NVIDIA RTX PRO 5000 Blackwell, AI & Machine Learning Benchmarks & Specs

48GB · AI Score 31.6/100 · first-party measured on 12 AI workloads

31.6 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA RTX PRO 5000 Blackwell was run on our pinned 12-workload AI suite on 2026-07-12, with under 0.5% run-to-run variance. On Llama 3.1 8B (Q4_K_M) NVIDIA RTX PRO 5000 Blackwell delivers about 208.3 tokens/sec. Stepping up to Qwen3 32B it holds roughly 54.27 tok/s. The full Llama 3.3 70B still runs, at about 26.29 tok/s. For image generation, SDXL runs at 8.73 it/s, and FLUX.1-dev at 1.96 it/s. All 12 workloads fit in 48GB. There is no model in our suite this card has to turn down.

AI & Machine Learning benchmark results

Text Generation tok/s 5

Qwen3 4B298.78
Llama 3.1 8B208.3
Qwen2.5-Coder 14B114.63
Qwen3 32B54.27
Llama 3.3 70B26.29
WorkloadResultTelemetryData
Qwen3 4B298.78 tok/s
3.1 GB peak131 W47°C2.29 tok/WQ4_K_M
✓ Measured
Llama 3.1 8B208.3 tok/s
4.8 GB peak171 W49°C1.22 tok/WQ4_K_M
✓ Measured
Qwen2.5-Coder 14B114.63 tok/s
8.8 GB peak181 W54°C0.63 tok/WQ4_K_M
✓ Measured
Qwen3 32B54.27 tok/s
18.8 GB peak166 W57°C0.33 tok/WQ4_K_M
✓ Measured
Llama 3.3 70B26.29 tok/s
39.9 GB peak158 W61°C0.17 tok/WQ4_K_M
✓ Measured

Image Generation images/min 3

Stable Diffusion XL17.46
Z-Image Turbo9.075
FLUX.1 dev4.2
WorkloadResultTelemetryData
Stable Diffusion XL17.46 images/min
14.5 GB peak297 W63°C3.4 s/img
✓ Measured
Z-Image Turbo9.08 images/min
25.7 GB peak300 W67°C6.6 s/img
✓ Measured
FLUX.1 dev4.2 images/min
36.6 GB peak300 W72°C14.3 s/img
✓ Measured

Image Editing images/min 2

WorkloadResultTelemetryData
FLUX.1 Kontext dev1.8 images/min
35.4 GB peak300 W76°C33.2 s/img
✓ Measured
Qwen-Image-Edit0.8 images/min
40.1 GB peak185 W71°C74.9 s/img
✓ Measured
CPU offload

Video Generation frames/s 2

WorkloadResultTelemetryData
LTX-Video (distilled)4.58 frames/s
9.4 GB peak174 W64°C21.2 s/clip
✓ Measured
CPU offload
Wan 2.2 5B (720p)0.56 frames/s
37.4 GB peak300 W77°C88.3 s/clip
✓ Measured
How we measured this. Every result comes from our own pinned, reproducible AI suite, 12 workloads: the Qwen3-4B to Llama-70B LLM ladder (llama.cpp, Q4_K_M), SDXL / Z-Image / FLUX-dev generation, FLUX-Kontext / Qwen-Edit editing, and LTX / Wan video, run first-party on rented hardware with under 0.5% run-to-run variance. Peak VRAM, power draw, temperature and tokens-per-watt are captured per workload. “Won’t fit” rows are real data: where a model exceeds the card’s VRAM at the tested precision we record a hard gate rather than silently dropping to a smaller quant. Measured 2026-07-12 · harness 2.0.0-standalone.

NVIDIA RTX PRO 5000 Blackwell specifications

ArchitectureBlackwell
CUDA cores14,080
VRAM48GB GDDR7 ECC
Memory bus384-bit
Memory bandwidth1344 GB/s
Boost clock2,377 MHz
TDP300 W
Process4nm (TSMC 4N)
InterfacePCIe 5.0 x16
Release date2025-08-01
Launch MSRP$4,500

Verdict, NVIDIA RTX PRO 5000 Blackwell on real AI workloads

NVIDIA RTX PRO 5000 Blackwell scores 31.6/100, #16 of 102. It ran all 12 workloads. Every figure here is our own measurement.

Relative performance: where the NVIDIA RTX PRO 5000 Blackwell lands

100% = this card, AI & Machine Learning headline metric (AI Score). #3 of 20 workstation cards in this vertical.

GPURelative%AI Score
NVIDIA RTX PRO 6000 Blackwell Workstation Edition
168%53.1
NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
138%43.5
NVIDIA RTX PRO 5000 Blackwell
100%31.6
NVIDIA RTX A6000
66%21
NVIDIA RTX PRO 4500 Blackwell
41%12.9
NVIDIA RTX A5500
27%8.4
NVIDIA Quadro RTX 8000
26%8.2

← All AI & Machine Learning GPU rankings

The silicon

Transistors92,200 million
Die size750 mm²
Process node4 nm
Fabricated byTSMC
Transistor density122.9 million per mm²

Denser than 96% of the 746 cards we have silicon data for. Density is the clearest measure of what a process node bought: a card that gained it without growing the die got its speed from the fab rather than the architecture.

Silicon figures from Wikipedia (CC BY-SA 4.0). Benchmarks on this page are our own. Compare every chip.

What this card can build

Whole-job timings, composed from our measured per-model results on this card.

WorkflowTimeEnergyBasis
24-frame storyboard3.4 min14.39 Whall 2 stages measured
6-panel comic page5.6 min24.38 Whall 3 stages measured
60-second AI short film6.7 min20.33 Whall 3 stages measured
Character sheet, 12 poses7.6 min34.5 Whall 2 stages measured
Full codebase review8.7 min26.33 Whmeasured
Short social clips16.5 min78.82 Whall 3 stages measured
Long-form article batch17.8 min46.68 Whmeasured
Product photo shoot25.1 min122.39 Whall 2 stages measured
Photo restoration batch55.9 min277.59 Whmeasured

Rent or buy?

This card is $4,500 to buy. The cheapest listed rate on Vast.ai is $0.593/hour, but that is the floor: we budget $0.712/hour, a 20% premium, because idle time, storage and unavailable cheap instances all land on the same bill. At that rate buying wins after 6,324 GPU-hours. Below it you are paying for idle silicon.

How you would use itGPU-hours a yearRental cost a yearTime to break even
2 hours a day, hobby730$5198.7 years
8 hours a day, working on it2,920$2,0782.2 years
24/7, always-on agent8,760$6,2348.7 months

At hobby usage this card is very unlikely to pay for itself before it is superseded. Rent it. Rental figures include a 20% premium over the cheapest listed rate. Ignores electricity, resale and the fact that a rented card can be a newer one tomorrow.

Rental price

$0.593/hr-4.4% since 2026-10-01low $0.467 · high $0.620

Cheapest of the RunPod and Vast on-demand rates we see, sampled daily. Spot and interruptible pricing runs lower.