Maxsun has officially announced the ARL-HX Mini Station, a high-performance compact workstation built for professional computing tasks. The 20-liter system packs powerful hardware into a small form factor, making it suitable for data-heavy applications, content creation, and AI-based workloads.
The ARL-HX Mini Station features a full-metal chassis designed for maximum airflow. Large mesh panels and ventilation points on the front and sides help maintain stable temperatures. It uses independent cooling chambers for the CPU and GPU, preventing heat buildup between components. The chassis also supports standard ATX power supplies, enabling flexible upgrade options.
At the heart of the system is Intel’s Core Ultra 9 275HX processor, offering 24 cores (8 performance and 16 efficiency cores) with clock speeds up to 5.4 GHz and a 160W TDP. The processor is soldered onto a mobile-on-desktop (MoTD) motherboard, optimized for stability and speed.
Memory support extends to 256 GB of DDR5 SO-DIMM RAM, with overclocked speeds of up to 7200 MT/s. The motherboard uses a custom T-shaped layout with enhanced wiring to handle high-speed memory performance.
For graphics, the Mini Station is configured with two Intel Arc Pro B60 GPUs, each featuring 24 GB of VRAM for a combined 48 GB capacity. The dual PCIe Gen5 slots allow for either two smaller GPUs or a single larger GPU, such as the RTX 5090, giving users flexibility for different workloads.
The ARL-HX Mini Station offers an extensive range of connectivity options, including four Thunderbolt ports (two TB5 and two TB4), 10G and 2.5G Ethernet, Wi-Fi 7, and eight USB Type-A ports split between the front and rear. Storage options include three M.2 slots, two SlimSAS SFF-8654-4i connectors supporting eight SATA devices, and a PCIe x4 slot.
The Maxsun ARL-HX Mini Station will begin shipping in September 2025, starting at approximately $2,800 USD. With high memory capacity, dual GPU support, and extensive connectivity, it is positioned as a capable workstation for professionals working with large datasets and demanding computational tasks.
