NVIDIA RTX A5500, AI & Machine Learning Benchmarks & Specs

24GB · AI Score 8.4/100 · anchored estimate vs 51 measured cards

8.4 AI Score Includes estimates

We have not run NVIDIA RTX A5500 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 RTX A5500 should deliver about 127.6 tokens/sec. Stepping up to Qwen3 32B it should hold roughly 30 tok/s. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 24GB. For image generation, SDXL should run near 4.25 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.

AI & Machine Learning benchmark results

Text Generation tok/s 5

Qwen3 4B187.5

Llama 3.1 8B127.6

Qwen2.5-Coder 14B69.9

Qwen3 32B30.5

Workload	Result	Telemetry	Data
Qwen3 4B	187.5 tok/s	estimated	Est.
Llama 3.1 8B	127.6 tok/s	estimated	Est.
Qwen2.5-Coder 14B	69.9 tok/s	estimated	Est.
Qwen3 32B	30.5 tok/s	estimated	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	8.51 images/min	estimated	Est.
FLUX.1 dev	✕ Won't fit	VRAM-gated at this precision	Est.
Z-Image Turbo	7.4 images/min	estimated	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)	3.31 frames/s	estimated	Est.
Wan 2.2 5B (720p)	0.4 frames/s	estimated	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 (Bandwidth Theil-Sen ladder off NVIDIA anchors × vendor factor (diffusion slot corrected (above the measured RTX A5000)); measured VRAM floors; recalibrated 2026-09-19 against published llama.cpp (CUDA/ROCm/Vulkan/SYCL) and Stable Diffusion results.). 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 RTX A5500 specifications

Architecture	Ampere
CUDA cores	10,240
VRAM	24GB GDDR6
Memory bus	384-bit
Memory bandwidth	768 GB/s
Boost clock	1,665 MHz
TDP	230 W
Process	8nm
Interface	PCIe 4.0 x16
Release date	2022-03-22
Launch MSRP	$3,600

Verdict, capable, but 24GB sets the ceiling

NVIDIA RTX A5500 scores 8.4/100, #30 of 102. It ran 8 of 12; 4 exceeded its 24GB. Figures are anchored estimates, not measurements, we flag that on every row.

Relative performance: where the NVIDIA RTX A5500 lands

100% = this card, AI & Machine Learning headline metric (AI Score). #6 of 20 workstation cards in this vertical.

GPU	%	AI Score
NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition	518%	43.5
NVIDIA RTX PRO 5000 Blackwell	376%	31.6
NVIDIA RTX A6000	250%	21
NVIDIA RTX PRO 4500 Blackwell	154%	12.9
NVIDIA RTX A5500	100%	8.4
NVIDIA Quadro RTX 8000	98%	8.2
NVIDIA RTX PRO 4000 Blackwell	90%	7.6
NVIDIA Quadro RTX 6000 (Turing)	88%	7.4
NVIDIA RTX A5000	88%	7.4

One tier up: NVIDIA RTX PRO 4500 Blackwell (+54%)
One tier down: NVIDIA Quadro RTX 8000 (-2%)
Best value alternative ($1,500): NVIDIA RTX PRO 4000 Blackwell (-10%)

← All AI & Machine Learning GPU rankings

The silicon

Transistors	28,300 million
Die size	628.4 mm²
Process node	8 nm
Fabricated by	Samsung
Transistor density	45 million per mm²

Denser than 81% 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	4 min	n/a	estimate, 0 of 2 stages measured
60-second AI short film	9.6 min	n/a	estimate, 0 of 3 stages measured
Full codebase review	14.3 min	n/a	estimate, 0 of 1 stage measured
Short social clips	22 min	n/a	estimate, 0 of 3 stages measured

Can't run: Product photo shoot (needs FLUX.1 Kontext dev), Photo restoration batch (needs FLUX.1 Kontext dev), Restore and enlarge photos (needs FLUX.1 Kontext dev), Character sheet, 12 poses (needs FLUX.1 dev), 6-panel comic page (needs FLUX.1 dev), Long-form article batch (needs Llama 3.3 70B).