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RTX 6000 Ada Generation
NVIDIA · GPU

RTX 6000 Ada Generation — Benchmarks & Specs

48 GB VRAM300W TDP$6,800 MSRP

Bottom line: how fast is the RTX 6000 Ada Generation?

At 4K (Path Traced, ray tracing on, DLSS Quality), the RTX 6000 Ada Generation averages 72 fps in Cyberpunk 2077, per Radargit. For local LLM inference it generates 131.0 tokens/sec running Llama 3 8B at Q4_K_M under llama.cpp, per GitHub - XiongjieDai GPU Benchmarks on LLM Inference. In 3DMark Fire Strike it scores 48,841 points, per Radargit. Its 48 GB of VRAM is the binding constraint for local inference: that capacity fits 70B-parameter open-weight models at Q4 without offloading.

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. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.

The RTX 6000 Ada Generation is a graphics card from NVIDIA. Key on-paper specs include 48 GB of GDDR VRAM, 300W TDP. It launched with a $6,800 MSRP, though street prices typically diverge meaningfully from launch pricing — see the linked product cards below for current Amazon listings. Data on this page draws on 10 synthetic benchmark results, 12 community AI inference reports, 7 measured game frame-rate results, aggregated from public benchmark databases (TechPowerUp, PassMark, Geekbench, Cinebench) and the LocalLLaMA community. Read this page when shopping the RTX 6000 Ada Generation, comparing it against other graphics cards in your build, or sizing it for a specific workload (gaming at 1080p/1440p/4K, productivity benchmarks, or local LLM inference).

Gaming Performance (measured FPS)

Average and 1% low frame rates by game, resolution, and quality preset. Bars are scaled against the fastest result on this page.

Measured gaming frame rates for the RTX 6000 Ada Generation by game, resolution, and quality preset. “1% low” is the frame-time floor that determines perceived smoothness. Each row links to its original review or benchmark database.
Game Resolution Settings Relative Avg FPS 1% low Source
Cyberpunk 2077 4K Path Traced RT on DLSS Quality 72 fps — Radargit 2025-03-11
Cyberpunk 2077 4K Path Traced RT on DLSS Quality 72 fps — RadarGit 2025-03-11
Alan Wake 2 4K Ultra RT on 64 fps — RadarGit 2025-03-11
Alan Wake 2 4K Ultra 64 fps — RadarGit 2025-03-11
Alan Wake 2 4K Ultra RT on DLSS Quality 64 fps — Radargit 2025-03-11
Starfield 4K Ultra RT on DLSS Quality 55 fps — Radargit 2025-03-11
Starfield 4K Ultra 55 fps — RadarGit 2025-03-11

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 6000 Ada Generation, in generated tokens per second. Higher is better; each row links to the community report or benchmark database it came from.
Model Quantization Relative Tokens/sec VRAM used Source
Llama 3 8B Q4_K_M llama.cpp 131.0 tok/s — GitHub - XiongjieDai GPU Benchmarks on LLM Inference 2024-05-01
llama3:8b q4_K_M llama.cpp 131.0 tok/s — GitHub XiongjieDai/GPU-Benchmarks-on-LLM-Inference 2024-05-01
llama3:8b q4_K_M llama.cpp 131.0 tok/s — XiongjieDai/GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-05-01
llama3:8b q4_K_M llama.cpp 131.0 tok/s — GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-10-01
llama3.1:8b q4_K_M llama.cpp 110.0 tok/s 5.5 GB MyAIHardware 2026-05-22
deepseekr1:32b — ollama 100.0 tok/s — LocalLLaMA 2026-04-18
llama4:17b-scout q4_K_M llama.cpp 56.0 tok/s 60.9 GB Fixstars Corporation Tech Blog 2025-05-21
llama4:scout-17b-16e q4_K_M llama.cpp 56.0 tok/s 30.4 GB Fixstars Corporation Tech Blog 2025-05-21
llama3:8b FP16 llama.cpp 52.0 tok/s — XiongjieDai/GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-05-01
llama3:8b FP16 llama.cpp 52.0 tok/s — GPU-Benchmarks-on-LLM-Inference (GitHub) 2024-10-01
Llama 3 8B F16 llama.cpp 52.0 tok/s — GitHub - XiongjieDai GPU Benchmarks on LLM Inference 2024-05-01
llama3:8b FP16 llama.cpp 52.0 tok/s — GitHub XiongjieDai/GPU-Benchmarks-on-LLM-Inference 2024-05-01

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 6000 Ada Generation — higher is better. Each row links to the public database the number was taken from.
Benchmark Relative Score Source
3DMark Fire Strike 48,841 points Radargit 2025-03-11
3DMark Fire Strike 48,841 points RadarGit 2025-03-11
3DMark Steel Nomad Lite 32,929 points RadarGit 2025-03-11
3DMark Steel Nomad Lite 32,929 points Radargit 2025-03-11
3DMark Time Spy Graphics 30,518 points Tom's Hardware 2023-02-02
3DMark Time Spy (Graphics Score) 30,518 points KitGuru 2023-02-03
PassMark G3D Mark 28,663 points PassMark (VideoCardBenchmark) 2023-03-08
PassMark G3D Mark 28,598 pts PassMark 2026-04-20
3DMark Time Spy 26,529 points Radargit 2025-03-11
3DMark Time Spy 26,048 points 3DMark 2024-03-01

Full Specifications

tdp w300
vram gb48
cuda cores18176
memory typeGDDR6

RTX 6000 Ada Generation — Frequently Asked Questions

What is the RTX 6000 Ada Generation best used for?
RTX 6000 Ada Generation is positioned as a 48 GB VRAM graphics card. Use it for high-end 4K gaming and local LLM inference. See the synthetic + AI benchmark tables below for measured performance.
When was the RTX 6000 Ada Generation released, and what was its launch MSRP?
Release year and launch MSRP aren't on file for RTX 6000 Ada Generation. Current pricing is visible on the linked Amazon product cards below.
Where do the benchmark numbers on this page come from?
Synthetic benchmarks are scraped from public databases (TechPowerUp, PassMark, Geekbench Browser, Cinebench leaderboards). AI inference numbers come from the LocalLLaMA community (Reddit threads, llama.cpp / Ollama discussion logs, and Phoronix when available). Every benchmark row carries an inline source citation — click through to verify the original number.
Can the RTX 6000 Ada Generation run local LLMs?
Yes — RTX 6000 Ada Generation has 12 AI inference benchmarks on file (see the AI Inference Performance section above for model + tokens-per-second numbers). With 48 GB VRAM, it fits the popular 32B-parameter open-weight models at Q4 quantization comfortably.
Where can I buy the RTX 6000 Ada Generation?
Active Amazon listings aren't on file for this exact SKU yet. See the linked benchmark sources and the Compare tool for adjacent parts that may be in stock — and check the /benchmarks index for the latest curated picks in this category.

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