Nutanix and NVIDIA align on integrated AI operating environment for enterprise workloads

As enterprises move from experimenting with generative AI to operationalising it at scale, the underlying infrastructure is becoming a central challenge. The rapid evolution of large language models (LLMs) over the past three years has driven unprecedented demand for compute, storage and networking architectures that can support growing model sizes, higher token volumes and increasingly complex AI pipelines.

Against this backdrop, Nutanix and NVIDIA are positioning an integrated AI operating environment aimed at simplifying how enterprises deploy and manage AI infrastructure built on accelerated computing platforms.

From experimentation to AI factories

The initial wave of publicly available LLMs demonstrated how token-based prediction could be applied to tasks such as text generation, image creation, summarisation and translation. As organisations began moving these capabilities into production, infrastructure requirements expanded rapidly—placing pressure on performance, scalability and power efficiency.

NVIDIA’s AI infrastructure has emerged as a foundational layer for ...