GIGABYTE Showcases Scalable NVIDIA-Powered AI Hardware at Ai Everything Abu Dhabi 2026 Spanning Desktop Supercomputers to GB300 Workstations
ABU DHABI — Global hardware and computing architecture provider GIGABYTE has unveiled its latest portfolio of NVIDIA powered artificial intelligence hardware solutions at Ai Everything Abu Dhabi 2026, taking place from October 6 to 7 at the ADNEC Centre.
Exhibiting at Booth H3 04, the computing manufacturer is showcasing systems engineered to democratize cognitive model development by shifting compute intensive workloads from remote public clouds toward secure, on premise desktop environments. The strategic portfolio enables developers, research institutions, and enterprises to build, fine tune, and validate proprietary algorithms locally while keeping intellectual property and regulated datasets strictly within enterprise perimeters prior to cloud deployment.
Headlining the launch is the AI TOP ATOM, an ultra compact personal artificial intelligence supercomputer based on the NVIDIA DGX Spark platform. Engineered for local algorithm development, fine tuning, and data science modeling, the system delivers 1 PFLOPS of FP4 compute throughput. Operating on high speed NVIDIA ConnectX 7 networking, the plug and play architecture provides storage allocations from one to four terabytes and supports four node clustering through a dedicated QSFP switch with 200GbE connectivity per node, aggregating up to 512GB of unified system memory for larger foundation models.
For heavier enterprise deployments, GIGABYTE is showcasing the W775 V10, a high performance deskside artificial intelligence workstation powered by the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip. The workstation delivers up to 20 PFLOPS of FP4 performance paired with 748GB of coherent system memory. Architected to process up to four hundred concurrent inference requests simultaneously, the system provides sovereign research laboratories and heavily regulated enterprises with the computational horsepower required to execute multi-modal inference and parameter intensive models locally.
Jay Lee, General Manager for Middle East, Turkey, and Africa at Giga Computing, stated that artificial intelligence development has historically imposed high cloud investment thresholds or reliance on congested shared compute clusters, placing small teams and research laboratories at an operational disadvantage. Lee underscored that GIGABYTE’s scalable on premise portfolio empowers technical teams to design, iterate, and validate workloads locally with maximum data sovereignty before expanding to enterprise data center clusters or hyperscale environments.
