NVIDIA GeForce RTX 2080 Ti Founders Edition, AI & Machine Learning Benchmarks & Specs

11GB · AI Score 2.2/100 · first-party measured on 12 AI workloads

2.2 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA GeForce RTX 2080 Ti Founders Edition was run on our pinned 12-workload AI suite on 2026-07-11, with under 0.5% run-to-run variance. On Llama 3.1 8B (Q4_K_M) NVIDIA GeForce RTX 2080 Ti Founders Edition delivers about 98.34 tokens/sec. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 11GB. For image generation, SDXL runs at 2.09 it/s, while FLUX.1-dev won't fit at BF16 (needs ~26GB). 9 of the 12 workloads won't fit on 11GB at the tested precision, Qwen2.5-Coder 14B, Qwen3 32B, Llama 3.3 70B, Z-Image Turbo and others. We publish those as hard gates rather than quietly dropping to a smaller quant.

Bench notes: from the person who ran it

Oldest card in my top tier and it still hangs on for small LLMs, but it works hard for it: 104% of its 250W rating on SDXL, and the worst efficiency I measured in this class at 0.79 tokens/watt. The 11GB keeps 8 of 12 workloads out. One flagged gate pending re-run. Quick note on the setup: all my AI benchmarking was done on rented cloud GPUs, I used all three of Vast.ai, RunPod and Modal depending on which had the card, and they all have their pros and cons. Same pinned harness on every run, and everything here got double-checked before it went up.

AI & Machine Learning benchmark results

Text Generation tok/s 5

Workload	Result	Telemetry	Data
Qwen3 4B	148.46 tok/s	2.6 GB peak187 W42°C0.79 tok/WQ4_K_M	✓ Measured
Llama 3.1 8B	98.34 tok/s	4.8 GB peak211 W48°C0.47 tok/WQ4_K_M	✓ Measured
Qwen2.5-Coder 14B	✕ Won't fit needs ~12 GB	VRAM-gated at this precision	✓ Measured
Qwen3 32B	✕ Won't fit needs ~23 GB	VRAM-gated at this precision	✓ 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	4.18 images/min	6 GB peak217 W71°C14.4 s/img	✓ Measured
Z-Image Turbo	✕ Won't fit needs ~13 GB	VRAM-gated at this precision	✓ 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)	✕ Won't fit needs ~14 GB	VRAM-gated at this precision	✓ Measured
Wan 2.2 5B (720p)	✕ Won't fit needs ~18 GB	VRAM-gated at this precision	✓ 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 2026-07-11 · harness 2.0.0-standalone.

NVIDIA GeForce RTX 2080 Ti Founders Edition specifications

Architecture	Turing (TU102)
CUDA cores	4,352
VRAM	11GB GDDR6
Memory bus	352-bit
Memory bandwidth	616 GB/s
Boost clock	1,545 MHz
TDP	250 W
Process	12nm
Interface	PCIe 3.0 x16
Release date	2018-09-20
Launch MSRP	$1,199

Verdict, capable, but 11GB sets the ceiling

NVIDIA GeForce RTX 2080 Ti Founders Edition scores 2.2/100, #80 of 102. It ran 3 of 12; 9 exceeded its 11GB. Every figure here is our own measurement.

Relative performance: where the NVIDIA GeForce RTX 2080 Ti Founders Edition lands

100% = this card, AI & Machine Learning headline metric (AI Score). #40 of 61 desktop cards in this vertical.

GPU	%	AI Score
AMD Radeon RX 7700 XT	114%	2.5
NVIDIA TITAN X (Pascal)	114%	2.5
AMD Radeon RX 6700	105%	2.3
NVIDIA GeForce RTX 3080	105%	2.3
NVIDIA GeForce RTX 2080 Ti Founders Edition	100%	2.2
NVIDIA GeForce RTX 3070 Ti	100%	2.2
NVIDIA GeForce RTX 2080 Super	95%	2.1
NVIDIA GeForce RTX 3070 Founders Edition	95%	2.1
NVIDIA GeForce RTX 5060	95%	2.1

One tier up: NVIDIA GeForce RTX 3080 (+5%) · compare head-to-head
One tier down: NVIDIA GeForce RTX 3070 Ti (0%) · compare head-to-head
Best value alternative ($179): Intel Arc B580 (-9%)

Same card, other workloads: NVIDIA GeForce RTX 2080 Ti Founders Edition Gaming benchmarks

← All AI & Machine Learning GPU rankings

The silicon

Transistors	18,600 million
Die size	754 mm²
Fabricated by	TSMC
Transistor density	24.7 million per mm²

Denser than 28% of the 76 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.

Can't run: 60-second AI short film (needs Qwen3 32B), 60-second AI short film, narrated (needs Qwen3 32B), 10 short social clips (needs Qwen3 32B), 40-product photo shoot (needs FLUX.1 Kontext dev), 6-panel comic page (needs Qwen3 32B), 20 long-form articles (needs Llama 3.3 70B), Full codebase review (needs Qwen2.5-Coder 14B), Character sheet, 12 poses (needs FLUX.1 dev), 100-photo restoration batch (needs FLUX.1 Kontext dev), 24-frame storyboard (needs Qwen3 32B), 100-photo restore and enlarge (needs FLUX.1 Kontext dev).