Can You Put Four RTX PRO 6000 Max-Q Cards in One Workstation?

Bottom Line

• Yes, and NVIDIA says so directly. The Max-Q datasheet (document 3519233) states you can scale up to four RTX PRO 6000 Max-Q GPUs.
• Four cards = 384GB GDDR7 with ECC, 96,256 CUDA cores, 1,200W of GPU.
• 1,200W of GPU does not fit a 15A circuit. With a workstation CPU the machine pulls roughly 1,720–1,830W at the wall. A 15A circuit tops out at 1,440W continuous. You need a 20A circuit.
• Four Workstation Editions are not a home build at all. 2,400W of GPU alone, past 2,900W at the wall — that is a 240V or datacentre conversation.
• The datasheet lists no NVLink. Four cards talk over PCIe 5.0 x16. Plan the software around that.
• MIG multiplies it further: each card splits into 4x24GB, so four cards give 16 isolated 24GB instances.

What NVIDIA Actually Says

Every card-side figure below is from NVIDIA’s own RTX PRO 6000 Blackwell Max-Q Workstation Edition datasheet, document 3519233. None of it is a review estimate.

The scaling claim is in the datasheet’s own body text, not inferred: it describes scaling up to four RTX PRO 6000 Max-Q GPUs to fine-tune LLMs and run local AI assistants. This is a supported configuration, not a hack.

Note what is absent. There is no NVLink row. The system interface is PCIe 5.0 x16 and nothing else. Anyone planning a four-card tensor-parallel deployment should design for PCIe bandwidth between cards — see is NVLink worth it for local LLMs, where the measured tensor-parallel benefit of a fast link drops to roughly 10% at four GPUs anyway.

The Circuit Is the Real Constraint

This is the section other 384GB build guides skip, and it is the one that decides whether the machine turns on.

North American residential and office branch circuits follow an 80% continuous-load convention — a load running more than three hours may use no more than 80% of the breaker rating. A local AI workstation running inference around the clock is a continuous load by any reading.

Now add up the machine:

So four Max-Q cards do not fit a 15A circuit. They fit a 20A circuit, and they fill most of it — you should not share that circuit with anything else, and a dedicated run is the right answer.

We want to be precise about this, because our own Max-Q vs Workstation Edition comparison makes the point that four Workstation Editions exceed a 15A circuit. That is true. What we are adding here is that four Max-Q cards exceed it too, once the platform is counted. The Max-Q makes a four-card build possible; it does not make it fit an ordinary outlet.

And four Workstation Editions? 2,400W of GPU, roughly 2,900–3,100W at the wall. That is past the continuous limit of a 20A 120V circuit as well. Four of those cards is a 240V installation or a rack, not a room.

Consult an electrician before you commit. The figures above are the standard convention; your local code, your breaker panel and your existing wiring are the actual authority.

Heat, Which Is the Same Problem Wearing a Coat

Every watt that goes in comes back out as heat. At 1,600W of continuous system draw, that is about 5,460 BTU/hr — a space heater on its high setting, running permanently, in whatever room the machine lives in.

Air conditioning that away costs additional electricity on top of the machine. At the US average of $0.18/kWh as of August 2026, 1,600W running 24/7 is about 1,168 kWh a month, roughly $210 a month in electricity alone before any cooling. Our electricity cost break-even page works through what that does to a rent-versus-buy comparison.

This is the honest reason four-GPU home workstations are rarer than the build charts suggest. The cards are the easy part.

Slots, Lanes and the Platform

Lanes. Four cards at PCIe 5.0 x16 is 64 lanes. No consumer AM5 or LGA1851 platform comes close — those give you roughly 24 usable lanes. You need Threadripper PRO or Xeon W class silicon, which is where the platform cost stops being a rounding error. Our motherboard and CPU guide for multi-GPU rigs covers the tiers.

You can run cards at x8 to fit a smaller platform. For inference this costs less than people fear, because weights load once and stay resident. For training and for tensor-parallel serving it costs more. Decide by workload, not by reflex.

Slots. Four dual-slot cards occupy eight slot widths. Most workstation boards expose seven expansion slots. Check the specific board’s slot spacing and the specific chassis’ slot count before ordering four cards — this is a measurement, not an assumption, and it is the most common way a quad build goes wrong on paper.

Airflow. The Max-Q uses an active blower that exhausts out the bracket, which is exactly the right cooler for stacked cards; it does not dump 300W into the neighbouring card’s intake the way an open-fan design does. Four blowers under sustained load are, however, loud. Nobody sits next to this machine.

What 384GB Actually Runs

Using our own published model footprints, kept consistent across the site:

The interesting capability at 384GB is not the biggest single model. It is that the KV cache stops being the binding constraint. A dense 70B needs exactly 40 GiB of FP16 cache for a full 128K window — a number that dominates a 48GB card and disappears on this machine.

And MIG changes the shape of the answer again. Each Max-Q splits into up to four isolated 24GB instances. Four cards is up to 16 isolated 24GB instances, each with its own resources. For a team serving many small models, or for hard isolation between users, that is a genuinely different product from “one big pool of VRAM” — and it is the reason to buy this over a single 96GB card beyond raw capacity.

What to Buy

The Max-Q is the card this build wants, and we have no affiliate link for it. We will not substitute a different card to fill the gap. Buy it from a workstation vendor or a PNY reseller, and use the identification tell: 300W means Max-Q, 600W means Workstation Edition. Listings routinely omit the variant from the title. Check the wattage, not the name.

If you are buying one 96GB card rather than four, the Workstation Edition is the variant we can point you at:

NVIDIA RTX PRO 6000 Blackwell 96GB — the 600W Workstation Edition. Correct for a single-card build in a large chassis. Not the variant to buy four of, for every reason above.

Buying it built is a defensible choice here. At four cards the platform, the chassis, the power delivery and the thermal design stop being commodity decisions, and a vendor that has validated the combination is worth money:

Threadripper PRO 9995WX workstation with RTX PRO 6000, 384GB system RAM and 4TB Gen5 — a validated single-GPU workstation platform with the lane count and power delivery a multi-card path needs. See prebuilt AI workstation vs DIY for how that trade actually prices out.

On price: NVIDIA lists the Workstation Edition at $13,250 as of August 2026, up from a $8,565 launch price. Max-Q street pricing is not consistently tracked; a single PNY listing was seen near $8,300, which is one retail sighting and not a street price. We are not going to multiply an unverified number by four and call it a budget. Get current quotes before you plan this build.

The Decision

See Also

• RTX PRO 6000 Max-Q vs Workstation Edition — the datasheet-by-datasheet delta between the two variants
• Is 48GB of VRAM Enough in 2026? — the tier most people should actually buy
• Motherboard and CPU for a Multi-GPU LLM Rig — where 64 PCIe lanes come from
• What PSU for a Local AI Rig — sizing supply before you size cards
• Is NVLink Worth It for Local LLMs? — why the missing NVLink row matters less than it looks
• Local LLM Electricity Cost and Break-Even — what 1,600W continuous costs per month
• Prebuilt AI Workstation vs DIY — when a validated build is worth the premium
• Can You Run Kimi K3 Locally? — the model 384GB still cannot hold

Sources

• NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition datasheet, document 3519233 — all per-card specifications, the MIG instance types, and the four-GPU scaling statement
• NVIDIA RTX PRO 6000 Blackwell Workstation Edition datasheet, document 5349469 — the 600W figure used for comparison
• Four-card totals, wall-draw estimates and BTU figures are our own arithmetic on those published specifications, not measurements
• The 80% continuous-load limit is the standard North American branch-circuit convention; confirm against local code with an electrician
• Electricity at $0.18/kWh (US average, August 2026; EIA-derived) from our hardware price reference
• Model footprints are our own published figures from can you run Kimi K3 locally, kept consistent across the site
• Pricing: NVIDIA list price $13,250 for the Workstation Edition as of August 2026 (VideoCardz, wccftech). Max-Q street pricing is deliberately not quoted as a figure.