🚀 #MOVA# Weekly Report 🔗 Ecosystem & Operations • WLFI Supernode Campaign activated — backed by a 20M WLFI incentive pool, unlocking nodes, early access & ecosystem rewards via MovaLiquid. • MOVA × WLFI Subscription Campaign expands access — 20 rounds, 1M WLFI each, enabling seamless participation with USD1 / MOVA. 🎨 Community & Events • Labour Day ⚙️ — recognizing the infrastructure powering payments, capital flows, and the next era of on-chain finance. 🧩 Technical • Next Testnet — Jupiter: EVM Parallel Execution Breakthrough – Optimistic parallel execution (Block-STM) → 3.5×–5× faster processing – Multi-version state cache → eliminates lock contention – Sustains 10,000+ TPS in high-frequency scenarios A major step toward multi-core, high-throughput PayFi infrastructure. 📘 Full report on Medium 👇 #MovaChain# #PayFi# #Web3# #RWA# #BlockchainInfrastructure# #JupiterTestnet# #ParallelEVM#

🇭🇰 The Scaling Summit HK 2026 | Session Recap Host: @499_DAO × City University of Hong Kong Co-host: @0G_labs × OpenSchool x IDM of CityU Special Partner: @BAI_AGI x @hetu_protocol 📌 Topic: High-Performance Execution Layer & Parallel EVM Programmable Intelligence demands extreme performance. ⚡ Top system architects dissected the high-performance execution layer. From parallel EVM to decentralized agentic routing, we explored what it truly takes to process millions of concurrent, autonomous transactions. 🎙️ Speakers & Mod: ▪️ @SerenaSeek, Founder of @BlockCentral_ai (Mod) ▪️ @jinglingcookies, AI Lead at @monad ▪️ @kinnnnnnn_____, CEO of @letsburnlab ▪️@0xLaughing, APAC Lead of @GoKiteAI #TheScalingSummit# #Infrastructure# #ParallelEVM#

Trading on Sei Network just got cheaper than it has been all month. Fees on $SEI have fallen to a 30-day low of $0.00213 per transaction, supporting high-frequency trading on its parallel EVM Layer 1. Details here: Full story:

Sei is leaning into its speed and low-cost edge Network fees on @SeiNetwork have fallen to a 30-day low of $0.00213 for every transaction. A single dollar worth $0.25 can process 117 transactions. The reduced fee suits $Sei's parallel EVM. This enables high-frequency decentralized exchange routing, arbitrage operations, and order book clearance. Market makers also benefit from avoiding cost surges during peak times.

ICYMI @MessariCrypto published a full breakdown of @GravityChain TL;DR - World computer for the agent era - Gravity Skill for AI coding agents - 12,000+ TPS powered by Gravity’s parallel EVM - Native oracle for real-world data Read the full report.

Spec Decoding (DSpark) finally works with Pipeline Parallelism in vLLM!! 🔥 A lot of the GPU poor/proletarian have been asking for this feature for a while now, but it took the recent Kimi K3's massive 2.8T parameters affecting the GPU middle class (B200) for it to be implemented! Before this change, GPU poors that needed to use pipeline parallelism, as their weights didn't fully fit on 1 server, would not be able to take advantage of DSpark. Shoutout to yongqinwang-cmd & Inferact for implementing it in vLLM!

A production-ready GLM-5.3-Flash setup for DGX Spark owners. - Tensor Parallelism: TP4 & TP8 specifically tuned for Spark nodes. - Optimized SGLang & NVFP4 - Ready for multi-node -

Join the @DeepSpeedAI team for virtual office hours on October 27! At last week’s PyTorch Conference, the DeepSpeed team shared the project’s latest progress during the PyTorch Foundation keynote and a technical session. They highlighted advances including AutoEP (expert parallelism), AutoTP (tensor parallelism), AutoSP (sequence parallelism), and Ray-based pipeline parallelism, with benchmarks showing that DeepSpeed matches or outperforms other state-of-the-art frameworks on the workloads evaluated. These virtual office hours will offer a deeper dive into the features and benchmark results presented at the conference, along with a discussion of DeepSpeed’s proposed Q4 roadmap. Interested in learning more, asking the team questions, or contributing to these projects? Join the conversation and share your ideas for what DeepSpeed should prioritize next. Everyone is welcome! 📅 Tuesday, October 27 🕘 9 AM PT / 12 PM ET 🔗 Join:

DeepSeek open-sourced the inference engine behind its own production AI service. DeepInfer is the framework DeepSeek uses to serve V4.1 Flash and they're giving away production tricks such as ⚡ DSpark speculative decoding 🧠 confidence-scheduled verification 📚 SWA bounded replay ⚙️ asynchronous scheduling 🧩 MoE expert parallelism + load balancing 🎯 structured JSON / regex / grammar output 🔬 deterministic + batch-invariant inference Plus DeepSeek's own stack of FlashMLA + DeepGEMM + DeepEP + DeepSelect + custom TileLang kernels DeepSeek says that future model inference code + new optimizations will land on this stack too. This is basically a look inside the code DeepSeek uses to make its enormous models practical to host. So now other inference harnesses can study the production implementation. ⚠️ Right now DeepInfer supports only ❌ no consumer NVIDIA GPUs ✅ NVIDIA SM100 ✅ Huawei Ascend 950 So this isn't Local AI yet. GH link in ALT