NVIDIA RTX A6000, AI & Machine Learning Benchmarks & Specs

48GB · AI Score 21.0/100 · first-party measured on 12 AI workloads

21 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA RTX A6000 was run on our pinned 12-workload AI suite, with under 0.5% run-to-run variance. On Llama 3.1 8B (Q4_K_M) NVIDIA RTX A6000 delivers about 124.87 tokens/sec. Stepping up to Qwen3 32B it holds roughly 32.18 tok/s. The full Llama 3.3 70B still runs, at about 15.73 tok/s. For image generation, SDXL runs at 5.01 it/s, and FLUX.1-dev at 1.01 it/s. All 12 workloads fit in 48GB. There is no model in our suite this card has to turn down. NVIDIA RTX A6000 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 4B184.34

Llama 3.1 8B124.87

Qwen2.5-Coder 14B68.51

Qwen3 32B32.18

Llama 3.3 70B15.73

Workload	Result	Telemetry	Data
Qwen3 4B	184.34 tok/s	2.7 GB peak144 W48°C1.28 tok/WQ4_K_M	✓ Measured
Llama 3.1 8B	124.87 tok/s	4.7 GB peak169 W52°C0.74 tok/WQ4_K_M	✓ Measured
Qwen2.5-Coder 14B	68.51 tok/s	8.7 GB peak171 W58°C0.4 tok/WQ4_K_M	✓ Measured
Qwen3 32B	32.18 tok/s	18.7 GB peak126 W60°C0.26 tok/WQ4_K_M	✓ Measured
Llama 3.3 70B	15.73 tok/s	39.8 GB peak114 W63°C0.14 tok/WQ4_K_M	✓ Measured

Image Generation images/min 3

Stable Diffusion XL10.02

Z-Image Turbo5.4

FLUX.1 dev2.164

Workload	Result	Telemetry	Data
Stable Diffusion XL	10.02 images/min	15.8 GB peak297 W59°C6 s/img	✓ Measured
Z-Image Turbo	5.4 images/min	25.6 GB peak296 W67°C11.1 s/img	✓ Measured
FLUX.1 dev	2.16 images/min	36.5 GB peak298 W76°C27.7 s/img	✓ Measured

Image Editing images/min 1

Workload	Result	Telemetry	Data
FLUX.1 Kontext dev	1.05 images/min	35.3 GB peak296 W79°C57.7 s/img	✓ 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.

NVIDIA RTX A6000 specifications

Architecture	Ampere
CUDA cores	10,752
VRAM	48GB GDDR6
Memory bus	384-bit
Memory bandwidth	768 GB/s
Boost clock	1,860 MHz
TDP	300 W
Process	8nm
Interface	PCIe 4.0 x16
Release date	2020-10-05
Launch MSRP	$4,650

Verdict, NVIDIA RTX A6000 on real AI workloads

NVIDIA RTX A6000 scores 21.0/100, #20 of 102. It ran all 12 workloads. Every figure here is our own measurement.

Relative performance: where the NVIDIA RTX A6000 lands

100% = this card, AI & Machine Learning headline metric (AI Score). #4 of 20 desktop cards in this vertical.

GPU	%	AI Score
NVIDIA RTX PRO 6000 Blackwell Workstation Edition	253%	53.1
NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition	216%	45.3
NVIDIA RTX PRO 5000 Blackwell	150%	31.6
NVIDIA RTX A6000	100%	21
NVIDIA RTX PRO 4500 Blackwell	61%	12.9
AMD Radeon Pro W7900	61%	12.8
NVIDIA Quadro RTX 8000	39%	8.2
NVIDIA RTX A5500	36%	7.6

One tier up: NVIDIA RTX PRO 5000 Blackwell (+50%) · compare head-to-head
One tier down: NVIDIA RTX PRO 4500 Blackwell (-39%) · 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	7.1 min	23.42 Wh	all 2 stages measured
6-panel comic page	12.1 min	42.76 Wh	all 3 stages measured
Full codebase review	14.6 min	41.58 Wh	measured
Character sheet, 12 poses	15.2 min	58.73 Wh	all 2 stages measured
20 long-form articles	29.7 min	56.52 Wh	measured
40-product photo shoot	45.5 min	207.87 Wh	all 2 stages measured
100-photo restoration batch	1 h 37 min	470.32 Wh	measured

Rent or buy?

This card is $4,650 to buy. The cheapest listed rate on RunPod is $0.330/hour, but that is the floor: we budget $0.396/hour, a 20% premium, because idle time, storage and unavailable cheap instances all land on the same bill. At that rate buying wins after 11,742 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	$289	16.1 years
8 hours a day, working on it	2,920	$1,156	4.0 years
24/7, always-on agent	8,760	$3,469	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

$0.330/hr+0.0% since 2026-08-14low $0.330 · high $0.330

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