data availability economics. The bandwidth-driven cost model for Ethereum execution clients will resemble the calculus for Arbitrum or Optimism sequencers, where posting calldata to Ethereum is the dominant variable cost.
Evidence: An Ethereum full node using Geth currently requires ~1 TB of SSD. A post-Verkle node may need less than 100 GB of state but must sustain a continuous 50+ Mbps download to stay synced, a requirement that excludes residential connections.
key-trends
THE BANDWIDTH TAX
The State of Play: Pre-Verkle Bottlenecks
Ethereum's current Merkle-Patricia Trie architecture forces nodes to download excessive data, creating a hard cap on decentralization and scalability.
01
The 128 KB Witness Wall
State proofs (witnesses) for complex smart contract interactions can bloat to >100 KB. This creates a hard bandwidth bottleneck for light clients and rollups, limiting their practical utility and increasing sync times for new nodes.
>100 KB
Witness Size
~1 MB/s
Sync Penalty
02
The Stateless Client Mirage
Stateless clients are the holy grail for scaling node count, but are impossible with Merkle trees. The exponential growth of witness size with tree depth makes it infeasible to broadcast proofs for even simple transactions across the p2p network.
O(log n)
Merkle Proof Growth
0%
Deployed Stateless
03
Rollup Inefficiency Tax
Layer 2s like Arbitrum and Optimism pay a direct cost for this inefficiency. Every state proof for fraud/validity verification is larger than necessary, increasing their on-chain data costs (calldata) and finality latency, which is passed to end-users.
$10B+
Collective TVL
+30%
Cost Overhead
04
The Solo Staker Squeeze
Running an Ethereum execution client (e.g., Geth, Nethermind) requires ~1 TB SSD and high I/O. The constant disk seeks for state reads during block validation create a performance ceiling, pushing consensus towards centralized, managed infrastructure providers.
~1 TB
SSD Required
<1%
Solo Stakers
deep-dive
THE BOTTLENECK
The Bandwidth Math of Stateless Verification
Verkle trees enable stateless clients by shrinking proofs, but the resulting bandwidth demand becomes the primary cost driver for node operators.
Statelessness trades storage for bandwidth. A stateless Ethereum client discards its multi-terabyte state, fetching compact Verkle proofs for each transaction instead. This shifts the operational burden from capital-intensive SSDs to recurring network costs.
Proof size dictates the cost curve. A 1-2 KB Verkle proof per transaction is a 100x improvement over Merkle trees, but it still creates a linear bandwidth relationship with network activity. High-throughput L2s like Arbitrum or Base will generate a continuous proof stream.
The node is now a data consumer. Unlike full nodes that serve historical data, stateless nodes are perpetual downloaders. Their economics are dictated by cloud provider egress fees (AWS, GCP) and ISP data caps, not hardware depreciation.
Evidence: A node processing 100 TPS with 1.5 KB proofs consumes ~1 TB of bandwidth daily. At AWS's $0.09/GB egress rate, that's a $2,700 monthly bill, making bandwidth the dominant OpEx.
VERKLE TREES VS. MERKLE TREES
Node Cost Model: Storage vs. Bandwidth Regimes
Comparison of node cost drivers and performance trade-offs between traditional Merkle-based state management and Verkle tree implementations, focusing on Ethereum's post-Dencun upgrade trajectory.
| Cost & Performance Driver | Merkle Tree Regime (Historical) | Verkle Tree Regime (Post-Dencun) | Hybrid/Transition State |
|---|---|---|---|
Primary Cost Driver | State Storage Growth (GB/TB) | State Proof Bandwidth (KB/MB) | Both (Storage + Proof Size) |
Node Sync Time (Full Archive) | Weeks (10+ TB state) | Days (< 2 TB state) | Days to Weeks (Variable) |
Witness Size for 1M Gas Block | ~1-2 MB | < 250 KB | ~500 KB - 1 MB |
State Proof Complexity | O(log n) Hashes | O(1) with KZG/Vector Commitments | O(log n) with proto-danksharding |
Hardware Bottleneck | SSD I/O & Capacity | Network Bandwidth & CPU | Network & Storage I/O |
Stateless Client Viability | |||
Incentive for Node Centralization | High (Storage Costs) | Lower (Bandwidth is Commodity) | Moderate |
Required Node Storage (Post-Witness Pruning) | Persistent Full State | Ephemeral State Cache | Pruned State + Cache |
counter-argument
THE BANDWIDTH TRADEOFF
The Steelman: Isn't This Still a Net Win?
Verkle trees significantly reduce proof sizes, but the primary cost shift is to bandwidth, not computation.
The core win is state proof compression. Verkle trees use Vector Commitments to shrink witness sizes from ~1MB to ~150KB, enabling stateless clients. This is the prerequisite for Ethereum's stateless future and light client viability.
The new bottleneck is data availability. Nodes now spend more cycles fetching and verifying these smaller proofs from the network. The cost model shifts from storage I/O to bandwidth and latency, similar to scaling challenges faced by Solana validators.
This is a strategic trade, not a free lunch. The Ethereum Foundation's Portal Network is the direct response to this new constraint, aiming to create a decentralized, incentivized content delivery network for state data.
Evidence: Current Ethereum nodes process ~50 MB/min of block data. Post-Verkle, the same node will handle more, smaller proofs, but network round-trips become the dominant latency factor for state access.
risk-analysis
VERKLE TREES & BANDWIDTH COSTS
The New Risk Matrix
Verkle trees promise state scalability, but shift the fundamental bottleneck from storage to bandwidth, creating a new calculus for node operators.
01
The Problem: Witness Size Bloat
Verkle proofs are tiny, but the witness data required to generate them is massive. Nodes must serve ~1-10 MB of data per block to light clients, turning every full node into a high-bandwidth CDN. This isn't a storage problem; it's a network I/O tax.
- Bandwidth costs become the primary operational expense.
- Risks re-centralization as hobbyist nodes are priced out.
- Creates a new Sybil vector: cheap to run a node, expensive to serve it honestly.
1-10 MB
Data/Block
>1 Gbps
Peak Load
02
The Solution: Bandwidth-Aware P2P
The network layer must evolve from a dumb gossip protocol to a bandwidth-market protocol. Think Filecoin for witnesses. Nodes with excess capacity can earn fees for serving data, while light clients pay for guaranteed latency. This mirrors the economic models of Helium and Arweave but for real-time state data.
- Incentivizes high-bandwidth node distribution.
- Monetizes the resource that actually matters post-Verkle.
- Prevents free-rider problems that plague current altruistic networks.
P2P Market
New Layer
Fee-for-Service
Model
03
The Arbiter: Light Client Centralization
If bandwidth costs are too high, applications will centralize around a few professional RPC providers like Alchemy, Infura, QuickNode. This recreates the very problem Ethereum has spent years solving. The true test of Verkle trees isn't proof size, but whether a light client in a coffee shop can sync the chain without relying on a trusted third party.
- RPC providers become the unavoidable bottleneck.
- Trust assumptions creep back into the system.
- Protocol-level bandwidth economics are non-negotiable for decentralization.
Critical Risk
For Decentralization
RPC Reliance
Centralization Vector
04
The Precedent: Solana's Lessons
Solana's ~1 Gbps network requirements provide a live case study in bandwidth-driven centralization. Its validator set is wealthier and more professionalized than Ethereum's. Verkle-enabled Ethereum risks following the same path unless it designs for resource pricing from day one. The solution isn't to avoid demands, but to build a market for them.
- Solana validators require enterprise-grade bandwidth.
- Ethereum's grassroots node ops are at risk.
- Proactive design must learn from existing high-throughput chains.
1 Gbps+
Solana Baseline
Wealthier Set
Validator Profile
future-outlook
THE BANDWIDTH BOTTLENECK
The Infrastructure Evolution
Verkle trees are a state management upgrade that reduces node bandwidth costs by orders of magnitude, enabling stateless clients and cheaper hardware requirements.
Verkle trees replace Merkle Patricia Tries by using vector commitments, collapsing proof sizes from ~1 KB to ~150 bytes. This fundamental compression slashes the data a node must download to verify a block, directly attacking the primary cost driver for node operators.
Statelessness becomes economically viable because validators no longer need the full state. A client can verify transactions with a tiny witness, similar to how zk-proofs like Starknet's Cairo verify execution without re-running it. This shifts the cost burden from storage to computation.
The bottleneck shifts to bandwidth, not storage. Projects like Celestia and EigenDA already optimize for this reality by separating data availability from execution. Verkle trees push monolithic chains like Ethereum toward a similar architectural separation internally.
Evidence: Ethereum's current witness sizes are ~1 MB per block. Post-Verkle, they target ~250 KB, a 75% reduction. This is the difference between requiring a data center and running a node on consumer-grade internet.
takeaways
VERKLE TREES & NODE ECONOMICS
Key Takeaways for Builders & Operators
Verkle trees are a foundational upgrade to Ethereum's state structure, shifting the primary node bottleneck from disk I/O to network bandwidth.
01
The Problem: State Growth Chokes Node Hardware
Ethereum's Merkle Patricia Trie (MPT) forces nodes to perform ~1000 disk I/O operations for a single state proof. This makes running a node prohibitively expensive for individuals, centralizing infrastructure to large providers like Infura and Alchemy.
- State size grows ~50 GB/year, compounding the issue.
- SSD requirements become a hard, escalating cost floor.
~1000 I/O
Per Proof
+50 GB/yr
State Growth
02
The Solution: Verkle Trees & Statelessness
Verkle trees use Vector Commitments (like KZG) to create tiny, constant-sized proofs (~150 bytes). This enables stateless clients, where validators only need the block and a proof, not the full state.
- Bandwidth becomes the primary cost, not storage I/O.
- Enables light clients with full-state security, challenging centralized RPC dominance.
~150 B
Proof Size
Witness → Bandwidth
Bottleneck Shift
03
The New Economics: Bandwidth as a Commodity
Post-Verkle, node ops compete on network latency and data throughput, not just capital for high-end SSDs. This commoditizes a more widely available resource.
- Home staking viability increases as hardware requirements democratize.
- Infrastructure-as-a-Service models (e.g., POKT Network, Blast API) gain an edge by optimizing global bandwidth distribution.
Latency
Key Metric
Home Staking ↑
Viability
04
The Builder Mandate: Design for Stateless Verification
Applications must optimize for the new stateless paradigm. Contracts with massive state reads per transaction will be disproportionately expensive.
- Witness size is the new gas guzzler. Batch operations.
- Layer 2s (e.g., Arbitrum, Optimism) must adapt their proving systems to be Verkle-efficient or face high L1 settlement costs.
Witness Size
New Cost Vector
L2s Impacted
Settlement Cost
05
The Risk: Witness DOS & P2P Network Overhaul
Bandwidth-driven networks are vulnerable to Witness Denial-of-Service attacks, where malicious actors spam transactions with large witnesses. The Ethereum P2P layer requires a fundamental redesign.
- Req/Resp protocol must be replaced with a transaction gossip model.
- Solutions like EIP-4444 (history expiry) are prerequisite to manage the load.
Witness DOS
New Attack Vector
P2P Redesign
Required
06
The Long Game: Enabling the Verge & Splurge
Verkle trees are not the end goal but the essential enabler for Ethereum's final scaling phases. They unlock The Verge (full statelessness) and The Splurge (maximal decentralization).
- ZK-EVMs (e.g., zkSync, Scroll) benefit massively from efficient state proof recursion.
- Final step towards a single consumer-grade machine verifying the entire chain.
The Verge
Enabled
ZK-EVM Synergy
Proof Recursion
ENQUIRY
Get In Touch
today.
Our experts will offer a free quote and a 30min call to discuss your project.
NDA Protected
Confidentiality24h Response
Time to ValueDirectly to Engineering Team
No Sales Fluff10+
Protocols Shipped
$20M+
TVL Overall