How XPUs Meet a World-Class AI Factory

To generate intelligence at scale, AI factories run continuously, and their economics are defined by delivered output: tokens per second, tokens per watt, cost per token, utilization and uptime. 

That requires AI infrastructure designed and built as a full factory, not a collection of individual accelerators.

Hyperscalers and AI-native companies building custom XPUs must consider not just XPU design, but the design and development of the entire AI platform, including scale-up and scale-out networking, rack-scale architecture, production factory software and a robust supplier ecosystem. 

At AI factory scale, this path is complex and costly, and represents a fundamental obstacle to getting XPUs to market quickly. 

Breaking the constraint means combining custom XPUs with proven, mature infrastructure — allowing builders to focus innovation where it matters most while harnessing established technology for the rest. 

NVLink Fusion delivers on that need, connecting XPUs to NVIDIA’s world-leading AI infrastructure to increase performance, accelerate time to market and mitigate risk for semi-custom AI factories.

Unlock XPU Performance With Fast Scale-Up

For modern workloads such as running trillion-parameter models, mixture-of-experts architectures and agentic AI, if the scale-up fabric cannot keep up, utilization drops and cost per token rises.

A scale-up networking solution must excel on three dimensions: 

• Delivered performance: End-to-end network performance, in-network compute and  mature software integration.
• Factory resiliency: Uptime, continuous health monitoring and telemetry, and component-level serviceability while the factory keeps running.
• Platform maturity: Reduced operational risk by using a mature technology stack with a demonstrated track record of large-scale deployments and realized return on investment.