1/ The Eclipse Performance Thesis Eclipse is building the Giga Scale Virtual Machine (GSVM), a new SVM client. A software-hardware co-designed, cross-layer optimized, GigaCompute blockchain that eclipses all scalability limits and represents a paradigm shift in performance.

5/ We discuss the changes, why they work, and provide a demo that can be deployed on any SVM environment in the full blog post. This is the future of apps! Read the full blog here: https://t.co/SKGycBbzYs

4/ The changes are hinged around priority ordering and MEV Taxes (h/t @danrobinson). Taking advantage of them requires minimal work from developers (~30 LoC and <200 CUs), and best of all, is entirely permissionless.

3/ We’ve implemented changes that enable applications to capture MEV via priority fees and control their sequencing (ACS) without losing the composability that comes from living on a general-purpose blockchain.

2/ In the last four years, Solana, Ethereum, Arbitrum, and Base have captured ~4.4 billion USD in priority fees, leaving nothing for the apps that generated most of this value. This is the rent-seeking behavior that motivated Web3, and it has to go.

1/ We have an exciting announcement to share. Permissionless MEV Internalization and Application Controlled Sequencing are now available to developers on Eclipse!

5/ This ZK DA system pushes Eclipse toward L2 stage 1 & beyond, proving verifiable Celestia DA on Ethereum without perf trade-offs. Love open-source? Fork us & contribute! Read the full post here: https://t.co/PmGpJjTXF2

4/ Challenges? We addressed timing issues with Steel History, liveness via custom Blobstream instances, & security concerns like relayer failures. Performance: Proofs in 40s on Bonsai or 20min locally. Anyone can generate proofs. A win for decentralization.

3/ Our ZK guest program verifies Blobstream attestations off-chain, handles index blobs & challenges unavailable data. We tackle block height validation, share proofs, & more. Supports SP1 & RISC Zero Blobstream implementations. Code will be open-sourced soon.

2/ Building on our DA proofs work, we use Celestia Blobstream for blob verification & RISC Zero's Steel for off-chain computations. Result? Constant low costs: Sequencer posts just one 32-byte value; Challenger pays ~300k gas + proof gen. Infinite data scalability unlocked.

1/ Introducing the Eclipse ZK DA Bridge with @celestia & @RiscZero! We've built an optimistic ZK DA challenge system for high-throughput L2s, slashing costs & boosting scalability. Say goodbye to DA headaches. Let's get into it.

6/ The DEX trilemma (Performance, Decentralization, Composability) forces tough choices, but innovation wins for users. This is Part 1. In Part 2 we will dissect top platforms & more. Read the full breakdown: https://t.co/HtGQT0M6vo

5/ Who benefits? Retail: Gasless UX & self-custody. Pros/HFT: Low-latency, MEV protection. Institutions: Compliance-ready audits, privacy via ZK. Monoliths for instant finality. Modular for ETH composability.

4/ Key differentiators? Finality (ms soft vs. min hard), DA economics (on-L1 conservative vs. modular cheap), Sequencer trust (centralized risks mitigated by forced exits). Performance: Hyperliquid ~200k OPS; GTE ~100k TPS, etc. We evaluated them via 4 pillars framework:

3/ Modular stacks (rollups on ETH/Solana) unbundle layers: Off-chain execution for ms soft finality, settlement on L1 for security. Use Celestia/EigenDA for cheap DA. Wins: Shared liquidity, escape hatches. Struggles: Soft-to-hard finality gap exposes risks in high-stakes

2/ Monolithic app-chains like Hyperliquid & dYdX integrate everything into one fast L1: execution, consensus, DA. Pros: Sub-second hard finality, no value leakage. Cons: Less composability with broader ecosystems. Ideal for speed demons prioritizing determinism.

1/ The CLOB Wars are heating up! A $100M+ loss on Hyperliquid wasn't a flop, it proved on-chain DEXs can handle CEX-grade volume. AMMs are out; CLOBs are in for deep liquidity & pro execution. The real battle? Monolithic vs. Modular architectures. Let's dive in.

6/ You can read more about this survey of options at: https://t.co/sWUTwXyZy1

5/ In part 2 of the blog, we explain how we achieved this state of the art performance with fine tuning snapshots frequency, subtree roots count, prefetching:

4/ Result? AlDBaran crushes 24M updates/sec with historization, over 48M without, vastly exceeding goals. You can learn more about the performance in our part 1 blog:

3/ The gap? None sustain the multi-million updates/sec in production contexts needed for true high-TPS blockchains. This shortfall sparked our AlDBaran: Decoupling in-RAM hot-path (Pleiades) from append-only proofs (Hyades), plus SIMD batching, subtree roots buffering, &