Skip to content
Llama Builds

High-end build · open-frame · Used parts

FJÄLLBO

AI workstation arranged on an IKEA table

Built by r/LocalLLaMA community member · Source: r/LocalLLaMA: 4x 3090 local AI workstation · Updated

Open-air AI rig built around a small white IKEA table, with MSI Suprim RTX 3090 cards on top and on the floor, the motherboard underneath, and several power supplies with thick cable bundles beside it.
Total cost
$6,486
VRAM
96GB
GPUs
4
System RAM
128GB

What can this build run?

With 96GB of VRAM across 4 GPUs, this build comfortably runs models up to Qwen3.5 122B-A10B (Q4_K_M, ~39 tokens/sec). Our top all-round pick for it is Qwen3.8 27B at Q8_0 (~21 tokens/sec).

Parts list

Every part in the FJÄLLBO

We may earn a commission when you buy through links on this page. It never changes what we recommend. How we make money

PartPriceBuy

GPU

4×NVIDIA GeForce RTX 3090 (used)

$3,400$850 eacheBay

CPU

AMD Ryzen Threadripper PRO 3955WX

$600Amazon

CPU Cooler

ARCTIC Liquid Freezer III

$89Amazon

Motherboard

ASUS Pro WRX80E-SAGE

$1,199Amazon

Memory

Remix Ram DDR4 128GB

$456Amazon

Storage

Samsung 980 Pro 2TB M.2-2280 NVMe SSD

$199Amazon

Case

IKEA FJÄLLBO table

$45

Power Supply

CORSAIR HX1500i 1500W

$698Amazon
Total$6,486

Listed prices from 2025; check current prices. The builder paid about $4,300 in total by buying everything used. Individual parts add up to $6,686.

Capability

Models this build runs well

Estimated for a single user with 8K context, with the model split across all GPUs (for example with llama.cpp). Best quantization that fits, ranked by our capability score.

  • Best overall · also coding, reasoning, vision

    Qwen3.8 27B

    Q8_0 · ~21 tokens/sec

  • Runner-up · also largest that fits

    Qwen3.5 122B-A10B

    Q4_K_M · ~39 tokens/sec

  • Fastest good model

    gpt-oss-20b

    MXFP4 · ~60 tokens/sec

ModelQuantSpeedFit
Qwen3.8 27BQ8_0~21 tok/sRuns well
Qwen3.5 122B-A10BQ4_K_M~39 tok/sRuns well
Qwen3.6 35B-A3BQ8_0~52 tok/sRuns well
Gemma 4 31BQ8_0~19 tok/sRuns well
gpt-oss-120bMXFP4~56 tok/sRuns well
Gemma 4 26B A4BQ8_0~48 tok/sRuns well
GLM-4.5-AirQ5_K_M~31 tok/sRuns well
gpt-oss-20bMXFP4~60 tok/sRuns well
Qwen3.5 9BQ8_0~48 tok/sRuns well
Gemma 4 E4BQ8_0~53 tok/sRuns well

The build

About this build

Four used RTX 3090s on an open IKEA table give this Threadripper PRO rig 96GB of VRAM for running 70B-class models locally. The builder bought every part on the used market for about $4,300.

Why this build

I bought everything on the used market, about $4,300 in total, and got 96GB of VRAM. I’m currently considering picking up two more 3090s and maybe one 5090, but I think the current price of 3090s makes them a great deal for building a local AI workstation.

Notes and caveats

  • The $4,300 figure is what the builder actually paid for used parts. The parts list totals $6,486 at the prices we listed when we added the build.
  • The “case” is an IKEA FJÄLLBO table, so everything runs open-air.

Source

Originally shared on r/LocalLLaMA: 4x 3090 local AI workstation.

Specifications

Full specs

GPU
4× RTX 3090
CPU
AMD Ryzen Threadripper PRO 3955WX
Motherboard
ASUS Pro WRX80E-SAGE
Memory
128GB DDR4 (Remix Ram)
Storage
Samsung 980 Pro 2TB NVMe SSD
Power supply
Corsair HX1500i 1500W
Case
IKEA FJÄLLBO table (open air)
Cooling
ARCTIC Liquid Freezer III
Form factor
open-frame
GPU power
1,400W rated

Keep browsing

Similar builds