Embracing extreme co-design with NVIDIA, Coreweave is delivering an order-of-magnitude performance leap on Vera Rubin NVL72.
Close collaboration with partners like CoreWeave is mission-critical to bringing up a new generation of NVIDIA accelerated computing into AI factories.
After months of co-engineering work, CoreWeave became the first AI cloud to bring up and validate Vera Rubin NVL72 — and it is now sharing the first measured performance numbers from live hardware.
CoreWeave ran a DeepSeek-R1 benchmark on Vera Rubin NVL72 and saw 10x improvement in tokens per second per megawatt compared with Grace Blackwell NVL72.
Tokens per megawatt is the metric that determines whether AI infrastructure can profitably scale. More tokens per megawatt means more intelligence from the same power budget, or the same workload on significantly less power . AI labs and enterprises such as Jane Street will use the Vera Rubin platform to scale its AI factories on the CoreWeave cloud.
DeepSeek R1’s MoE architecture makes all-to-all GPU communication a critical requirement at scale: Each token must be routed across distributed expert sub-networks. Vera Rubin NVL72’s 260 TB/s all-to-all NVLink 6 fabric removes that constraint, enabling the rack to behave as a single unified accelerator.
CoreWeave is among the first to deploy the NVIDIA Spectrum-X Ethernet SN6600-LD as the switching fabric for Vera Rubin NVL72.
Built on the 102.4 Tb/s Spectrum-6 switch chip and featuring a liquid-cooled design, CoreWeave deploys dense switching racks, delivering 1.64 Pb/s per rack with 100% more capacity than previous generation air-cooled switches. CoreWeave also provides a fully non-blocking, multi-plane, multi-rail spine and leaf fabric connecting Vera Rubin NVL72 GPUs without oversubscription.
NVIDIA Vera Rubin NVL72 is powering Google Cloud’s first A5X instance, now up and running for London startup Ineffable Intelligence.
Ineffable Intelligence develops a new generation of intelligent “superlearner” systems that continuously learn through experience to discover new breakthroughs across all fields.
Ineffable Intelligence’s agents learn directly from interaction with their environments, rather than from static datasets. Instead of using large language models, Ineffable is developing “superlearner” systems through reinforcement learning, generating experience across continuously simulated, massively parallel environments and rapidly translating that experience into policy updates and evaluation. These tightly coupled learning loops place exceptional demands on compute, memory bandwidth and interconnect, requiring infrastructure that can operate at enormous scale with extremely low latency.
“The next era of research requires the next era of hardware,” said Lasse Espeholt, cofounder of Ineffable Intelligence. “We feel privileged to work with the teams at NVIDIA and Google Cloud, who were able to grant us early access to Vera Rubin. The support across both teams has been unmatched; we were up and running almost immediately and are already testing infra for our superlearners.”
NVIDIA Vera Rubin NVL72 is designed for this kind of agentic training , delivering predictable latency, high utilization and significantly more intelligence per dollar than previous-generation systems, making it a natural platform choice for large-scale reinforcement learning.
Google Cloud A5X instances, announced at Google Cloud Next , are bare-metal instances built on NVIDIA Vera Rubin NVL72 rack-scale systems, delivering up to 10x lower inference cost per token and 10x higher token throughput per megawatt than the prior generation.
A5X uses NVIDIA ConnectX‑9 SuperNICs combined with next-generation Google Virgo networking, enabling clusters that can scale to tens of thousands of NVIDIA Rubin GPUs within a single site and up to nearly a million GPUs across multisite configurations, giving customers a unified, AI‑optimized stack for training, tuning and serving frontier, open, agentic and physical AI models while optimizing for performance, cost and sustainability.
This infrastructure is designed to help unlock the next generation of reinforcement learning systems for breakthroughs in superlearning and superintelligence.
Benchmark results from DeepInfra show that the NVIDIA Vera CPU is more than twice as fast and can support more concurrent AI agents compared with other CPUs.
Cloud platform DeepInfra, an early access participant in the NVIDIA open AI ecosystem, independently designed and ran benchmarks using its production AI agent infrastructure. DeepInfra processes nearly five trillion tokens a week, with about 30% driven by agentic systems. Its cloud platform is built for high-throughput AI inference.
The benchmarks demonstrate support for up to 1.6x more concurrent AI agents at the same quality of service and up to 2.2x faster orchestration than alternative CPUs, while improving infrastructure utilization and cost efficiency. These results show that the NVIDIA Vera CPU delivers the cost efficiency, low latency and throughput that production agentic AI demands.
As AI agents take on more complex reasoning, planning, tool use and data movement, CPU performance has become increasingly important for orchestrating work around each model call.
Part of NVIDIA’s extreme codesign approach to AI factories, the Vera CPU is built for agentic workloads. DeepInfra’s benchmark highlights how the NVIDIA Vera CPU helps cloud providers improve infrastructure utilization, increase cost efficiency and support more concurrent AI agents at the same quality of service.
Learn more about the NVIDIA Vera Rubin platform .
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
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Reference reading
- https://blogs.nvidia.com/blog/vera-rubin/#primary
- https://blogs.nvidia.com/blog/author/nvidiawriters/
- https://blogs.nvidia.com/blog/vera-rubin/#disqus_thread
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