Stavros Vlachakis

One debug_traceBlock on Ethereum mainnet can be 2+ GB of JSON in RAM. It's the heaviest RPC workload a node serves. @Nethermind 1.39.0 streams traces per-opcode: 15 ms to first byte, 40% faster, 99.98% less memory, same 2 GB output, byte for byte.

If you're an Ethereum RPC or infra provider, execution speed sets your latency floor and memory sets your bill. @Nethermind is the fastest execution client on 90% of Mainnet blocks, most consistent on p95/p99 blocks on <1/3 the peak RAM of the alternative.

@Nethermind Add to that rock solid stability and fastest developing client Nethermind / Reth / Ethrex for last month: Merged PR's: 318 / 177 / 82 Authors: 40 / 41 / 13 Lines added 96k / 18k / 38k

The most impressive parts is than @Nethermind client does this while being most consistent on slow blocks (p95 and p99). And maintaining lowest memory footprint.

And now, 90% of Ethereum blocks over the last 24 hours have been executed fastest by the @Nethermind client.

Great dashboard for tracking Ethereum client performance, created by the EthRex team. @Nethermind has been the fastest client to process approximately 80% of Ethereum blocks (last 12 hours results). Full dashboard: grafana.ethrex.xyz/d/client-cmp-v…

1/ Announcing Ethereum Institutional An independent non-profit dedicated to accelerating the institutional adoption of Ethereum, its L2s, applications and overall ecosystem.

Looking back at Nethermind's core development journey over the years makes me incredibly proud of what the team has accomplished. The Resiliency Phase Before the Merge, there was effectively no alternative to Geth. It was by far the most stable and performant execution client, and execution client diversity barely existed. That concentration posted a major risk to Ethereum's resilience and one of its core properties: never going down. Today, Nethermind stands alongside Geth as one of the leading execution clients, with each accounting for roughly 30% of the network. The Ethereum Scaling Phase Once execution client diversity became a reality, the next major challenge was scaling Ethereum. Ethereum had been stuck at around a 30M gas limit for a long time. Nethermind led much of the performance engineering effort, demonstrating that Ethereum could safely operate at significantly higher throughput. Beyond setting an example, many of our optimisations and ideas were adopted by other client teams, helping raise performance across the whole Ethereum. Just as importantly, we helped establish a performance engineering culture within Ethereum core development, bringing a more data-driven approach to gas limits and gas pricing. That work was later adopted and expanded by the EF. Ethereum still has plenty of room to scale, but we're moving in the right direction. What's Next We’re now focused on the next set of challenges: 1. Executing on the Strawmap while leveraging AI as much as possible and exploring how AI agents can make Ethereum development increasingly autonomous. 2. Making Ethereum post-quantum resilient. It's part of the Strawmap, but it's important enough to deserve a separate point. 3. Accelerating institutional adoption of Ethereum. 4. Improving RPC layer - from hardening and design to making it verifiable.

Nethermind 1.38.0 is live: 51 contributors. 372 changes. Nethermind co-authored EIP-7928 (Block-level Access Lists), which lands in this release. BALs let the client declare storage accesses up front and execute independent transactions in parallel rather than sequentially. EIP-7976 increases calldata floor cost and EIP-7981 prices access list tokens. All three are implemented ahead of Glamsterdam activation. Several performance improvements: Hot-path optimizations across the execution layer. Address bytes are now embedded inline, removing a secondary allocation. EVM stack and EvmMemory tighten, parallel execution reduces worldstate and txprocessor allocations, and precompile caching extends. EraE support arrives. Operators can prune historical data from local storage and re-import any block range from a SHA-256-verified remote archive, covering pre and post-merge. The P2P layer rewrite cuts per-peer allocation by 54MB and 2.25M objects. Flat DB now persists its layout and refuses to start under a mismatched one, eliminating a class of restart-time corruption.

First blocks processed using the Nethermind execution client on a full @Arbitrum local chain simulation🧪 A major step in our partnership to bring high-performance client diversity to Arbitrum. We are using a modified version of nitro-testnode to initialize a fresh local chain and process blocks using the Nethermind Client. This will be our foundation for testing newly implemented features and configurations. We are currently working on web assembly execution and adding stylus support. Up next: Syncing to Sepolia testnet.

🎉The @gnosischain Pectra hardfork is a success and is running smoothly on the Nethermind Client! A big congratulations to the Gnosis team for this impressive milestone and for leading the way towards implementing the Pectra upgrade!

The Aztec Public Testnet is Live! Bringing users to Ethereum is going to require privacy. We’re building on @aztecnetwork because privacy isn’t a feature, it’s the foundation. Link: aztec.network/developers

Aztec’s Public Testnet is live. The privacy revolution is finally here.

REAL decentralization. With Gigagas. Surge testnet is live in Stage 2! A based rollup template showcasing trustless scaling true to @Ethereum principles. 1 Ggas per second capacity via Nethermind Client, on a fully open-source stack you can use today. Get started now: - Add to wallet - Bridge Hoodi ETH - Start experimenting Check out our docs: docs.surge.wtf Explore our Github: github.com/NethermindEth/…