Earlier this year, we set a new record by computing 314 trillion digits of Pi. The calculation ran for months on a single Dell PowerEdge R7725, pushing modern CPU and storage infrastructure to the limit while demonstrating just how far enterprise hardware has come. When the run finally finished, however, the record itself turned out

Lenovo’s ThinkPad P16 Gen 3 is a high-end mobile workstation built around Intel’s Core Ultra 9 275HX and NVIDIA’s RTX PRO 5000, paired with a 16-inch 3200 x 2000 Tandem OLED touchscreen. It is a 5.6-pound workstation-replacement system built for users who rely on GPU acceleration, high-core-count CPUs, large memory pools, and PCIe Gen5 storage,

Lenovo designed the ThinkPad P14s Gen 6 for engineers, educators, and creative professionals who need to handle heavy workloads while staying highly portable. Equipped with the Intel Core Ultra 7 265H, this mobile workstation features a dedicated NPU (Neural Processing Unit) with Intel AI Boost, delivering up to 13 TOPS of efficient AI-accelerated performance. Additionally,

On December 15, 2025, Microsoft announced that Windows Server 2025 would finally adopt the NVMe standard natively in its storage architecture. However, NVMe storage has been a popular storage format on servers, enterprise workstations, and consumer PCs for many years, with OS compatibility built in since Windows Server 2012 R2 and Windows 8.1. With this

The Acer Veriton GN100 AI Mini Workstation is one of several Spark-based systems we are evaluating, all built around NVIDIA’s GB10 Grace Blackwell Superchip. Like the others, the GN100 is designed to bring datacenter-class AI compute into a compact desktop form factor, enabling developers and researchers to run and refine models locally rather than relying

When we first got our hands on the NVIDIA DGX Spark back in October, it was clear that NVIDIA was serious about shrinking datacenter-class AI down to something that could live on a desk. Our initial Founders Edition sample gave us an early look at what the Grace Blackwell-based GB10 platform could do in a

With the initial release of NVIDIA’s DGX Spark platform, we’re now seeing different vendors package the GB10 Grace Blackwell foundation into their own compact desktop systems. While the core board and silicon remain standardized, differences emerge in chassis design, cooling behavior, storage configuration, and overall execution. In this review, we’re focusing on GIGABYTE’s implementation with

The ASUS Ascent GX10 follows the same core build around the NVIDIA GB10 Superchip, pairing an Arm v9.2-A CPU complex with integrated Blackwell graphics and 128GB of unified LPDDR5x memory. NVIDIA rates the platform at up to 1 petaFLOP of FP4 AI compute, supporting model fine-tuning up to 200 billion parameters. CPU and GPU communication

The AI infrastructure market is not moving in a single direction; it is separating into two distinct worlds. On one side are frontier training clusters, built to develop foundation models at a massive scale, tightly coupled to proprietary fabrics and a narrow set of accelerators. The other is the rapidly expanding reality of enterprise inference,