Ethereum Foundation Updates L2 Benchmarks as Solana Reports Latency Improvements

Executive Summary

• Ethereum ecosystem dashboards formalize throughput, finality, and data cost benchmarks across leading Layer 2 networks, enabling apples-to-apples comparisons for developers and enterprises according to L2Beat.
• Solana engineering teams highlight latency and validator performance metrics from recent network telemetry, spotlighting client diversity and pipeline optimizations as documented by Solana.
• Zero-knowledge projects publish prover time and hardware cost disclosures to quantify real-world proving overheads for rollups, with public notes from Polygon Labs and StarkWare.
• Data availability platforms detail pricing per megabyte and sampling assumptions to benchmark rollup total costs, with methodology updates accessible via Celestia and Ethereum.org.

Why Benchmarks Are Tightening Now Recent updates from Ethereum scaling trackers and client teams emphasize standardized definitions for throughput, latency, finality, and data availability (DA) costs to reduce confusion for infrastructure buyers and application teams. Public dashboards increasingly separate raw transactions per second from gas-normalized throughput and sustained rates under load, a distinction highlighted by L2Beat’s activity methodology and Ethereum.org scaling guidance. For builders, the headline shift is comparability. Rollups and high-performance L1s now publish latency distributions instead of single-point medians, and they disclose sequencer configurations, batch intervals, and proof generation windows. Solana performance notes point to pipeline, banking, and scheduler improvements that affect end-to-end confirmation times, documented in Solana’s performance guidance, while rollup teams align on presenting time-to-inclusion and time-to-finality separately, reflecting Optimism and Base operator practices. How Teams Are Publishing Comparable Metrics Ethereum L2 networks increasingly report sustained throughput under representative load, rather than peak bursts, and include fee-per-transaction breakouts into execution gas, calldata or blob costs, and proposer tips. This mirrors the methodology shifts described by L2Beat’s scaling activity and DA cost primers on Ethereum.org. Zero-knowledge rollups add prover runtime and hardware footprint to benchmarks, enabling cost-per-proof estimates that roll into end-user pricing, a topic both Polygon Labs and StarkWare have addressed in technical updates. On Solana, validator performance and client diversity have become first-class metrics, with engineering updates underscoring the impact of network stack optimizations on sub-second propagation and reduced tail latency. The documentation and telemetry practices outlined in Solana’s performance docs aim to translate microbenchmarks into observable user-facing confirmation times. For cross-chain comparisons, DA providers like Celestia have pushed for explicit cost-per-MB disclosure and sampling assumptions, making it easier to project total cost of ownership for rollups. Company Comparison Benchmarks Now Tracked Publicly With enterprise procurement ramping up, several teams now publish side-by-side datasets or methodologies so application leaders can evaluate trade-offs. Public trackers and open-source suites like Hyperledger Caliper are seeing renewed use in pre-deployment pilots, especially where RFPs require third-party validation of throughput and latency claims. Meanwhile, infrastructure operators such as Coinbase through Base, and data providers like Messari, are aligning output formats to reduce ambiguity between estimates and on-chain telemetry. Teams are also disclosing operational constraints alongside performance data: sequencer failover modes, proof submission intervals, and congestion control settings. That shift, reinforced by Optimism’s public architecture notes and StarkWare’s proving system updates, helps buyers understand the gap between lab results and production behavior. For readers tracking the broader enterprise implications, see our coverage of related Crypto developments. Company and Network Metrics Snapshot Company And Network Benchmark Snapshot

Network or Stack	Key Benchmark Metric	How Reported	Source
Ethereum L2s (multiple)	Throughput and activity normalization	Gas-normalized, sustained under load	L2Beat scaling activity
Solana	Latency and validator performance	Telemetry plus client optimization notes	Solana performance docs
Polygon zk Stack	Prover runtime and hardware needs	Technical blog updates and benchmarks	Polygon Labs blog
StarkNet	Proof system throughput and costs	Release notes and engineering posts	StarkWare news
Celestia	Data availability cost per MB	Pricing examples and DA assumptions	Celestia blog
Optimism and Base	Time-to-inclusion vs finality	Operator disclosures and docs	Optimism vision, Base blog

What Buyers Should Ask For In 2026 Pilots Enterprise and protocol buyers evaluating stacks should request: sustained throughput at p95 latency targets; breakdowns of fees into execution, DA, and proof costs; and worst-case time-to-finality under congestion or degraded modes. These details are increasingly standard in ecosystem documentation and trackers like L2Beat, and in engineering posts from Solana and Polygon Labs. Procurement teams should also seek independent reproducibility via open suites such as Hyperledger Caliper and compare implied total cost of ownership using DA pricing references from Celestia and Ethereum’s data availability guidance on Ethereum.org. This builds on broader Crypto trends of increased transparency and third-party validation to de-risk deployments while maintaining performance targets. FAQs { "question": "Which benchmarks matter most when comparing Ethereum L2s and Solana?", "answer": "Focus on sustained throughput under load, p95 latency, time-to-inclusion versus time-to-finality, and a clear breakdown of fees into execution gas, data availability, and proof costs. Public resources like L2Beat detail gas-normalized activity for L2s, while Solana documentation highlights latency and validator performance telemetry. Together, these reveal real user experience, not just peak numbers. Ask for reproducible runs, workload definitions, and configuration details from networks and operators." } { "question": "How should zero-knowledge rollup proving costs be evaluated?", "answer": "ZK rollup benchmarks should include prover runtime on specified hardware, memory footprint, and proof submission intervals, plus how they affect batch sizing and finality. Teams such as Polygon Labs and StarkWare have outlined proving considerations in technical posts that translate into end-user fees. Use these disclosures to compare cost-per-proof and sensitivity to hardware upgrades. Consistent reporting makes it possible to project total cost of ownership across different ZK stacks." } { "question": "What data availability metrics should buyers request from providers?", "answer": "Ask for explicit cost-per-megabyte, sampling assumptions, and how data is priced during congestion or upgrades. Providers like Celestia outline DA considerations in blog posts, and Ethereum.org provides guidance on DA trade-offs for rollups. Combine DA costs with execution and proof expenses to estimate end-to-end fees per transaction. Ensure metrics include both typical and worst-case scenarios to capture operational risk." } { "question": "How can enterprises validate network claims before deployment?", "answer": "Use open-source benchmarking suites such as Hyperledger Caliper for reproducible tests, and cross-check results against public dashboards like L2Beat or operator telemetry. For more on [related health tech developments](/a-review-of-digital-therapeutics-market-size-reports-2025-2030-for-uk-europe-us-canada-uae-saudi-arabia-india-brazil-and-china-07-12-2025). Request configuration files, workload definitions, and test harness code. Pilot on realistic workloads that mirror expected user behavior, and measure p95 latency and failure recovery. Include third-party observers or auditors where possible to avoid bias in reported performance numbers." } { "question": "What trends will shape crypto performance comparisons in 2026?", "answer": "Expect more standardized reporting across networks, broader client diversity to reduce tail latency, and clearer disclosures on DA and proving costs. Rollups will emphasize blob usage efficiency and finality windows, while Solana and other high-throughput L1s highlight improvements from network stack optimizations. Greater alignment on definitions will aid procurement, with independent dashboards and open benchmarks serving as the de facto source of truth for buyers." } References

• Scaling Activity Methodology - L2Beat, Accessed January 2026
• Performance and Optimization Guide - Solana, Accessed January 2026
• Polygon Labs Technical Blog - Polygon Labs, Accessed January 2026
• StarkWare News and Updates - StarkWare, Accessed January 2026
• Data Availability and Pricing Posts - Celestia, Accessed January 2026
• Data Availability Overview - Ethereum.org, Accessed January 2026
• Hyperledger Caliper Benchmarking Tool - Linux Foundation Hyperledger, Accessed January 2026
• Optimism Architecture and Vision - Optimism, Accessed January 2026
• Operator Notes and Updates - Base by Coinbase, Accessed January 2026
• Crypto Market Data and Research - Messari, Accessed January 2026