shop_ai_universal_workstation.png
shop_ai_universal_workstation.png

Zen Universal AI Workstation — "Built for More"

$50,000.00

Starting at $50,000 — the one system built to run essentially every practical open-weight AI model available in 2026, including frontier-scale models most workstations can't touch.

What it runs

  • DeepSeek V4-Flash at native precision (~170–175GB) — dual RTX PRO 6000 Blackwell is a named qualifying configuration for this model
  • Llama 4 Maverick at Q2_K (~116GB) and near-Q4 with RAM offload
  • gpt-oss-120b, Llama 4 Scout at Q8, and DeepSeek V4-Pro at 4-bit — all comfortably inside 192GB of VRAM
  • Kimi K2.6 / K2 Thinking at low-bit quantization (192GB VRAM + 512GB RAM clears the ~247GB+ combined memory requirement)
  • Every image and video model at full precision, including FLUX.2 dev FP16 and Wan 2.2 FP16 at 720p

Core specs

  • 2x NVIDIA RTX PRO 6000 Blackwell 96GB (192GB combined VRAM)
  • AMD Threadripper PRO 9975WX
  • 512GB DDR5 RDIMM memory (8-channel)
  • 2x 8TB NVMe model vault (16TB) + 2TB NVMe OS drive
  • WRX90 platform, high-wattage power supply, full custom liquid cooling loop

A lower-cost quad-consumer-GPU alternative (4x RTX 5090, 128GB VRAM) is available as the \"Universal AI Workstation — Quad Consumer Edition\" for customers who want to trade some model headroom for a lower price point.

Best for: organizations that need on-prem access to frontier-scale open models without exception — the honest ceiling of what a workstation (not a server cluster) can run.

Hardware requirement research: LushBinary, Unsloth, TensorRigs. Pricing subject to current GPU/memory market conditions — final quote confirmed at order.

Starting at $50,000 — the one system built to run essentially every practical open-weight AI model available in 2026, including frontier-scale models most workstations can't touch.

What it runs

  • DeepSeek V4-Flash at native precision (~170–175GB) — dual RTX PRO 6000 Blackwell is a named qualifying configuration for this model
  • Llama 4 Maverick at Q2_K (~116GB) and near-Q4 with RAM offload
  • gpt-oss-120b, Llama 4 Scout at Q8, and DeepSeek V4-Pro at 4-bit — all comfortably inside 192GB of VRAM
  • Kimi K2.6 / K2 Thinking at low-bit quantization (192GB VRAM + 512GB RAM clears the ~247GB+ combined memory requirement)
  • Every image and video model at full precision, including FLUX.2 dev FP16 and Wan 2.2 FP16 at 720p

Core specs

  • 2x NVIDIA RTX PRO 6000 Blackwell 96GB (192GB combined VRAM)
  • AMD Threadripper PRO 9975WX
  • 512GB DDR5 RDIMM memory (8-channel)
  • 2x 8TB NVMe model vault (16TB) + 2TB NVMe OS drive
  • WRX90 platform, high-wattage power supply, full custom liquid cooling loop

A lower-cost quad-consumer-GPU alternative (4x RTX 5090, 128GB VRAM) is available as the \"Universal AI Workstation — Quad Consumer Edition\" for customers who want to trade some model headroom for a lower price point.

Best for: organizations that need on-prem access to frontier-scale open models without exception — the honest ceiling of what a workstation (not a server cluster) can run.

Hardware requirement research: LushBinary, Unsloth, TensorRigs. Pricing subject to current GPU/memory market conditions — final quote confirmed at order.