Equipment Solutions for AI and Creative Production Companies

GPU Workstations, AI Inference Servers and High-Capacity Storage Solutions


Where Does Building an AI Machine in Hong Kong Get Stuck?

You want to build a machine to run model training or an inference service, only to find that Hong Kong retail channels simply have no stock - high-end RTX GPUs are in long-term shortage or selling at inflated street prices, while sourcing overseas yourself takes time and makes warranty follow-up difficult. This is not a short-term phenomenon: GDDR7 VRAM only began mass production at scale in 2026, and capacity is still ramping up; lead times across the entire supply chain for CoWoS advanced packaging, high-end PCB substrates and power management chips have lengthened in tandem. The compute needs of AI start-ups and creative production companies are urgent, but the supply channel has always been the bottleneck.

Market reality (2026): PC Partner Group - Hong Kong-based and Singapore-listed, whose brands include Zotac, Inno3D and Manli - has confirmed that GPU supply will remain tight in the second half of 2026. Industry media filmed local AI companies buying RTX 5090 cards by the box to assemble AI servers, with retail spot prices at one point exceeding RMB 40,000, against an official launch price of USD 1,999.


From Single-Card Workstations to Inference Servers, We Build It for Hong Kong AI Teams

We are a Hong Kong-based AI GPU compute equipment supplier, providing one-stop GPU compute hardware for AI start-ups, generative AI service providers, and VFX and video production companies.


GPU Workstations (Individual / Small-Team Compute)

  • Deep learning workstations fitted with high-end NVIDIA RTX graphics cards, supporting model fine-tuning and local development
  • Current models range from the RTX PRO 6000 Blackwell (96GB GDDR7, around 1.8TB/s memory bandwidth) to the RTX 5090 (32GB), tiered by budget and VRAM requirements
  • Configured to your framework requirements: CUDA core count, VRAM capacity and cooling budget clarified in one go
  • Quiet chassis options, suitable for placement in an office environment

AI Inference Servers (Inference Server)

  • Multi-GPU server platforms supporting model deployment to provide services externally
  • Configuration advice for mixed training and inference workloads, avoiding wasted budget on the wrong specifications
  • Rack-mount designs that can go straight into a server room or a colocation facility

High-Capacity Storage Solutions

  • NVMe SSD arrays: addressing the read/write bottleneck of training datasets
  • NAS / storage servers: centralised management of training data, model checkpoints and asset libraries
  • Tiered storage advice: hot data on NVMe, cold data on high-capacity HDD

Creative Production Compute

  • Workstation configurations for 3D rendering, video colour grading and compositing
  • Multi-node render farm solutions
  • Advice on GPU memory upgrade paths scaled to project size

Deployment Support

  • On-site installation, plus advisory on setting up drivers and framework environments (CUDA, PyTorch and others)
  • Cooling and power assessment: whether your office can handle multi-GPU machines, reviewed together before the quotation
  • Warranty and send-in repair handling, so you don't have to deal directly with overseas manufacturers when hardware fails

Three Questions to Ask Before Buying AI Hardware


Question Why It Matters
Training or inference as the primary workload? Training is about VRAM and bandwidth, inference is about throughput; buying in the wrong direction simply burns money
Office or server room? Determines chassis form factor, cooling and power configuration
How large is the dataset? Determines the scale of the storage array, so you don't under-buy and have to top up later


Tell Us About Your AI Project Requirements

Tell us your model scale, budget and deployment environment, and we will put together an AI compute solution delivered and supported in Hong Kong.