NVIDIA RTX A5000, AI & Machine Learning Benchmarks & Specs

24GB · AI Score 7.4/100 · first-party measured on 12 AI workloads

7.4 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA RTX A5000 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 A5000 delivers about 119.86 tokens/sec. Stepping up to Qwen3 32B it holds roughly 30.49 tok/s. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 24GB. For image generation, SDXL runs at 3.73 it/s, while FLUX.1-dev won't fit at BF16 (needs ~26GB). 4 of the 12 workloads won't fit on 24GB at the tested precision, Llama 3.3 70B, FLUX.1-dev, FLUX.1 Kontext, Qwen-Image-Edit. We publish those as hard gates rather than quietly dropping to a smaller quant. NVIDIA RTX A5000 isn't a retail purchase for most people. It's rented by the hour. You can run this exact card on RunPod.

AI & Machine Learning benchmark results

Text Generation tok/s 5

Qwen3 4B171.68

Llama 3.1 8B119.86

Qwen2.5-Coder 14B64.89

Qwen3 32B30.49

Workload	Result	Telemetry	Data
Qwen3 4B	171.68 tok/s	2.7 GB peak136 W53°C1.26 tok/WQ4_K_M	✓ Measured
Llama 3.1 8B	119.86 tok/s	4.9 GB peak154 W58°C0.78 tok/WQ4_K_M	✓ Measured
Qwen2.5-Coder 14B	64.89 tok/s	8.6 GB peak180 W65°C0.36 tok/WQ4_K_M	✓ Measured
Qwen3 32B	30.49 tok/s	18.7 GB peak161 W73°C0.19 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

Workload	Result	Telemetry	Data
Stable Diffusion XL	7.46 images/min	15.7 GB peak227 W80°C8 s/img	✓ Measured
Z-Image Turbo	4.05 images/min	23.1 GB peak228 W86°C14.7 s/img	✓ Measured
FLUX.1 dev	✕ Won't fit needs ~26 GB	VRAM-gated at this precision	✓ Measured

Image Editing images/min 2

Workload	Result	Telemetry	Data
FLUX.1 Kontext dev	✕ Won't fit needs ~26 GB	VRAM-gated at this precision	✓ Measured
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)	2.7 frames/s	9.2 GB peak182 W85°C35.9 s/clip	✓ Measured
Wan 2.2 5B (720p)	0.24 frames/s	16.6 GB peak211 W87°C201.2 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 A5000 specifications

Architecture	Ampere (GA102 derivative)
CUDA cores	8,192
VRAM	24GB GDDR6
Memory bus	384-bit
Memory bandwidth	768 GB/s
Boost clock	1,695 MHz
TDP	230 W
Process	8nm
Interface	PCIe 4.0 x16
Release date	2021-04-12
Launch MSRP	$2,250

Verdict, capable, but 24GB sets the ceiling

NVIDIA RTX A5000 scores 7.4/100, #37 of 102. It ran 8 of 12; 4 exceeded its 24GB. Every figure here is our own measurement.

Relative performance: where the NVIDIA RTX A5000 lands

100% = this card, AI & Machine Learning headline metric (AI Score). #11 of 20 desktop cards in this vertical.

GPU	%	AI Score
NVIDIA Quadro RTX 8000	111%	8.2
NVIDIA RTX A5500	103%	7.6
NVIDIA RTX PRO 4000 Blackwell	103%	7.6
NVIDIA Quadro RTX 6000 (Turing)	100%	7.4
NVIDIA RTX A5000	100%	7.4
AMD Radeon Pro W7800	84%	6.2
NVIDIA RTX 4500 Ada Generation	80%	5.9
AMD Radeon Pro W6800	74%	5.5
NVIDIA RTX A4500	69%	5.1

One tier up: NVIDIA Quadro RTX 6000 (Turing) (0%) · compare head-to-head
One tier down: AMD Radeon Pro W7800 (-16%)
Best value alternative ($1,500): NVIDIA RTX PRO 4000 Blackwell (+3%) · compare head-to-head

← 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
24-frame storyboard	7 min	24.57 Wh	all 2 stages measured
60-second AI short film	11.8 min	36.17 Wh	all 3 stages measured
Full codebase review	15.4 min	46.13 Wh	measured
10 short social clips	37.2 min	129.95 Wh	all 3 stages measured

Can't run: 40-product photo shoot (needs FLUX.1 Kontext dev), 6-panel comic page (needs FLUX.1 dev), 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), 100-photo restore and enlarge (needs FLUX.1 Kontext dev).

Rent or buy?

This card is $2,250 to buy. The cheapest listed rate on RunPod is $0.160/hour, but that is the floor: we budget $0.192/hour, a 20% premium, because idle time, storage and unavailable cheap instances all land on the same bill. At that rate buying wins after 11,719 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	$140	16.1 years
8 hours a day, working on it	2,920	$561	4.0 years
24/7, always-on agent	8,760	$1,682	1.3 years

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

$0.160/hr+0.0% since 2026-08-14low $0.160 · high $0.160

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