NVIDIA Quadro RTX 5000, AI & Machine Learning Benchmarks & Specs

16GB · AI Score 3.5/100 · anchored estimate vs 51 measured cards

3.5 AI Score Includes estimates

We have not run NVIDIA Quadro RTX 5000 on our bench. These figures are anchored estimates, interpolated per workload against the 51 GPUs we did measure. On Llama 3.1 8B (Q4_K_M) NVIDIA Quadro RTX 5000 should deliver about 81 tokens/sec. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 16GB. For image generation, SDXL should run near 1.57 it/s, while FLUX.1-dev won't fit at BF16 (needs ~26GB). 6 of the 12 workloads won't fit on 16GB at the tested precision, Qwen3 32B, Llama 3.3 70B, FLUX.1-dev, FLUX.1 Kontext and others. We publish those as hard gates rather than quietly dropping to a smaller quant.

AI & Machine Learning benchmark results

Text Generation tok/s 5

Qwen3 4B126.4

Llama 3.1 8B81

Qwen2.5-Coder 14B45.1

Workload	Result	Telemetry	Data
Qwen3 4B	126.4 tok/s	estimated	Est.
Llama 3.1 8B	81 tok/s	estimated	Est.
Qwen2.5-Coder 14B	45.1 tok/s	estimated	Est.
Qwen3 32B	✕ Won't fit	VRAM-gated at this precision	Est.
Llama 3.3 70B	✕ Won't fit	VRAM-gated at this precision	Est.

Image Generation images/min 3

Workload	Result	Telemetry	Data
Stable Diffusion XL	3.14 images/min	estimated	Est.
Z-Image Turbo	1.5 images/min	estimated	Est.
FLUX.1 dev	✕ Won't fit	VRAM-gated at this precision	Est.

Image Editing images/min 2

Workload	Result	Telemetry	Data
FLUX.1 Kontext dev	✕ Won't fit	VRAM-gated at this precision	Est.
Qwen-Image-Edit	✕ Won't fit	VRAM-gated at this precision	Est.

Video Generation frames/s 2

Workload	Result	Telemetry	Data
LTX-Video (distilled)	1.88 frames/s	estimated	Est.
Wan 2.2 5B (720p)	✕ Won't fit	VRAM-gated at this precision	Est.

How this estimate is derived. This card hasn’t been through our bench yet, so its numbers are anchored estimates, interpolated from the 51 first-party measured cards (LLM: bandwidth Theil-Sen ladder · diffusion/video: tensor-throughput ladder within architecture family · gates: realistic Q4/BF16 VRAM floors). The VRAM “won’t fit” gates are exact, since they’re pure capacity limits. Estimates are replaced with measured data as more silicon goes through the bench. Full methodology →

NVIDIA Quadro RTX 5000 specifications

Architecture	Turing (TU104)
CUDA cores	3,072
VRAM	16GB GDDR6
Memory bus	256-bit
Memory bandwidth	448 GB/s
Boost clock	1,770 MHz
TDP	230 W
Process	12nm
Interface	PCIe 3.0 x16
Release date	2018-08-14
Launch MSRP	$2,299

Verdict, capable, but 16GB sets the ceiling

NVIDIA Quadro RTX 5000 scores 3.5/100, #56 of 102. It ran 6 of 12; 6 exceeded its 16GB. Figures are anchored estimates, not measurements, we flag that on every row.

Relative performance: where the NVIDIA Quadro RTX 5000 lands

100% = this card, AI & Machine Learning headline metric (AI Score). #17 of 20 desktop cards in this vertical.

GPU	%	AI Score
NVIDIA RTX 4500 Ada Generation	169%	5.9
AMD Radeon Pro W6800	157%	5.5
NVIDIA RTX A4500	146%	5.1
NVIDIA RTX A4000	117%	4.1
NVIDIA Quadro RTX 5000	100%	3.5
NVIDIA RTX 2000 Ada Generation	89%	3.1
Intel Arc Pro A60	66%	2.3
NVIDIA RTX A2000	37%	1.3

One tier up: NVIDIA RTX A4000 (+17%)
One tier down: NVIDIA RTX 2000 Ada Generation (-11%)
Best value alternative ($625): NVIDIA RTX 2000 Ada Generation (-11%)

← All AI & Machine Learning GPU rankings

What this card can build

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

Workflow	Time	Energy	Basis
Full codebase review	22.2 min	n/a	estimate, 0 of 1 stage measured

Can't run: 60-second AI short film (needs Qwen3 32B), 60-second AI short film, narrated (needs Qwen3 32B), 10 short social clips (needs Qwen3 32B), 40-product photo shoot (needs FLUX.1 Kontext dev), 6-panel comic page (needs Qwen3 32B), 20 long-form articles (needs Llama 3.3 70B), Character sheet, 12 poses (needs FLUX.1 dev), 100-photo restoration batch (needs FLUX.1 Kontext dev), 24-frame storyboard (needs Qwen3 32B), 100-photo restore and enlarge (needs FLUX.1 Kontext dev).