🚀 #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#

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 -

A lot of work goes into serving a model efficiently. For the Nemotron 3 Ultra NIM, our engineers tuned caching, memory, parallelism, decoding and more. On four B200 GPUs, those optimizations supported up to 2.5x more concurrent users while maintaining 50 TPS/user. Read the engineering deep dive →

ALERT🚨 GB300 NVL72 NVLINK BACKPLANE ENABLES 13x BETTER PERF PER DOLLAR THAN HOPPER ON AGENTIC INFERENCE Through extreme co-design, GB300 NVL72 uses an innovative copper backplane to expand the scale-up domain to 72 versus 8 on Hopper. This allows optimizations like @vllm_project wide expert parallelism, which allows each GPU to have only a subset of experts.

vLLM @vllm_project sessions at #PyTorchCon# NA 2026 span the serving stack, from attention and KV cache management to disaggregated serving and hardware portability across accelerators. Speakers will cover attention and KV cache systems, disaggregated serving, expert parallelism, and vLLM across TPU, Trainium, Arm, and IBM Spyre. Featured speakers include: @RedHat: Lucas Wilkinson, Matthew Bonanni, Zhanqiu Hu, @rickynds, and Alex Brooks @amazon: Sunita Nadampalli @IBM: Or Ozeri, Thomas Parnell, and Dave Grove @Huawei: Mengqing Cao @nvidia: Itay Alroy @Google: @Rob_Mulla and Qi Zhou @awscloud: Maen Suleiman @Meta: Richard Zou, Colin Taylor, and Angela Yi @BAAIBeijing: Yonghua Lin @fujitsulabs: Abhishek Jain and N Maajid Khan @IBMResearch: Antoni Viros i Martin and Avery Blanchard @MistralAI: Nicolò Lucchesi @tensormesh: @this_will_echo @googlecloud: Bill Jia Register by September 4 to save: Read the vLLM session guide:

NVIDIA GB300 NVL72 IS 7X BETTER 💰💰 PERF PER DOLLAR 💰💰 THAN H200 on long context agentic workloads due to disagg prefill and wide expert parallelism optimizations which take advantage of NVL72 copper backplane.