Rack-Scale Infrastructure, Validated for AI Factories

At the foundation of “Future Landing” is GIGABYTE’s expanding portfolio of rack-scale AI infrastructure designed for next-generation AI factories.

Among the latest highlights is the NVIDIA Vera Rubin NVL72, showcased as part of GIGABYTE’s broader rack-scale portfolio. Alongside its rack-scale platforms, GIGABYTE also presents GAIFA (GIGABYTE AI Factory Accelerator), a purpose-built AI factory in Taiwan where next-generation compute, high-speed networking, and NVIDIA’s software stack are integrated into a fully validated environment for system verification, workload optimization, and deployment readiness.

At the operational layer, GPM (GIGABYTE POD Manager) provides unified visibility and infrastructure-level monitoring across compute, networking, cooling, and power systems, enabling AI factories to operate and scale as a coordinated system.

Infrastructure Built for Accelerated Deployment

To accelerate deployment beyond conventional data center construction, GIGABYTE introduces GADU (GIGABYTE Accelerated Deployment Unit), a modular AI infrastructure platform that integrates high-density compute, advanced cooling, and power distribution into transportable, deployment-ready systems. Supporting direct liquid cooling and immersion cooling architectures, GADU enables organizations to expand AI capacity with significantly reduced deployment timelines while maintaining flexibility across diverse operational environments.

Together with GIGABYTE's rack-scale systems and infrastructure software, GADU transforms infrastructure into a scalable, rapidly deployable platform.

Physical AI from Simulation to Action

Demonstrating how AI moves beyond simulation and into real-world operation, GIGABYTE presents a complete real-to-sim-to-real workflow built on NVIDIA's full-stack AI platforms.

The workflow begins with high-fidelity digital twins built through NVIDIA OVX systems, powered by the XLS4-SX2-LAS1 platform on NVIDIA MGX™ architecture with RTX™ PRO GPUs for large-scale Omniverse simulations. AI training then advances through the G2L4-SD4-LA08 platform on NVIDIA HGX™ architecture, where synthetic data generation and reinforcement learning take place. Once validated, trained models are deployed to edge systems powered by NVIDIA Jetson for real-time robotic control, brought to life through live demonstrations alongside Isaac Sim visualizations.

Clinical AI at the Point of Care

GIGABYTE also showcases a growing clinical AI ecosystem for real-time medical inference at the point of care. Working alongside healthcare partners, GIGABYTE integrates BRIX mini PCs with AI-assisted diagnostic systems supporting bone marrow smear classification and real-time polyp detection during colonoscopy. The VFG100, an FPGA-accelerated vision platform, delivers real-time image preprocessing with ultra-low CPU overhead, while AI TOP ATOM enables local inference for pulmonary imaging analysis, meeting healthcare data privacy and compliance requirements.

Bringing AI Closer to Where Decisions Are Made

Extending AI beyond centralized infrastructure, GIGABYTE also showcases the W775 workstation and AI TOP ATOM desktop AI supercomputer for private training, model customization, and agentic AI workflows powered by NVIDIA NemoClaw.

Beyond the main showcase on the 1st floor, visitors can also explore GIGABYTE’s dedicated exhibit on the 4th floor, where AI TOP systems and consumer AI innovations demonstrate how GIGABYTE’s computing capabilities extend from AI infrastructure to everyday intelligent experiences. At COMPUTEX 2026, GIGABYTE demonstrates how “Future Landing” is turning AI infrastructure into systems that are ready, deployable, and already happening.