The quad 5090 server rig

Four RTX 5090s: 128GB of VRAM and 7,168GB/s aggregate. The fastest token production per dollar in local AI.

TECHNICAL DIFFICULTY: 4 OF 4 · SERVER ROOM

How hard is this to assemble? four graphics cards, dual power supplies, ECC system memory, rack-grade parts: board-level assembly and a tuning afternoon

Four cards change what local AI can do: video generation at production quality, image pipelines that finish while you watch, and token rates no single box matches. It is also why the difficulty rating has a top level: two power supplies, a 2,400W draw, and tensor parallelism configured by hand. Setup day is a project, and the result is a small server that earns its shelf.

WHO THIS BUILD IS FOR

You have built machines before and you want the ceiling. Image and video generation at quality, batch inference for a team, and the satisfaction of a machine you assembled yourself.

ESTIMATED TOTAL

$27,180

prices refreshed weekly
last check: Oct 3, 2026

The parts

NVIDIA RTX 5090 32GB x4 32GB 1792GB/s nvidia

Four cards: 128GB VRAM total, 7,168GB/s aggregate. Dual PSU territory (2x 1,600W).

street price via Newegg, checked Oct 3

$27,180

What it runs

Ternary Bonsai 2 27B

6GB of ternary weights (1.76 bits per weight): this stack renders it faster than any single-GPU box on earth.

GLM-5.3-Flash

2-bit puts 80GB of weights across 128GB of VRAM with tensor parallelism: real context, four fans of noise.

Qwen3.8-Omni-Flash

4-bit is 62GB in 128GB: the omni model plus video generation headroom.

WHAT IT WILL NOT RUN

The 2.8T MoE class is still out of reach: 700GB of weights at 2-bit does not fit in 128GB of VRAM. Sustained 2,400W is a real line on the electricity bill at full duty.

POWER, NOISE, AND THE ROOM IT LIVES IN

Two power supplies, 2,400W at full load, and the sound of four cards working: this machine wants a dedicated circuit and a room with a door. Cable management is part of the build, and you will do it twice.