BIZON ZX4000 – Station IA water-cooled (2× A100)

BIZON ZX4000 – AI Workstation (2× A100 / H100)

🔎 Overview

• Model: BIZON ZX4000 – high-end water-cooled AI workstation, built specifically for deep learning training and inference with 2 datacenter-class GPUs (A100, H100, or equivalent).

• Starting Price: $14999 (base config).

💧 Advanced Water-Cooling

• Full liquid-cooling loop (CPU + 2 GPUs) with quick disconnects, reservoir, radiators, and pump.

• Runs up to 3× quieter than air-cooled rigs.

• Keeps GPU temps stable around 50–60 °C (versus 85–90 °C with standard cooling).

⚡ AI Performance Optimized

• Plug-and-play: shipped ready with all major frameworks (TensorFlow, PyTorch, CUDA, cuDNN, etc.).

• Optimized for LLMs (LLaMA, Alpaca), Stable Diffusion, and “ChatGPT-like” workloads locally.

• Stable 24/7 performance for heavy compute labs or enterprise AI teams.

🖥️ Hardware Highlights

• CPU: AMD Threadripper Pro (up to 96 cores).

• Memory: Up to 2 TB DDR5 ECC (4800 MHz) across 8 channels.

• Motherboard: ASRock WRX90 WS EVO with 7× PCIe 5.0 x16 slots, M.2, SATA, MCIO.

• Storage: PCIe Gen5 NVMe SSDs + expansion options.

• Networking: Dual 10 Gb LAN, dedicated IPMI, optional InfiniBand 100 Gb/s.

• Chassis: Premium aluminum build, tempered glass panel, Titanium 1500W PSU.

🔌 Connectivity

• Front panel: 2× USB 3.0, 1× USB 3.1 Gen2 Type-C, audio jacks.

• Rear panel: USB4 Type-C, multiple USB 3.2, DisplayPort, S/PDIF, LAN, IPMI port.

📦 Delivery & Support

• Shipping: usually 3–7 business days.

• Warranty/Support: up to 5-year extended warranty, with enterprise-level support.

• ROI vs Cloud: BIZON claims ROI within 6 months compared to renting GPUs in the cloud, with up to 2× better performance.

🔑 Summary – BIZON ZX4000 (2× A100)

🚀 Why choose BIZON ZX4000 for AI?

• Extreme performance for LLM fine-tuning, vision models, and HPC AI workloads.

• Datacenter-class reliability in a desk-friendly workstation.

• Much quieter and cooler than typical rackmount servers.

• Faster ROI vs cloud GPU rentals if running continuous AI workloads.