RTX PRO 5500 vs RTX PRO 6000 Max-Q: 84 GB at 600 W or 96 GB at 300 W

RTX PRO 5500 vs RTX PRO 6000 Max-Q: memory, bandwidth and power

In the RTX PRO 5500 vs RTX PRO 6000 Max-Q comparison, the specifications NVIDIA publishes as of 16 October 2026 put the RTX PRO 6000 Blackwell Max-Q ahead of the RTX PRO 5500 Blackwell on memory, bandwidth, video engines and MIG. It has 96 GB of GDDR7 against 84 GB and 1,792 GB/s against 1,398 GB/s, four video encoders against three and four MIG instances against two, at a board power of 300 W against up to 600 W. The 5500 offers twice the power budget and a design for rack-mounted workstations, but NVIDIA has not yet published the compute figures that would show what the extra 300 W buys.

For language models that settles the choice now, because memory capacity and bandwidth decide which model fits and how fast it generates. For rendering, which depends more on compute, the comparison stays open until NVIDIA publishes clocks and TFLOPS for the 5500; simulation and CAE solvers limited by memory bandwidth favour the Max-Q already. Our RTX PRO 5500 overview covers the card’s launch status and its place against the RTX PRO 5000.

RTX PRO 5500 specs NVIDIA publishes as of October 2026

NVIDIA’s RTX PRO 5500 page has been online since early September 2026. On 16 October 2026 it still shows “Coming Soon” with a “Notify Me” sign-up and the line “Preliminary product specifications, subject to change.” NVIDIA’s product literature page lists datasheets for the RTX PRO 6000, 5000, 4500, 4000, 4000 SFF and 2000, and none for the 5500. The Max-Q has a full datasheet, and its product page carries a “Buy Now” button.

NVIDIA RTX PRO 5500 and RTX PRO 6000 Max-Q product pages and NVIDIA’s RTX PRO desktop GPU overview, read 16 October 2026; Max-Q datasheet 5349650 (June 2026); NVIDIA vGPU supported-GPU list, updated 2 October 2026.

NVIDIA has not yet published the 5500’s memory bus width or its FP32 TFLOPS. Figures for both circulate in partner listings and press reports, and we leave them out until NVIDIA confirms them. NVIDIA describes the board as dual slot at 4.4 inches high and 11.1 inches long, 0.6 inches longer than the Max-Q. Its footnote says the “Liquid-cooled solution is available in the RXM form factor”, a term NVIDIA does not define. NVIDIA’s CUDA GPU list, read on 16 October 2026, places both cards under compute capability 12.0, so CUDA code compiled for one also targets the other once an NVIDIA driver release lists the 5500 as supported.

LLM inference: 84 or 96 GB and the bandwidth gap

Token generation reads the model’s weights once per token, so on a model that fits both cards the rate follows memory bandwidth. Llama 3.3 70B in FP8 reads about 70.6 GB per token. That puts the arithmetic ceiling for one user at about 25 tokens per second on the Max-Q and about 20 on the 5500, a gap of 28 per cent. Our GPU memory bandwidth comparison sets both cards against the rest of the range.

Capacity decides how many conversations fit next to the weights. We size it with the rule of our users-per-card guide: 90 per cent of the memory the driver reports, less 3 GiB for the runtime, less the weights, with an FP8 cache of 1.25 GiB for one 8K conversation of the 70B model. The driver reports 95.6 GiB on a 96 GB card, and for the 84 GB card we scale that in proportion, since no driver figure for it is published yet.

In FP8, at 67.7 GiB of weights, Llama 3.3 70B leaves about 15 GiB of cache on the Max-Q, enough for twelve 8K conversations, and about 4.6 GiB on the 5500, enough for three. In NVIDIA’s NVFP4 checkpoint, 39.8 GiB, the counts rise to about thirty-four and twenty-five. gpt-oss-120b, at 60.8 GiB, leaves about 22 GiB on the Max-Q and about 11 GiB on the 5500. These figures are our arithmetic from published specifications, not measurements, and production servers keep more in reserve.

Fine-tuning follows the same order. Gradients and optimiser states sit in memory beside the weights, so the 12 GB more on the Max-Q decides the largest model or batch that fits on one card.

Rendering, simulation and CAE: what the 600 W may add

Path-traced rendering depends mainly on shader and RT Core throughput once the scene fits in memory, and there the 5500’s 600 W budget could pay off. Simulation codes vary, and many GPU CFD and implicit finite-element solvers are limited by memory bandwidth as much as by FP32 throughput, and on those the Max-Q’s 28 per cent bandwidth lead applies. The Max-Q runs its 24,064 CUDA cores at 300 W, and NVIDIA rates it at 110 TFLOPS of FP32 and 333 TFLOPS of RT Core performance at its boost clock. For the 5500 NVIDIA states neither a core count nor a clock, so whether its higher power limit turns into higher sustained throughput than the Max-Q cannot be read from NVIDIA’s figures. We found no independent rendering or simulation test of the 5500 as of 16 October 2026.

Memory still sets the ceiling for scene and mesh size, and there the Max-Q has 12 GB more. Video work points the same way, since the Max-Q carries four NVENC and four NVDEC engines and the 5500 three of each. A studio or engineering team that needs the 5500 for compute should wait for NVIDIA’s datasheet and the first published tests before it orders several cards.

We supply both cards. Tell us which models, scenes or solvers the cards will run and how many people use them, and we compare the two for your workload in the quote.

MIG, vGPU and sharing cards in a team

Both cards split into isolated MIG instances, with different granularity. The Max-Q datasheet lists up to four instances of 24 GB, two of 48 GB or one of 96 GB, and NVIDIA’s MIG user guide, updated on 13 October 2026, lists the Max-Q with four. For the 5500, NVIDIA’s product page gives “one instance with up to 84 GB, or two instances with up to 42 GB each”. The 5500 is not in the MIG user guide yet, so its profile names and its driver and vBIOS prerequisites are not published.

A 42 GB instance holds a 32B model in FP8, at 32 GiB of weights, with some room for cache, and a 48 GB Max-Q instance holds the same model with more. A 24 GB Max-Q instance takes a 14B model in FP8 for a developer who needs a GPU of their own. On the Max-Q, MIG runs on Linux after the card is switched to compute display mode, as our edition comparison of the RTX PRO 6000 describes.

Neither card is on NVIDIA’s vGPU supported-GPU list, updated on 2 October 2026. MIG instances on either card therefore serve processes and containers on one Linux host. Virtual desktops with a shared GPU need vGPU, which among the RTX PRO 6000 editions only the Server Edition supports.

Four cards in one system: power, heat and chassis

The RTX PRO 5500 is built, in NVIDIA’s words, “for rack-mounted workstation deployment”, where “IT teams can centralize GPUs into managed racks, share them across users, and scale capacity as demand grows”. The Max-Q is built for density under a desk, and NVIDIA states that it “enables up to four GPUs in a single system”, with “up to 384 GB of combined memory across a four-GPU configuration”.

Card figures from NVIDIA’s product pages and the Max-Q datasheet (16 October 2026); wall power is our estimate with the same margin as our four-card Max-Q article, not a measurement.

Four Max-Q cards and a 350 W processor stay on one 16 A circuit at 230 V, which carries 3,680 W, and towers from several makers list that configuration, as our four-card Max-Q workstation guide shows. Four 5500 cards at up to 600 W each take about 15 A at 230 V at the top of our estimate, close to the 16 A of such a circuit and above the 80 per cent of a feed that we plan with. That load belongs on a rack position with a 32 A or three-phase feed, with C19 outlets (16 A) wherever one power supply draws more than the 10 A a C13 outlet carries. The heat comes to about 11,000 to 12,000 BTU per hour, which belongs in a server room.

In the makers’ specifications that our four-card article collects, no tower lists more than two 600 W cards. As of 16 October 2026 we found no workstation or server maker’s specification that lists the RTX PRO 5500, so the number of 5500 cards per chassis is a question for the system maker once it qualifies the card.

Take a team of 16 people in engineering and data science who share GPUs from one machine. Four Max-Q cards in one tower give each person a 24 GB instance, or eight people a 48 GB instance each, on an office circuit. Four 5500 cards in a rack-mounted workstation give eight people a 42 GB instance each and move about 3.5 kW of load and heat into the server room. For a team of that size the Max-Q build serves twice as many people with smaller instances, or the same eight people with 48 GB each, at half the card power and on an office circuit.

We check the rack, power and airflow before we quote. Send us the chassis, the feed and the inlet temperature of the rack position, and we say which of the two builds it carries.

Which card for which workload

Our reading of NVIDIA’s published specifications as of 16 October 2026 and the arithmetic in this article.

The 5500 sits between the RTX PRO 5000 and the 6000 in memory, and our comparison of the RTX PRO 6000, 5000 and 4500 shows which model class fits each memory size. If your models fit in 84 GB and your system maker designs its rack-mounted workstations around the 5500, the card is worth evaluating once NVIDIA publishes its full datasheet. For the other workloads in the table, the Max-Q is the card NVIDIA has fully specified today.

What we supply

We supply the RTX PRO 5500 and the RTX PRO 6000 in all three editions, Workstation, Max-Q and Server Edition, on one EU contract and invoice with manufacturer warranty; the RTX PRO 6000 product page compares its three editions, and our professional GPU range covers the rest of the NVIDIA cards we supply. We also build GPU workstations and AI servers to order around them, sized to the workload, assembled and burn-in tested. Where a rack workstation needs virtual desktops instead, we put the Server Edition and the vGPU licences in the same quote.

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