NVIDIA RTX 5000 Ada Generation, AI & Machine Learning Benchmarks & Specs

32GB · AI Score 11.0/100 · first-party measured on 12 AI workloads

11 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA RTX 5000 Ada Generation 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 5000 Ada Generation delivers about 103.18 tokens/sec. Stepping up to Qwen3 32B it holds roughly 25.88 tok/s. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 32GB. For image generation, SDXL runs at 6.37 it/s, and FLUX.1-dev at 0.6 it/s. 2 of the 12 workloads won't fit on 32GB at the tested precision, Llama 3.3 70B, Qwen-Image-Edit. 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 4B170.72

Llama 3.1 8B103.18

Qwen2.5-Coder 14B56.66

Qwen3 32B25.88

Workload	Result	Telemetry	Data
Qwen3 4B	170.72 tok/s	2.8 GB peak157 W65°C1.09 tok/WQ4_K_M	✓ Measured
Llama 3.1 8B	103.18 tok/s	5 GB peak201 W70°C0.51 tok/WQ4_K_M	✓ Measured
Qwen2.5-Coder 14B	56.66 tok/s	8.7 GB peak202 W77°C0.28 tok/WQ4_K_M	✓ Measured
Qwen3 32B	25.88 tok/s	18.8 GB peak197 W83°C0.13 tok/WQ4_K_M	✓ Measured
Llama 3.3 70B	✕ Won't fit needs ~46 GB	VRAM-gated at this precision	✓ Measured

Image Generation images/min 3

Stable Diffusion XL12.74

Z-Image Turbo5.925

FLUX.1 dev1.286

Workload	Result	Telemetry	Data
Stable Diffusion XL	12.74 images/min	14.7 GB peak236 W84°C4.7 s/img	✓ Measured
FLUX.1 dev	1.29 images/min	23.6 GB peak149 W86°C46.9 s/img	✓ Measured CPU offload
Z-Image Turbo	5.93 images/min	25.7 GB peak229 W86°C10.2 s/img	✓ Measured

Image Editing images/min 2

Workload	Result	Telemetry	Data
FLUX.1 Kontext dev	0.79 images/min	24.8 GB peak178 W89°C76.5 s/img	✓ Measured CPU offload
Qwen-Image-Edit	✕ Won't fit needs ~42 GB	VRAM-gated at this precision	✓ Measured

Video Generation frames/s 2

Workload	Result	Telemetry	Data
LTX-Video (distilled)	3.23 frames/s	9.3 GB peak164 W85°C30 s/clip	✓ Measured CPU offload
Wan 2.2 5B (720p)	0.32 frames/s	18.5 GB peak211 W90°C153.1 s/clip	✓ Measured CPU offload

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 5000 Ada Generation specifications

Architecture	Ada Lovelace
CUDA cores	12,800
VRAM	32GB GDDR6 ECC
Memory bus	256-bit
Memory bandwidth	576 GB/s
Boost clock	2,550 MHz
TDP	250 W
Process	4nm
Interface	PCIe 4.0 x16
Release date	2023-08-09
Launch MSRP	$4,000

Verdict, capable, but 32GB sets the ceiling

NVIDIA RTX 5000 Ada Generation scores 11.0/100, #27 of 102. It ran 10 of 12; 2 exceeded its 32GB. Every figure here is our own measurement.

Relative performance: where the NVIDIA RTX 5000 Ada Generation lands

100% = this card, AI & Machine Learning headline metric (AI Score). #4 of 61 desktop cards in this vertical.

GPU	%	AI Score
NVIDIA RTX 6000 Ada Generation	216%	23.8
NVIDIA GeForce RTX 5090	203%	22.3
NVIDIA RTX 5880 Ada Generation	134%	14.7
NVIDIA RTX 5000 Ada Generation	100%	11
NVIDIA GeForce RTX 4090	96%	10.6
NVIDIA GeForce RTX 3090 Ti	77%	8.5
NVIDIA Titan RTX	75%	8.2
NVIDIA GeForce RTX 3090	70%	7.7

One tier up: NVIDIA RTX 5880 Ada Generation (+34%) · compare head-to-head
One tier down: NVIDIA GeForce RTX 4090 (-4%) · compare head-to-head
Best value alternative ($1,599): NVIDIA GeForce RTX 4090 (-4%) · compare head-to-head

← All AI & Machine Learning GPU rankings

The silicon

Transistors	76,300 million
Die size	608.4 mm²
Process node	4 nm
Fabricated by	TSMC
Transistor density	125.4 million per mm²

Denser than 97% 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.

Workflow	Time	Energy	Basis
24-frame storyboard	5.1 min	18.41 Wh	all 2 stages measured
60-second AI short film	9.5 min	27.06 Wh	all 3 stages measured
6-panel comic page	12.8 min	35.55 Wh	all 3 stages measured
Character sheet, 12 poses	16 min	46.88 Wh	all 2 stages measured
Full codebase review	17.6 min	59.48 Wh	measured
Short social clips	27.9 min	97.41 Wh	all 3 stages measured
Product photo shoot	53.7 min	162.13 Wh	all 2 stages measured
Photo restoration batch	2 h 6 min	374.53 Wh	measured

Can't run: Long-form article batch (needs Llama 3.3 70B).

Rent or buy?

This card is $4,000 to buy. The cheapest listed rate on Vast.ai is $0.388/hour, but that is the floor: we budget $0.466/hour, a 20% premium, because idle time, storage and unavailable cheap instances all land on the same bill. At that rate buying wins after 8,591 GPU-hours. Below it you are paying for idle silicon.

How you would use it	GPU-hours a year	Rental cost a year	Time to break even
2 hours a day, hobby	730	$340	11.8 years
8 hours a day, working on it	2,920	$1,360	2.9 years
24/7, always-on agent	8,760	$4,079	11.8 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

$0.388/hr+15.5% since 2026-09-30low $0.336 · high $0.416

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