Best ASUS Compact & SFF Desktops in 2026

Its 13th Gen Intel Core i7 processor and integrated Iris Xe graphics deliver solid performance within a 0.51kg chassis that supports dual storage drives. The system's extensive connectivity, including Thunderbolt 4 and 2.5G Ethernet, is notable for such a compact form factor. This barebone kit is best for IT departments or home office users building reliable, space-efficient workstations for general productivity and digital signage.

Its compact 0.59kg chassis houses a 14-core Intel Ultra 5 processor and integrated Intel Arc graphics with 16GB of dedicated VRAM, making it a uniquely powerful mini PC. The system offers excellent future-proofing with PCIe 5.0 storage, DDR5 memory slots, and modern connectivity like WiFi 7 and Thunderbolt. This barebone kit is best for professionals seeking a highly portable, modular workstation for business applications and light creative tasks, not gaming.

Its compact 120W chassis houses a 14-core Intel Ultra 5 CPU and 16GB of fast DDR5 RAM, making it a potent mini desktop. The inclusion of WiFi 7 and Thunderbolt 4 provides excellent connectivity for a modern workstation. This system is best for developers and office users who need a powerful, space-saving PC that can drive multiple displays but has no need for serious gaming.

Its AMD Ryzen AI 7 350 8-core CPU and integrated Radeon 860M graphics provide solid performance for office tasks in a remarkably compact 0.55kg chassis. The inclusion of WiFi 7 and a 1TB PCIe 4.0 SSD ensures fast connectivity and storage for modern workflows. This mini PC is best for home office users and small businesses needing a powerful, space-saving desktop for productivity and video conferencing.

Its NVIDIA Blackwell GPU architecture, with 5th Gen Tensor Cores, delivers up to 1,000 AI TOPS for intensive machine learning workloads. The compact 1.48kg chassis houses a 20-core GB10 Superchip and 128GB of LPDDR5x memory, offering exceptional compute density. This system is best for AI researchers and developers requiring a portable, high-performance node for training and inference tasks.