NVIDIA GeForce RTX 4060 Ti 16GB, AI & Machine Learning Benchmarks & Specs

16GB · AI Score 3.2/100 · first-party measured on 12 AI workloads

3.2 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA GeForce RTX 4060 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 4060 Ti delivers about 57.09 tokens/sec. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 16GB. For image generation, SDXL runs at 2.29 it/s, while FLUX.1-dev won't fit at BF16 (needs ~26GB). 6 of the 12 workloads won't fit on 16GB at the tested precision, Qwen3 32B, Llama 3.3 70B, FLUX.1-dev, FLUX.1 Kontext and others. We publish those as hard gates rather than quietly dropping to a smaller quant.

Bench notes: from the person who ran it

Important: this is the 16GB SKU, I say that everywhere because the 8GB version is a different card for AI. The 16GB ran LTX video and Z-Image, stuff even 12GB cards refuse. It did creep to 103% of its 160W rating on SDXL and hit 77°C on video, but for a budget AI card the VRAM does the talking. 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

Qwen3 4B96.29

Llama 3.1 8B57.09

Qwen2.5-Coder 14B31.12

Workload	Result	Telemetry	Data
Qwen3 4B	96.29 tok/s	2.8 GB peak99 W52°C0.97 tok/WQ4_K_M	✓ Measured
Llama 3.1 8B	57.09 tok/s	4.8 GB peak111 W55°C0.51 tok/WQ4_K_M	✓ Measured
Qwen2.5-Coder 14B	31.12 tok/s	8.5 GB peak126 W62°C0.25 tok/WQ4_K_M	✓ 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	4.58 images/min	14.5 GB peak161 W75°C13.1 s/img	✓ Measured
Z-Image Turbo	1.35 images/min	14 GB peak106 W75°C44.8 s/img	✓ 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)	1.5 frames/s	9.1 GB peak117 W77°C64.5 s/clip	✓ 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 4060 Ti 16GB specifications

Architecture	Ada Lovelace
CUDA cores	4,352
VRAM	16GB GDDR6
Memory bus	128-bit
Memory bandwidth	288 GB/s
Boost clock	2,535 MHz
TDP	165 W
Process	4 nm
Interface	PCIe 4.0 x16
Release date	2023-07-18
Launch MSRP	$499

Verdict, capable, but 16GB sets the ceiling

NVIDIA GeForce RTX 4060 Ti scores 3.2/100, #63 of 102. It ran 6 of 12; 6 exceeded its 16GB. Every figure here is our own measurement.

Relative performance: where the NVIDIA GeForce RTX 4060 Ti 16GB lands

100% = this card, AI & Machine Learning headline metric (AI Score). #26 of 61 desktop cards in this vertical.

GPU	%	AI Score
AMD Radeon RX 6800 XT	103%	3.3
AMD Radeon RX 6800	103%	3.3
AMD Radeon RX 6900 XT	103%	3.3
AMD Radeon RX 7800 XT	103%	3.3
NVIDIA GeForce RTX 4060 Ti 16GB	100%	3.2
GeForce RTX 5070	100%	3.2
NVIDIA GeForce RTX 4070 Super	97%	3.1
NVIDIA GeForce RTX 4070	97%	3.1
NVIDIA GeForce RTX 4070 Ti	94%	3

One tier up: AMD Radeon RX 7800 XT (+3%)
One tier down: GeForce RTX 5070 (0%) · compare head-to-head
Best value alternative ($349): Intel Arc A770 Limited Edition (-9%)

Same card, other workloads: NVIDIA GeForce RTX 4060 Ti 16GB Gaming benchmarks

← All AI & Machine Learning GPU rankings

The silicon

Transistors	22,900 million
Die size	187.8 mm²
Process node	4 nm
Fabricated by	TSMC
Transistor density	121.9 million per mm²

Denser than 95% 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.

Workflow	Time	Energy	Basis
Full codebase review	32.1 min	67.32 Wh	measured

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), 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).