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New capabilities across compute, storage and networking keep customers productive and accelerate the AI loop. #pressrelease September 16, 2026
CoreWeave, Inc. (Nasdaq: CRWV), The Essential Cloud for AI™, today announced the bring up of multi-rack NVIDIA Vera Rubin NVL72 on CoreWeave Cloud, putting hundreds of NVIDIA Rubin GPUs into a single scale-out cluster for agentic AI. The company also announced two new capabilities in CoreWeave AI Object Storage, cross-region write acceleration and a new Archive tier, that keep the data those workloads depend on close to the GPUs.
Multi-rack Vera Rubin NVL72 clusters allow for training and inference jobs to run across hundreds of Rubin GPUs. That matters for multi-step agentic workloads, which are sensitive to data-access latency because delays can compound across repeated model calls and tool use. Cross-region write acceleration removes the wait even when working across multiple regions. A job writes locally while CoreWeave replicates the data to another region in the background, so an agent's intermediate state, retrieved context, and outputs move as fast as its reasoning. The GPUs don't wait, and neither does the loop.
Scaling agentic AI with multi-rack NVIDIA Vera Rubin NVL72
A single NVIDIA Vera Rubin NVL72 rack pairs 72 Rubin GPUs with 36 Vera CPUs, NVIDIA NVLink 6, NVIDIA ConnectX-9 SuperNICs, and NVIDIA BlueField-4 DPUs. With multi-rack Vera Rubin NVL72, CoreWeave unifies racks of hundreds of accelerators using NVIDIA Spectrum-X Ethernet networking into a single scale-out cluster. This delivers the capacity to train larger models, serve more demanding inference workloads, and run reinforcement learning at scale, and achieves required engineering at every layer across compute, networking, storage, cooling, power, firmware, and software, to perform as one coordinated system.
CoreWeave brings multiple racks up as a single system through:
Automating rack life cycle control. Racks arrive as hardware that needs to be connected and validated. CoreWeave Mission Control® automates rack setup through the Rack LifeCycle Controller, which coordinates hardware detection, firmware updates, validation, power, and cooling, with Racky providing rack control and Valvey executing cooling actions.
Validating performance from components to systems. CoreWeave combines NVIDIA field diagnostics with full-rack workload testing, comparing every result, building upon years of real-world experience, before a rack goes into production. Only racks that clear this bar as a system move into production, so every GPU performs at its best.
Scaling the network with the GPUs. Every Rubin GPU is equipped with two NVIDIA Connect X-9 SuperNICs per Rubin GPU, providing 1.6 Tb/s of connectivity scale out connectivity per GPU across multiplane, multirail paths, supporting roughly 128,000 GPUs per rail in a non-blocking fabric. The modular topology allows racks to be added without redesigning the fabric at each expansion.
Read the full press release here.