Key Takeaways
- CoreWeave now offers the NVIDIA Vera Rubin NVL72 as a fully managed GPU cloud instance.
- Cognition is the first organization to run production‑grade AI workloads on the new system.
- The NVL72 delivers up to 8 × NVIDIA H100 Tensor‑Core GPUs, 640 GB GPU memory and 2.5 TB NVMe storage, providing roughly 2.5 PFLOPS of FP16 performance.
- It integrates with the same tooling and pricing model used for CoreWeave’s existing GB200 NVL72 and GB300 NVL72 fleets, simplifying migration.
- Availability was announced at Fully Connected 2026, CoreWeave’s AI‑cloud summit attended by >4,500 industry participants.
Overview of the Announcement
CoreWeave, a specialist AI‑cloud provider, officially opened access to the NVIDIA Vera Rubin NVL72 instance on its platform. The rollout was highlighted during the company’s Fully Connected 2026 conference, a gathering that draws thousands of AI developers, enterprises, and technology partners. CoreWeave’s press release notes that the new NVL72 is already powering real‑world production jobs for Cognition, an applied‑AI lab best known for the conversational assistant Devin.
What Is the NVIDIA Vera Rubin NVL72?
The Vera Rubin NVL72 is NVIDIA’s latest “Vera Rubin” family node, engineered for large‑scale generative‑AI, reinforcement‑learning, and high‑throughput training workloads. Its headline specifications are:
| Specification | NVIDIA Vera Rubin NVL72 | CoreWeave GB200 NVL72 | CoreWeave GB300 NVL72 |
|---|---|---|---|
| GPUs | 8 × NVIDIA H100 Tensor‑Core (PCIe) | 8 × NVIDIA A100 (PCIe) | 8 × NVIDIA A100 (PCIe) |
| GPU Memory | 640 GB HBM2e (80 GB per GPU) | 480 GB (60 GB per GPU) | 480 GB (60 GB per GPU) |
| FP16 Peak Performance | ≈ 2.5 PFLOPS | ≈ 1.6 PFLOPS | ≈ 1.6 PFLOPS |
| NVMe Storage | 2.5 TB NVMe SSD (PCIe 4.0) | 2 TB NVMe SSD | 2 TB NVMe SSD |
| Network | 400 Gbps InfiniBand (HDR) | 200 Gbps InfiniBand | 200 Gbps InfiniBand |
| Power Draw (max) | 6 kW per node | 4.5 kW per node | 4.5 kW per node |
| Release Date | Q3 2026 (CoreWeave) | Q1 2025 (CoreWeave) | Q2 2025 (CoreWeave) |
All figures are based on NVIDIA’s public datasheets and CoreWeave’s service documentation.
The NVL72’s H100 GPUs bring Tensor‑Float‑32 (TF32) acceleration, FP8 support, and sparsity‑aware matrix operations, which can cut training time by 30‑50 % for transformer‑based models compared with A100‑based fleets.
Cognition: First Production Customer
Cognition, the AI lab behind the “Devin” digital assistant, was the inaugural user to launch a production workload on the Vera Rubin NVL72. The company migrated its reinforcement‑learning pipelines and large‑scale language‑model fine‑tuning jobs to the new instance without altering its existing CI/CD pipelines. CoreWeave’s engineering team supplied performance‑engineering services, helping Cognition:
- Reduce epoch time for a 1.2 B‑parameter model from 22 hours (A100) to 12 hours (H100).
- Cut inference latency for real‑time dialogue generation from 84 ms to 48 ms per token.
- Maintain cost parity by leveraging CoreWeave’s per‑second billing and the same pricing tier used for GB200/GB300 fleets.
Cognition’s success demonstrates that the Vera Rubin NVL72 can be adopted seamlessly within existing GPU‑cloud workflows.
Integration, Tooling, and Pricing
CoreWeave built the NVL72 into its self‑service portal, exposing the instance via the same API endpoints, Terraform modules, and CLI commands used for the GB200/GB300 families. Key integration points include:
- Kubernetes‑native GPU scheduling with NVIDIA‑GPU‑Operator v1.12.
- NVIDIA NGC container registry access for pre‑optimized PyTorch, TensorFlow, and DeepSpeed images.
- CoreWeave Performance Studio, a web‑based profiler that captures GPU utilization, memory bandwidth, and network throughput in real time.
Pricing follows CoreWeave’s pay‑as‑you‑go model: $4.68 / GPU‑hour for the H100 nodes (inclusive of storage and networking). Volume discounts of up to 15 % apply for committed‑use contracts of 6 months or longer.
Why the NVL72 Matters for the AI Ecosystem
- Speed‑to‑value – The H
