DDN, Nebul and NVIDIA Advance AI Inference Economics Through High-Performance KV Cache Acceleration

PARIS, France - July 8, 2026 - DDN, the global leader in AI and data intelligence solutions, today announced continued progress in its collaboration with Nebul, a European leader in providing sovereign-hybrid cloud solutions, to optimize large-scale AI inference performance through advanced KV Cache acceleration and high-performance data infrastructure.

The collaboration brings together Nebul's AI inference platform, DDN's Infinia data intelligence architecture, and NVIDIA accelerated computing technologies to address one of the most important challenges facing production AI environments: maximizing the economic return on AI infrastructure investments through higher GPU utilization, faster token generation, and lower cost-per-token. DDN's Infinia, running on Nebul's NVIDIA infrastructure, generates new tokens 10x faster and lifts GPU utilisation across Nebul's inference platform.

Across the industry, enterprises, cloud providers, and sovereign AI initiatives are increasingly measuring success through business outcomes such as GPU utilization, cost-per-token, tokens-per-watt, and time-to-production. In this environment, data infrastructure has emerged as a critical determinant of AI profitability.

"The AI conversation has fundamentally changed," said Alex Bouzari, CEO and Co-Founder at DDN. "For years, the industry focused on acquiring GPUs. Today, the question is how efficiently those GPUs generate value. Inference has become the economic engine of AI, and reducing the cost of every token produced is now one of the most important challenges facing the industry."

"For years, the industry focused on building larger models. Today the challenge is making those models economically viable in production," said Arnold Juffer, CEO at Nebul. "Every organization is looking for ways to generate more value from its AI infrastructure investments. Through our collaboration with DDN and NVIDIA, we are demonstrating how KV Cache optimization and high-performance data architectures can improve inference efficiency, reduce latency, and help unlock the next phase of AI adoption.

"AI infrastructure is increasingly defined by efficiency at scale," said Rod Evans, Vice President of Cloud Infrastructure at NVIDIA. "As organizations deploy larger models and agentic AI workloads into production, technologies that improve GPU utilization, reduce latency, and accelerate token generation become critical. DDN continues to be an important collaborator in advancing the data and infrastructure capabilities needed to support the next generation of AI factories."

Running production inference on Nebul's NVIDIA infrastructure, DDN's Infinia platform delivers tokens responses nearly 10x faster than serving the same workloads without a KV cache fabric, and up to 5x faster than alternative solutions. The DDN acceleration advantage was sustained across workload profiles from short interactive prompts to large-token contexts under heavy concurrent demand. The economics follow directly so the same hardware serves more users, generates more tokens, and drives the cost of each one down.

The Economics of AI Have Shifted

Industry attention has historically centered on model performance and GPU availability. However, as organizations deploy AI into production, a new bottleneck has emerged: data movement and inference efficiency.

Agentic AI workloads, retrieval-augmented generation (RAG), and large-scale inference environments place unprecedented demands on infrastructure. Every millisecond of latency and every percentage point of GPU idle time directly impacts profitability.

"Training builds the asset. Inference is where it earns," said Bouzari. "The next generation of AI applications will be powered by agents that perform meaningful business transactions and decisions. The economics of those systems depend on infrastructure that can deliver data at the speed AI operates."

DDN's Infinia platform was purpose-built to address these challenges through distributed KV Cache services, GPU-native data movement, intelligent data orchestration, and high-performance storage architectures that maximize accelerator efficiency.

Accelerating the AI Factory Era

The Nebul collaboration reinforces DDN's broader vision that AI infrastructure must evolve beyond traditional storage architectures and become an active participant in AI execution.

This vision aligns with DDN's leadership position across the AI ecosystem, where the company powers more than one million GPUs worldwide and supports many of the industry's largest AI factories, sovereign AI initiatives, research institutions, financial services organizations, and enterprise AI deployments.

As organizations seek to operationalize AI at scale, DDN believes the defining metrics of success will increasingly become:

• GPU utilization
• Cost per token
• Tokens per watt
• Time-to-first-token
• Time-to-production

Organizations that optimize these metrics will achieve sustainable AI economics. Those who do not risk deploying infrastructure that remains underutilized despite significant investment.

"We don't sell storage," Bouzari added. "We help organizations maximize the economic return on every GPU, every token, and every watt. That's the foundation of the AI economy."

For more information about AI inference economics, visit DDN at RAISE or visit https://www.ddn.com/lp/events/raise-2026/book-a-meeting/.

About DDN

DDN is the world's leading provider of AI data storage and data management platforms, powering over 20 years of innovation across HPC, enterprise, and the largest AI deployments on Earth. With its EXA, Infinia, and intelligent data management platforms, DDN delivers unmatched performance, scale, and business value for customers building next-generation AI factories, hyperscale clouds, and Sovereign AI initiatives. DDN is the trusted partner for thousands of the world's most data-intensive organizations, including the leading national labs, research institutions, enterprises, hyperscalers, financial firms, and autonomous vehicle innovators. For more information, visit https://www.ddn.com.

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DDN Media Contact:
Amanda Lee,
VP, Marketing,
Analyst & Public Relations
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