Nutanix announced that its Nutanix Unified Storage (NUS) solution is now NVIDIA-Certified at the enterprise level, validating the platform for enterprise and cloud provider deployments running large-scale production AI workloads. The certification provides a validated configuration intended to reduce integration risk and help customers scale AI infrastructure with more predictable storage behavior.
The company also disclosed plans to extend its AI-native storage roadmap with support for NVIDIA Vera BlueField-4 STX. Nutanix framed this as an effort to improve data access and storage efficiency while simplifying operations as AI environments grow.
Addressing Storage as a GPU Utilization Constraint
As organizations build out “AI factory”-style infrastructure, Nutanix is targeting a recurring problem in production environments: GPU capacity is often limited by the ability to consistently feed data to accelerators. Fragmented infrastructure, siloed datasets, and inconsistent I/O can introduce bottlenecks that slow deployments and reduce effective GPU utilization. Nutanix is positioning NUS, along with its NVIDIA certification, to deliver a more consistent data path and reduce deployment variability across the stack.
Thomas Cornely, EVP of Product Management at Nutanix, emphasized that the goal is to remove infrastructure fragmentation and data silos so AI pipelines can sustain reliable throughput at scale. Jason Hardy, VP of Storage Technology at NVIDIA, similarly highlighted storage as a gating factor for enterprise AI, noting that certification provides customers with a more interoperable platform, reducing bottlenecks and improving GPU efficiency. Both sets of comments centered on interoperability, predictable scaling, and validated configurations rather than point performance claims.
Reference Architecture
Nutanix described the NVIDIA-Certified NUS reference architecture as being built on a 10-node all-NVMe cluster. On the protocol side, it uses enhanced parallel NFS (pNFS) and GPUDirect Storage over NFS with RDMA. The objective is a low-latency, high-throughput data path between GPU hosts and storage, designed to maintain resilience and minimize downtime as environments scale.
For the network fabric, Nutanix stated the design uses NVIDIA Spectrum-X Ethernet, including Spectrum-4 switches and BlueField-3 DPUs. Nutanix also provided scaling figures, claiming linear performance growth from 10GB/s read and 5GB/s write at 32 GPUs up to 160GB/s read and 80GB/s write at 1,024 GPUs.
Workload Coverage and Supported GPU Platforms
Nutanix positioned the architecture as a foundation for a range of AI workflows, including training, fine-tuning, inference, and RAG pipelines. The company also described broad compute compatibility, citing support for x86-based systems and multiple NVIDIA GPU configurations, including NVIDIA RTX 6000 PRO Blackwell, NVIDIA H200 NVL, NVIDIA HGX platforms with B200, H200, or H100 GPUs, and NVIDIA GH200 Grace Hopper Superchip configurations.
Availability
Nutanix said the NVIDIA-Certified Nutanix Unified Storage reference architecture is available now. Planned support for NVIDIA BlueField-4 STX is expected in the second half of 2026.
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