NVIDIA · GPU · Ada Lovelace

NVIDIA RTX 5000 Ada Generation — Benchmarks & Specs

32 GB VRAM

Short answer: the NVIDIA RTX 5000 Ada Generation generates a median 89.9 tokens/sec on 7-9B dense models at 4-bit (Q4) under llama.cpp, across 3 cited runs from OpenLLMBenchmarks and GPU-Benchmarks-on-LLM-Inference. Its 32 GB of VRAM holds up to DeepSeek-R1-Distill-Qwen 32B at Q4_K_M with an ~8K context, by the Will-It-Run matrix's sizing (20 of 23 models fit). A used eBay listing for it is $4,399.00, checked 2026-10-20 20:17 UTC (listings can end at any time).

Median speed 89.9 tok/s 3 cited runs, 7-9B at Q4, llama.cpp
Fits in 32 GB up to DeepSeek-R1-Distill-Qwen 32B at Q4_K_M → at ~8K context; 20 of 23 models in the Will-It-Run matrix

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Bottom line: how fast is the RTX 5000 Ada Generation?

SpecPicks median: 89.9 tokens/sec across 3 cited single-user runs of 7-9B dense models at 4-bit (Q4) under llama.cpp (range 89.9–89.9 tok/s), from OpenLLMBenchmarks, GPU-Benchmarks-on-LLM-Inference (2 runs). One of those runs: llama3:8b at q4_K_M generates 89.9 tokens/sec under llama.cpp, per GPU-Benchmarks-on-LLM-Inference. In Geekbench 5 Vulkan it scores 251,643 points, per Technical.city. It has 32 GB of VRAM, and the llama3:8b run above (8B parameters) is the largest model on file at 4-bit quantization on this card. Larger models have no sourced run on file.

Every figure above is a row in the tables below, and each row links out to the review or public benchmark database the number was taken from; the SpecPicks median is computed here from the runs it names, each a row in the AI table. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.

eBay listing (Open box): $4,399.00, checked 2026-10-20 20:17 UTC. eBay listings are third-party and can end at any time; as an eBay Partner Network member, SpecPicks may earn a commission.

Check what fits in 32 GB: by Q4-class file size, 20 of the 23 open-weight models in the SpecPicks Will-It-Run matrix load entirely into the NVIDIA RTX 5000 Ada Generation's 32 GB with 1.5 GB left for an ~8K context, up to DeepSeek-R1-Distill-Qwen 32B (a 19.9 GB Q4_K_M file per its Hugging Face listing). Check a model in the Will-It-Run matrix →

The RTX 5000 Ada Generation is a graphics card from the Ada Lovelace family from NVIDIA. Key on-paper specs include 32 GB of VRAM. Data on this page draws on 2 linked listings, 12 synthetic benchmark results (top 10 shown), 9 community AI inference reports, compiled from GPU-Benchmarks-on-LLM-Inference, OpenLLMBenchmarks, LocalLLaMA, Notebookcheck, Technical.city, 3DMark, NanoReview, PassMark, Puget Systems, TopCPU.net; each table row links to its source. Read this page when shopping the RTX 5000 Ada Generation, comparing it against other graphics cards in your build, or sizing it for a specific workload (synthetic benchmark scores or local LLM inference).

AI Inference Performance

Tokens per second under each model + quantization. Higher = faster generation. Bars compare runs across the same model.

Local LLM inference throughput on the RTX 5000 Ada Generation, in generated tokens per second for a single request (one user's generation speed). Higher is better; each row links to the community report or benchmark database it came from.
Model	Quantization	Tokens/sec	VRAM used	Source
deepseekr1:32b	— ollama	100.0 tok/s	—	LocalLLaMA 2026-04-18
llama3:8b	q4_K_M llama.cpp	89.9 tok/s	—	OpenLLMBenchmarks 2024-01
llama3:8b	q4_K_M llama.cpp	89.9 tok/s	—	GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-05
llama3.1:8b	q4_K_M llama.cpp	89.9 tok/s	—	XiongjieDai/GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-08
llama3:8b	FP16 llama.cpp	32.7 tok/s	—	GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-05
llama3.1:8b	FP16 llama.cpp	32.7 tok/s	—	XiongjieDai/GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-08
llama3:8b	FP16 llama.cpp	32.7 tok/s	—	OpenLLMBenchmarks 2024-01
qwen3:30b	— ollama	13.0 tok/s	—	LocalLLaMA 2026-04-17
phi-3-mini-4k-instruct	q4_K_M llama.cpp	— tok/s	—	Puget Systems 2024-08-22

Synthetic Benchmarks

Higher is better. Bars are scaled within each benchmark family (multi-thread, single-thread, etc.) so you can compare like-with-like at a glance.

Synthetic benchmark scores for the RTX 5000 Ada Generation — higher is better. Each row links to the public database the number was taken from. A benchmark listed more than once is separate published results, shown as published rather than averaged.
Benchmark	Score	Source
Geekbench 5 Vulkan	251,643 points	Technical.city (Geekbench Browser aggregate) retrieved 2026-07-11
Geekbench 5 OpenCL	193,891 points	Technical.city (Geekbench Browser aggregate) retrieved 2026-07-11
PassMark G3D Mark	30,648 points	PassMark VideoCardBenchmark retrieved 2026-07-11
PassMark G3D Mark	30,293 points	PassMark Software retrieved 2026-05-05
PassMark G3D Mark	30,156 pts	PassMark retrieved 2026-04-20
3DMark Steel Nomad Lite	28,751 points	NanoReview (3DMark Browser aggregate) retrieved 2026-07-11
3DMark Fire Strike	27,190 points	Notebookcheck retrieved 2026-07-11
3DMark Time Spy	14,894 points	Notebookcheck retrieved 2026-07-11
3DMark Time Spy	14,170 points	TopCPU.net retrieved 2026-08-20
3DMark Time Spy	13,898 points	3DMark 2024-06-09

Products Featuring the RTX 5000 Ada Generation

Quadro RTX 5000 Ada Generation GDDR6 32GB

$4999.00

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PNY

NVIDIA Quadro RTX 5000 Graphic Card - 32 GB GDDR6

$4499.00

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Full Specifications

VRAM	32 GB

RTX 5000 Ada Generation — Frequently Asked Questions

What is the RTX 5000 Ada Generation best used for?

RTX 5000 Ada Generation is a 32 GB VRAM Ada Lovelace-family workstation graphics card. Professional 3D modeling, CAD, rendering and simulation on certified drivers, plus local LLM inference in its large VRAM pool, are the headline use cases; the benchmark tables on this page place it within its generation.

Where do the RTX 5000 Ada Generation benchmark numbers come from?

Each benchmark row on this page names its source (public benchmark databases such as TechPowerUp, PassMark, Geekbench and Cinebench, and community reports such as r/LocalLLaMA threads) and links to it, so every number can be checked against the original.

Can the RTX 5000 Ada Generation run local LLMs?

Yes — AI inference results for the RTX 5000 Ada Generation are on file; the AI Inference Performance section on this page lists model, quantization and tokens-per-second for each run. With 32 GB VRAM, 32B-parameter open-weight models fit at Q4 quantization.

Where can I buy the RTX 5000 Ada Generation?

Amazon listings for the RTX 5000 Ada Generation are linked at the top of this page and in the Products Featuring the RTX 5000 Ada Generation section. SpecPicks earns a small affiliate commission on qualifying purchases, at no extra cost to the buyer.