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Supermicro / Gigabyte / ExxactRTX PRO GPU SystemsDatacentre tier · POA · £60k – £300k+

RTX PRO 6000 Server (4×–8×)

384–768 GB of VRAM in a rack — passive Server Edition cards, colocation power, and every open model on the list.

Price

POA

Component maths: 4× ≈ £55–75k · 8× ≈ £110–150k+ ex VAT — all vendors quote-led

verified 2026-07 · supply & lease options in every proposal

NVIDIA RTX PRO server — exploded render of an 8-GPU 4U MGX chassisSupermicro / Gigabyte / Exxact
384–768 GB
Total VRAM

4× to 8× Server Edition

1.79 TB/s
Per-card bandwidth

14.3 TB/s aggregate at 8×

5–6.5 kW
8-GPU draw

colocation territory

POA
Pricing

~£55k (4×) to £150k+ (8×)

The machine

Past two GPUs, the platform moves to the passive-cooled Server Edition in rack chassis: Supermicro (20+ system configurations), Gigabyte's MGX 4U (8× GPU + BlueField-3, PCIe Gen6) and Exxact (to 10×). Four cards give 384 GB — GLM-5.2 territory at 4-bit; eight give 768 GB, which serves Kimi K2.6's full INT4 checkpoint or, often smarter, N independent replicas of a 120B model for maximum aggregate throughput.

Pricing is quote-led: component maths puts 4× builds around £55–75k and 8× at £110–150k+ ex VAT (the one public 8× sticker, $346k at a reseller, looks heavily marked up — negotiate from components). An 8-GPU box draws 5–6.5 kW at 75 dB+: this is colocation or comms-room territory, and we scope hosting as part of the engagement.

vs its siblings: The scale tier — engineered per engagement, hosted where it belongs.

Memory, to scale

768 GB model-visible · bandwidth is the speed limit

8× GDDR7 ECC (per card)

96 GB · 1.79 TB/s each

GDDR7

For scale

DGX Spark — 128 GB @ 273 GB/s

Mac Studio M3 Ultra — 512 GB @ 819 GB/s

DGX Station GB300 — 748 GB coherent

Capability

What it actually runs

Declared from research and benchmarks, not computed marketing — tokens-per-second figures are cited where a real measurement exists.

  • Kimi K2.6 (1T)INT4fits594 GB on the 8× build
  • GLM-5.24-bitwith headroomfrom the 4× build
  • Qwen3.5 397BFP8with headroom8× build, full quality
  • DeepSeek V4 Flashnativewith headroomwith datacentre-grade concurrency
  • N× gpt-oss-120b replicasMXFP4with headroomoften the best £/token play
Specification

The full sheet

Systems

Supermicro
SYS-522GA-NRT 5U — to 8× SE, dual Xeon/EPYC, 2 TB DDR5
Gigabyte
XL44-SX2-AAS1 4U MGX — 8× SE + BlueField-3, 400 Gb networking
Exxact
TS4 4U platforms — to 10× SE

Capability

384 GB (4×)
GLM-5.2 at 4-bit · DeepSeek 671B-class at Q3 · V4 Flash with huge concurrency
768 GB (8×)
Kimi K2.6 INT4 whole · or N× 120B replicas for max throughput
Alternative
H200 NVL (141 GB @ 4.8 TB/s, NVLink) for >100-user concurrency — $28–35k/card

Hosting

Power/noise
Passive cards, chassis airflow, 75 dB+ — never office-hostable
Options
UK colocation, comms room with dedicated circuit, or Scan's hosted 3XS cloud

Where it shines

  • Every open model on this page, at production concurrency
  • Replica serving: 8 independent 120B instances beats one giant model for many fleets
  • Standard x86 servers — familiar ops, familiar procurement

The trade-offs

  • Colocation or serious comms-room infrastructure required
  • Quote-led pricing in a volatile market — validity windows are short
  • No NVLink pooling on this card class — biggest single models prefer GB300/H200 silicon

Buy this box for

Whole-business inference behind the MCP boundaryMulti-model serving: triage + drafting + coding tiers on one boxOrganisations consolidating from per-token APIs at scale
The platform

Understanding RTX PRO GPU Systems

NVIDIA RTX PRO 6000 Blackwell · 96 GB GDDR7

Where unified-memory boxes optimise for capacity, the RTX PRO 6000 Blackwell optimises for speed: 1.79 TB/s of memory bandwidth is 6–7× a DGX Spark. A single card serves gpt-oss-120b at ~150 tok/s for one user — or thousands of tokens per second aggregate under vLLM batching. This is the silicon for department-scale production serving on 120B-class models, and the pragmatic fine-tuning platform: QLoRA up to 120B fits on one card, with full CUDA, vLLM, SGLang and TensorRT-LLM support.

Two cards give 192 GB — notably, enough to serve DeepSeek V4 Flash's native FP4/FP8 checkpoint, the most capable open model that fits a workstation. Four give 384 GB; beyond that the passive Server Edition scales to 8 GPUs in a rack chassis for colocation. UK-built systems come from Scan's 3XS line with local warranty and support.

Buyers should know the market context: the GDDR7 shortage pushed the card from its $8,565 launch MSRP to ~$13,250 (+55%) by mid-2026 — about £11,300 inc VAT in the UK — and no successor exists or is announced. The Max-Q variant (300 W) sacrifices ~13% compute for half the power and heat, and since LLM decode is bandwidth-bound, its single-stream speed is nearly identical — it is the card of choice for dense multi-GPU builds.

Sources & verification

Specifications and prices verified 2026-07 against the sources below. The memory shortage is repricing this market monthly — we re-verify at quote.

Compare against the rest of the catalogue, or have us spec it against your workloads.

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Make it real

Spec the RTX PRO 6000 Server (4×–8×) for your workload

We'll size it against your real token volumes, quote supply and lease options, and stand up the models with evals that prove they do the job — or tell you honestly that a different box (or the API) wins.