Nutanix has announced that its Unified Storage (NUS) solution is now certified by NVIDIA at the enterprise level. This certification aims to empower enterprises and cloud providers to reliably deploy storage solutions that can handle the performance, security, and scaling needs of substantial AI workloads.
Unveiling future support for NVIDIA Vera BlueField-4 STX, Nutanix underscores its commitment to accelerating data access, enhancing storage efficiency, and simplifying AI operations on a large scale.
Maximising GPU efficiency
With the increasing demand for AI factories in enterprises and cloud environments, there is an urgent need for infrastructure that can seamlessly manage data flow, optimise GPU usage, and minimise deployment risks. Essential to this endeavour is the ability to deliver data to powerful GPUs efficiently and reliably, avoiding the pitfalls of fragmented systems and siloed data that can undermine performance and scalability.
The NVIDIA certification granted to Nutanix offers a verified configuration
The NVIDIA certification granted to Nutanix offers a verified configuration to back enterprise-level AI infrastructure deployments. This validation ensures the NUS is compatible with the entire NVIDIA AI infrastructure stack, aiming to alleviate I/O bottlenecks and integration challenges. As a result, organisations can ensure their critical resources, both GPUs and data, operate at peak efficiency within production settings.
Requirements of modern AI workloads
"To build and run AI factories successfully, enterprises must move past fragmented infrastructure and data silos that limit GPU infrastructure efficiency," stated Thomas Cornely, executive vice president of Product Management at Nutanix.
"This NVIDIA certification validates that Nutanix Unified Storage delivers the full-stack interoperability, linear scalability, and reliable data velocity that modern AI workloads demand. By collaborating closely with NVIDIA, we are giving customers a unified, high-performance foundation to scale their production AI operations with confidence."
The role of storage in AI workloads
Jason Hardy, vice president of Storage Technology at NVIDIA, noted, "As enterprises scale their AI factory deployments to meet demanding agentic AI workloads, storage is foundational to unlocking full-stack performance, efficiency, and accuracy. Nutanix Unified Storage achieving NVIDIA certification gives customers a trusted, interoperable foundation to eliminate data bottlenecks, maximise GPU utilisation, and scale production AI workloads with confidence."
AI performance at scale
To support large-scale AI, the solution incorporates NVIDIA Spectrum X Ethernet
Nutanix Unified Storage is built on a 10-node, all NVMe cluster, utilising advanced parallel NFS (pNFS) and GPUDirect Storage over NFS with RDMA. This setup delivers a low-latency, high-throughput data path directly between GPUs and storage, maximising utilisation while minimizing downtime.
The solution provides a scalable base for enterprise AI, enabling transition from specific GPU deployments to expansive production environments, maintaining predictable storage performance as demands grow. To support large-scale AI, the solution incorporates NVIDIA Spectrum X Ethernet, NVIDIA Spectrum 4 switches, and BlueField 3 DPUs, enhancing read and write capabilities from 10 GB/s and 5 GB/s for 32 GPUs to 160 GB/s and 80 GB/s for 1,024 GPUs.
This robust architecture supports a range of AI workloads including training, fine-tuning, inference, and RAG pipelines, across various compute platforms like x86-based systems and NVIDIA HGX servers with the latest GPUs. The NVIDIA-Certified Nutanix Unified Storage reference architecture is currently available, with plans for NVIDIA BlueField-4 STX support anticipated in the latter half of 2026.
Nutanix, a pioneer in hybrid multicloud computing, announces the Nutanix Unified Storage (NUS) solution is NVIDIA-Certified at the enterprise level.
NVIDIA-Certified Storage is designed to enable enterprises and cloud providers to confidently deploy storage solutions that support the performance, security, and scale required for large-scale production AI workloads. Nutanix is also advancing AI-native storage with planned support for NVIDIA Vera BlueField-4 STX, reinforcing its focus on faster data access, greater storage efficiency, and simpler AI operations at scale.
Maximise GPU utilisation
As enterprises and cloud providers race to build AI factories to support production AI workloads, they require infrastructure that can keep data moving, maximise GPU utilisation, and reduce deployment risk. Success depends not only on access to powerful GPUs but on the ability to feed those systems with data efficiently and reliably. Fragmented infrastructure, siloed data, and inconsistent performance can slow deployments, limit GPU efficiency, and make AI harder to scale reliably.
With this certification, Nutanix is providing enterprises and cloud providers with a validated configuration to support enterprise deployment of AI infrastructure. The certification helps ensure NUS is validated for full-stack interoperability with NVIDIA AI infrastructure, helping to reduce I/O bottlenecks and integration risk. By enabling linear scalability for the data-hungry demands of AI workloads, it helps ensure an organisation’s most valuable assets, its GPUs and data, are working at maximum efficiency in production environments.
Modern AI workloads
“To build and run AI factories successfully, enterprises must move past fragmented infrastructure and data silos that limit GPU infrastructure efficiency,” said Thomas Cornely, executive vice president, Product Management, Nutanix.
“This NVIDIA certification validates that Nutanix Unified Storage delivers the full-stack interoperability, linear scalability, and reliable data velocity that modern AI workloads demand. By collaborating closely with NVIDIA, we are giving customers a unified, high-performance foundation to scale their production AI operations with confidence.”
Agentic AI workloads
"As enterprises scale their AI factory deployments to meet demanding agentic AI workloads, storage is foundational to unlocking full-stack performance, efficiency, and accuracy,” said Jason Hardy, vice president, Storage Technology, NVIDIA. “Nutanix Unified Storage achieving NVIDIA certification gives customers a trusted, interoperable foundation to eliminate data bottlenecks, maximise GPU utilisation, and scale production AI workloads with confidence."
Built on a 10-node, all NVMe cluster, NUS leverages enhanced parallel NFS (pNFS) and GPUDirect Storage over NFS with RDMA to establish a low-latency, high-throughput, and resilient data path directly between GPUs and storage—maximising utilisation while minimising downtime.
Large-scale AI performance
The result is a scalable foundation for enterprise AI that helps customers move from targeted GPU deployments to larger production environments while keeping storage performance predictable as AI workloads expand. To support large-scale AI performance, the solution uses NVIDIA Spectrum X Ethernet, including NVIDIA Spectrum 4 switches and BlueField 3 DPUs, and delivers linear scalability from 10 GB/s read and 5 GB/s write for 32 GPUs to 160 GB/s read and 80 GB/s write for 1,024 GPUs.
This resilient, zero-downtime architecture provides a flexible foundation for AI workloads, supporting training, fine-tuning, inference, and RAG pipelines across a wide range of compute platforms including x86-based systems (NVIDIA RTX 6000 PRO Blackwell, NVIDIA H200 NVL), NVIDIA HGX servers with B200, H200, or H100 GPUs, and NVIDIA GH200 Grace Hopper Superchip configurations.
The NVIDIA-Certified Nutanix Unified Storage reference architecture is available today. Planned support for NVIDIA BlueField-4 STX is expected to be available in the second half of 2026.
