NVIDIA GeForce RTX 3060 Ti, AI & Machine Learning Benchmarks & Specs

8GB · AI Score 2.0/100 · first-party measured on 12 AI workloads

2 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA GeForce RTX 3060 Ti 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 3060 Ti delivers about 76.93 tokens/sec. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 8GB. For image generation, SDXL runs at 1.1 it/s, while FLUX.1-dev won't fit at BF16 (needs ~26GB). 9 of the 12 workloads won't fit on 8GB 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

The 3060 Ti is basically a lesson in what 8GB means in 2026, 9 of my 12 workloads wouldn't even load. What it does run, it runs hot: SDXL pushed it to 81°C at 99% of its 200W rating, and that was also my noisiest run on this card. If you're buying for AI, the 8GB is the whole story. 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	118.21 tok/s	2.9 GB peak130 W63°C0.91 tok/WQ4_K_M	✓ Measured
Llama 3.1 8B	76.93 tok/s	4.8 GB peak145 W67°C0.53 tok/WQ4_K_M	✓ Measured
Qwen2.5-Coder 14B	✕ Won't fit needs ~11.5 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	2.2 images/min	6.5 GB peak151 W81°C27.3 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 3060 Ti specifications

Architecture	Ampere (GA104)
CUDA cores	4,864
VRAM	8GB GDDR6
Memory bus	256-bit
Memory bandwidth	448 GB/s
Boost clock	1,665 MHz
TDP	200 W
Process	8nm
Interface	PCIe 4.0 x16
Release date	2020-12-02
Launch MSRP	$399

Verdict, capable, but 8GB sets the ceiling

NVIDIA GeForce RTX 3060 Ti scores 2.0/100, #87 of 102. It ran 3 of 12; 9 exceeded its 8GB. Every figure here is our own measurement.

Relative performance: where the NVIDIA GeForce RTX 3060 Ti lands

100% = this card, AI & Machine Learning headline metric (AI Score). #47 of 61 desktop cards in this vertical.

GPU	%	AI Score
NVIDIA GeForce RTX 3070 Founders Edition	105%	2.1
NVIDIA GeForce RTX 5060	105%	2.1
NVIDIA GeForce RTX 2070 SUPER	100%	2
NVIDIA GeForce RTX 2080 Founders Edition	100%	2
NVIDIA GeForce RTX 3060 Ti	100%	2
Intel Arc B580	100%	2
NVIDIA GeForce RTX 2060 Super	95%	1.9
NVIDIA GeForce RTX 2070	95%	1.9
NVIDIA GeForce RTX 3050	95%	1.9

One tier up: NVIDIA GeForce RTX 2080 Founders Edition (0%)
One tier down: Intel Arc B580 (0%)
Best value alternative ($179): Intel Arc B580 (0%)

Same card, other workloads: NVIDIA GeForce RTX 3060 Ti Gaming benchmarks

← All AI & Machine Learning GPU rankings

The silicon

Transistors	17,400 million
Die size	392.5 mm²
Fabricated by	Samsung
Transistor density	44.3 million per mm²

Denser than 42% 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).