NVIDIA RTX PRO 6000 Blackwell alternatives: which 48, 32 and 24 GB cards do which job

RTX PRO 6000 alternatives from 24 to 48 GB in one table

The cards in our range that do the same kind of work as an NVIDIA RTX PRO 6000 Blackwell are the NVIDIA RTX PRO 5000 Blackwell with 48 GB, the NVIDIA RTX PRO 4500 Blackwell with 32 GB as Workstation Edition and as passive Server Edition, the NVIDIA RTX 5000 Ada Generation with 32 GB and the single-slot NVIDIA RTX PRO 4000 Blackwell with 24 GB. By our sizing rule they hold 40.0, 25.7 and 18.5 GiB of model weights and cache per card, against 83.0 GiB on the 96 GB card. Which of them is an alternative depends on the largest model or scene that has to sit on one card: Llama 3.3 70B in FP8, with 67.7 GiB of weights, fits one 96 GB card and none of these five.

The RTX PRO 6000 comes in three editions with 96 GB each: the Workstation Edition at 600 W, the Max-Q at 300 W and the passive Server Edition at up to 600 W. Their figures are collected in our RTX PRO 6000 Blackwell specs. This page sorts the five smaller cards by the job they do and marks where the line to the 96 GB card runs.

NVIDIA datasheets 5349550 (RTX PRO 5000, June 2026), 5108623 (RTX PRO 4500 Workstation Edition, April 2026), 5192801 (RTX PRO 4500 Server Edition, April 2026), 2898211 (RTX 5000 Ada, August 2023) and 5323450 (RTX PRO 4000, June 2026); RTX PRO 6000 from NVIDIA's datasheets as collected in our specs article. Every card in the table has memory with ECC.

Four of the five are Blackwell cards on PCIe 5.0 x16 whose Tensor Cores support FP4 and FP8; NVIDIA's CUDA page of 16 October 2026 gives them compute capability 12.0. The RTX 5000 Ada is an Ada Lovelace card on PCIe 4.0 x16 with compute capability 8.9, which covers FP8 and no FP4.

Which card does which job

Budgets by our sizing rule and model sizes as in the sections below; vGPU from NVIDIA's supported-GPU list of 2 October 2026; encoders from NVIDIA's datasheets and its Video Encode and Decode GPU Support Matrix of 16 October 2026.

The first row is the line. Where it applies, the 96 GB card is the answer. Where it does not, the other rows name a card with less memory, 145 to 300 W of board power and, for two of the five, a single slot.

We supply all five cards across the EU; send us your largest model or scene and the systems the cards go into, and we reply with a written quote within one business day.

Where one 96 GB card has no substitute

Our sizing rule takes 0.9 times the memory the driver reports and subtracts 3 GiB per card; what remains is the budget for weights plus KV cache. The driver shows 95.6 GiB on the 96 GB card, which gives 83.0 GiB. For the smaller cards we scale the reported memory from that figure in proportion to capacity. That scaling is an assumption, and the driver on the delivered card decides. The derivation is in our guide to how many users one RTX PRO 6000 serves.

A model with more than 40 GiB of weights stays on the large card. Llama 3.3 70B in NVIDIA's FP8 checkpoint has 67.7 GiB of weights. On a 96 GB card that leaves 15.3 GiB, by our estimate room for 12 conversations of 8,192 tokens with an FP8 KV cache at 1.25 GiB each. gpt-oss-120b has 60.8 GiB of weights and leaves 22.2 GiB. Either file is larger than the whole memory of a 48 GB card.

The same holds for a render scene that needs more than 48 GB on one GPU, and for a chassis that has to carry the most memory in two slot widths: by our division a 96 GB card brings 48 GB per slot width, the RTX PRO 4500 Server Edition 32 GB and the RTX PRO 4000 24 GB. Between 48 and 96 GB we also supply the RTX PRO 5000 with 72 GB and the RTX PRO 5500 with 84 GB, with budgets of 61.5 and 72.3 GiB by the same rule; they are outside this comparison.

What a 48 GB, 32 GB or 24 GB card holds by our sizing rule

The table lists publishers' own model files with their sizes on Hugging Face, read 10 November 2026. A file within the budget fits, and the difference is room for context. A file larger than the budget and no larger than 0.9 times the card's memory is above our budget, and we do not plan on it. A file larger than 0.9 times the card's memory does not fit.

File sizes of the publishers' own files on Hugging Face, read 10 November 2026; classes by our sizing rule, not a measurement. Every file that fits a smaller card also fits the larger ones.

The 32 GB row has the borderline cases. Qwen's FP8 file of Qwen3.8-27B, 28.75 GiB, is above our budget on a 32 GB card, and we do not plan on it there; on a 48 GB card it fits. NVIDIA's NVFP4 checkpoint of the same model, 21.9 GB or 20.4 GiB, fits one 32 GB card with about 5.3 GiB left. NVFP4 files compute natively only on Blackwell cards, so this applies to the RTX PRO 4500 in both editions. On the RTX 5000 Ada, with the same 32 GB and the same 25.7 GiB, the FP8 or 16-bit file is the one to size with.

A model that fits several of these cards holds a different number of conversations on each.

Our estimate, memory-bound, not a measurement: (budget − weights) ÷ KV cache per conversation of 8,192 tokens with an FP8 cache (0.625, 1.0 and 1.25 GiB), rounded down.

These counts say what fits. They say nothing about the tokens per second a conversation gets. For the RTX PRO 5000 48 GB, the RTX PRO 4500 Workstation Edition and the RTX PRO 4000 no measured LLM token rate has been published in a form we can cite, so this page prints none. NVIDIA publishes the memory bandwidth, which bounds the generation rate of one conversation once the model fits: by our division, the 1,344 GB/s of the RTX PRO 5000 is three quarters of the 1,792 GB/s of an RTX PRO 6000 Workstation Edition, and the 896 GB/s of the RTX PRO 4500 Workstation Edition is half.

For the Server Edition a measurement exists: StorageReview (14 October 2026, Dell PowerEdge R770, vLLM 0.27.1, 32 concurrent requests) reported 1,107 output tokens per second for one RTX PRO 4500 Server Edition with Ministral 3 14B in FP8 at 512 input and 512 output tokens. That result belongs to the Server Edition alone.

Two, three or four smaller cards against one RTX PRO 6000

The table has three ways to reach 96 GB with smaller cards next to the single card, and two larger builds.

Sums of NVIDIA's datasheet figures; usable memory by our sizing rule, as on our pages for these builds. The first row is the RTX PRO 6000 Workstation Edition.

Each card addresses only its own memory. NVIDIA's datasheets for the RTX PRO 5000, the RTX PRO 4500 Workstation Edition and the RTX PRO 4000 list no NVLink, the product brief of the Server Edition states "Not supported", and the datasheet of the RTX 5000 Ada says "No". A model larger than one card is therefore split by the serving software over PCIe, with tensor or pipeline parallelism, and every split puts traffic between the cards into each generated token. The overhead of 3 GiB is paid per card: four 24 GB cards keep 74.0 GiB by our rule, one 96 GB card 83.0 GiB.

The order we plan in is the same on all our multi-card pages. First choose a precision in which the model fits one card. Then run one copy per card behind a load balancer: no data moves between the cards, and a failed card takes out only its own copy. Split a model only when it fits no single card.

With Llama 3.3 70B in FP8 as the example, and conversations of 8,192 tokens with an FP8 KV cache as above, two RTX PRO 5000 48 GB cards hold one tensor-parallel copy with 9 conversations by our memory arithmetic, four RTX PRO 4000 cards hold one with 5 and four 32 GB cards one with 28, against 12 on a single 96 GB card that needs no traffic between cards. Over more than two cards without NVLink, vLLM disables its custom all-reduce and uses NCCL. We found no consistent published measurement of tensor-parallel scaling on four or eight of these cards, so split copies come without a speed figure here. Twelve builds with their conversation counts are in several RTX PRO 5000 or 4500 cards or fewer RTX PRO 6000, and the link between the cards is the subject of one model on several GPUs over PCIe or NVLink.

By our estimate each of the four 96 GB builds draws about 1.1 kW at the wall: board power plus one 350 W processor, plus 15 per cent for the rest of the system, to be confirmed by a measurement on the delivered system. A 230 V circuit with 16 A, planned at 80 per cent, carries 2.94 kW, so the chassis decides more than the circuit. Four of the five cards are actively cooled; the Server Edition is passive and depends on the airflow of a server whose maker lists it. Each card has one 16-pin PCIe CEM5 power connector; the box of the RTX PRO 4000 holds an adapter from one 8-pin PCIe lead, the boxes of the other three workstation cards an adapter from two.

We build workstations and servers to order with these cards and check the platform, power and cooling before we quote; tell us the chassis, the circuit and the cards you plan.

Rendering, CAD and video on the smaller cards

For GPU rendering the memory line is the scene. Chaos states for V-Ray GPU that the scene has to fit into GPU memory completely, and Blender's documentation says that several GPUs can render, each with its own memory. Where the scene fits, the choice among the workstation cards is one of render throughput.

Blender Open Data, read 10 November 2026: median samples per minute of the submissions for Blender 4.5.0; crowd-sourced, OptiX and CUDA pooled.

Puget Systems' professional GPU roundup of 18 December 2025, run on a Ryzen 9 9950X3D, put the RTX PRO 5000 50 per cent ahead of the RTX 5000 Ada in Blender Cycles and 35 per cent ahead in V-Ray GPU.

The software makers' pages we read on 10 November 2026 name much smaller memory figures for CAD and BIM. Autodesk gives 8 GB as the recommended GPU memory for AutoCAD 2027 and 12 GB for large datasets, 8 GB for the Performance tier of Revit 2027 and 8 or 16 GB for Inventor 2027. It pairs memory figures with a "Bandwidth" value in GB/s that it does not define, so we compare the memory only. The four workstation cards of this comparison meet those memory figures, the 24 GB RTX PRO 4000 in a single slot. Our guide to the GPU for a CAD workstation goes through the applications.

For video the differences are the engines and the codecs. NVIDIA's datasheets give the RTX PRO 5000 and the RTX PRO 4500 Server Edition three NVENC and three NVDEC engines, and the RTX PRO 4500 Workstation Edition, the RTX PRO 4000 and the RTX 5000 Ada two of each. NVIDIA's support matrix of 16 October 2026 lists 4:2:2 encoding for the three Blackwell workstation cards and not for the RTX 5000 Ada; AV1 encoding is listed for all four.

The five cards and their pages

NVIDIA's MIG user guide (4 November 2026), the Server Edition datasheet 5192801 for its MIG line, and NVIDIA's vGPU supported-GPU list (2 October 2026).

MIG on the RTX PRO 5000 needs Linux, driver 575.57.08 or later, vBIOS 98.02.73.00.00 and the display mode set to compute. For the RTX PRO 4500 Workstation Edition, NVIDIA's MIG guide lists an RTX PRO 4500 Blackwell without naming the edition, and the Workstation Edition datasheet does not mention MIG, so we do not plan on it. The Server Edition runs on drivers of the R595 branch from 595.58.03 or of R620, and the RTX 5000 Ada serves vGPU with its display ports turned off. The 32 GB choices are compared in RTX PRO 4500 or RTX PRO 4500 Server Edition and RTX 5000 Ada vs RTX PRO 4500 Blackwell.

Related pages: the Blackwell family from 24 to 96 GB in RTX PRO 6000 vs 5000 vs 4500 Blackwell, the 48 GB class in our 48 GB GPU comparison, complete builds in GPU workstation builds from the RTX PRO 2000 to the 5000, branded towers in RTX PRO cards in Dell, HP and Lenovo workstations, the server class in H200 NVL alternatives for LLM inference, and how to name card, edition and memory size in a request in NVIDIA GPU part numbers: what to state in a quote.

Orders run on one European contract with an invoice from Austria, and the manufacturer warranty is handled through us. Describe the models, the software and the number of cards, or write to request@eurokommerz.at, and you receive a written quote within one business day.

FAQ