Autonomous Computer

From

€22,889.70

Autonomous Computer

Personal AI data center, on your desk. 2 GPUs.

BuildBuild: Complete machine · 2× RTX 5090

Complete machine · 2× RTX 5090

VRAM · 64 GB

FP32 · 210 TFLOPS

Case · CNC aluminum, black

Risers · 2× PCIe 5.0 ×16

Board · ASUS W790E-SAGE SE

CPU · Intel Xeon w5-3423

Power · 2000W, 12V-2x6

Cooling · 6 fans

Complete machine · 2× RTX PRO 6000

DIY kit · Case and PCIe 5.0 risers

Memory

64 GB

128 GB

192 GB

256 GB

Storage

1 TB

2 TB

4 TB

8 TB

Buy more, save more

Qty	Price
3-4	€22,203
5-9	€21,744
10-29	€21,516
30+	€21,288

€22,889.70

Free shipping within 2-4 weeks

Autonomous Computer

Free shipping within 2-4 weeks

€22,889.70

Own your intelligence.

Never revoked.

Your models don't get deprecated, rate-limited, or pulled. The weights sit on your disk.

Private by physics.

Prompts never leave the building. Nobody trains on your work. Not by policy, by physics.

No per-token bill.

Own the machine and agents can run around the clock. You pay for electricity, not tokens.

Yours to keep.

Fine-tune on what only you know. The model becomes an asset you own, and it sells with the company.

GPUs

Two cards, tuned and burn-tested. We install RTX 5090 or RTX PRO 6000 Blackwell— installed, driver-loaded, and benchmarked as one system before it ships. Plug it in and run.

64–192GB

Total VRAM

210–252TFLOPS

FP32

3,584GB/s

Memory bandwidth

Chassis

Milled from solid aluminum. Not a bent-steel box — a billet, milled inside and out until only the machine is left. It moves heat like a heatsink; the triangular cutouts keep it stiff without dead weight. 12.5 × 12.5 × 16 inch, anodized black.

33lb

Weight

CNC

Solid aluminum

Riser

A full ×16 to every card. Each GPU reaches the board over its own server-grade PCIe 5.0 riser — shielded, custom-cut, no dropped lanes. Every power run is cut to length and sleeved by hand.

x16

Lanes per card

64GB/s

Per card

Gen 5

PCIe

Motherboard

ASUS Pro WS W790E-SAGE SE. The hardest choice in a multi-GPU build, solved with a workstation board: every card gets a full ×16, and the BIOS ships pre-tuned so every card links at full width.

PCIe 5.0 ×16 slots

DDR5 channels

W790

Chipset

CPU

Intel Xeon w5-3423. The lanes are the point: 112 lanes of PCIe 5.0 means both cards, the NVMe, and the risers never fight for bandwidth.

112

PCIe 5.0 lanes

Cores

4677

Socket

Power

2000W that doesn't flinch. Under full load the box pulls up to 1600W — and cheap power is where multi-GPU builds die. We spec 2000W with native 12V-2x6, feeding clean power to every card. The result is boring: it just runs.

2000W

Power supply

1600W

Max draw

120V

Standard outlet

Cooling

Air moved on purpose. Six fans on a single controller, mapped to the airflow path before a panel was cut — not bolted on after.

Memory & Storage

ECC memory, fast NVMe. Error-correcting memory catches the silent bit-flip before it corrupts the job you left running overnight. The NVMe loads a 70B checkpoint in seconds, not minutes. Need more? Configure up to 256GB RAM and 8TB Gen5 NVMe.

128GB

ECC RAM

2TB

NVMe

7GB/s

Read

Performance

Concurrent usersPer-user generationTotal tok/sTTFT (s)

4 users76.8Total tok/s840TTFT (s)0.64 s

8 users72.1Total tok/s1,488TTFT (s)1.15 s

16 users64Total tok/s2,390TTFT (s)2.27 s

24 users52Total tok/s3,004TTFT (s)2.41 s

How big is your team?

vLLM • FP8 weights + KV • 1K prompt • 512 output

Qwen3.6-27B, per user (tok/s)

Grey: Mac Studio M3 Ultra single user, published run. Blue: this box on vLLM FP8, per user while serving 4 and 24 users at once.

Mac Studio M3 Ultra 512GB, 1 user (MLX 4-bit)

Mac Studio M3 Ultra, 1 user, best tuned build (MTPLX v2)

2x RTX 5090, EACH of 4 users (this box)

2x RTX 5090, EACH of 24 users (this box)

Source:Community benchmark

What Qwen3.6-27B gets done in one hour.

Runs these models

Language6

Qwen3.6 27B
Qwen3.6 35B A3B
Gemma-4 31B
Gemma-4 26B A4B
Laguna-S 2.14-bit GGUF
Laguna-XS 2.1

Image3

Qwen Image 2512
Qwen Image Editing 2511
FLUX.2-dev

Video2

Wan 2.2
MiniMax H3

Quantized builds noted per model. What fits depends on context length and KV cache.

GPU

Cards

2x NVIDIA RTX 5090 or 2x NVIDIA RTX PRO 6000 Blackwell

Total VRAM

64 GB (RTX 5090) / 192 GB (RTX PRO 6000)

FP32 compute

210 TFLOPS (RTX 5090) / 252 TFLOPS (RTX PRO 6000)

Interconnect

PCIe 5.0 x16 per card, Gen5 riser cables

Compute

CPU

Intel Xeon w5-3423 - 12 cores, 112 PCIe 5.0 lanes

Motherboard

ASUS Pro WS W790E-SAGE SE - 7x PCIe 5.0 x16

CPU cooler

Heatsink 4677-2UAF8

Memory & storage

RAM

128 GB (4x 32GB DDR5-4800 ECC) - configurable 64-256 GB

Storage

2TB NVMe PCIe 4.0 - configurable 1-8TB, Gen5 on 8TB

Power & cooling

Power supply

Open-source hardware

The whole machine
is open.

Every CAD file, bill of materials, and BIOS setting — free on GitHub. Fork it, change it, build your own, even sell it. This is how the personal computer began: in the open. We’re doing it again, for AI hardware.

GitHub 1.2k

autonomous-ai / autonomous-computer

2x-5090/ 4x-5090/ 8x-5090/ 4x-6000/

bom/ step_models/ stl-models/ photos/

README.md setup.md

MIT · 147 forks

Clone it. Build it. Sell it. We just want it built.

Autonomous Computer

Personal AI data center, on your desk. 2 GPUs.