NVIDIA GeForce RTX 4070 Super, AI & Machine Learning Benchmarks & Specs

12GB · AI Score 3.1/100 · first-party measured on 12 AI workloads

3.1 AI Score ✓ Measured

Every number on this page is first-party: NVIDIA GeForce RTX 4070 Super 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 4070 Super delivers about 93.62 tokens/sec. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 12GB. 8 of the 12 workloads won't fit on 12GB at the tested precision, Qwen3 32B, Llama 3.3 70B, Z-Image Turbo, FLUX.1-dev and others. We publish those as hard gates rather than quietly dropping to a smaller quant.

Bench notes: from the person who ran it

Coolest-running card of the mid-range Ada bunch, never saw it break 60°C, even holding 97% of its power rating on the coder model. Efficiency is genuinely good at 1.32 tokens/watt. The 12GB is what stops it: 8 of 12 workloads exceeded VRAM. 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 4B152.84

Llama 3.1 8B93.62

Qwen2.5-Coder 14B51.23

Workload	Result	Telemetry	Data
Qwen3 4B	152.84 tok/s	2.6 GB peak116 W54°C1.32 tok/WQ4_K_M	✓ Measured
Llama 3.1 8B	93.62 tok/s	4.6 GB peak148 W57°C0.63 tok/WQ4_K_M	✓ Measured
Qwen2.5-Coder 14B	51.23 tok/s	8.6 GB peak142 W60°C0.36 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 2

Workload	Result	Telemetry	Data
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 4070 Super specifications

Architecture	Ada Lovelace
CUDA cores	7,168
VRAM	12GB GDDR6X
Memory bus	192-bit
Memory bandwidth	504 GB/s
Boost clock	2,475 MHz
TDP	220 W
Process	4nm
Interface	PCIe 4.0 x16
Release date	2024-01-17
Launch MSRP	$599

Verdict, capable, but 12GB sets the ceiling

NVIDIA GeForce RTX 4070 Super scores 3.1/100, #65 of 102. It ran 3 of 12; 8 exceeded its 12GB. Every figure here is our own measurement.

Relative performance: where the NVIDIA GeForce RTX 4070 Super lands

100% = this card, AI & Machine Learning headline metric (AI Score). #28 of 61 desktop cards in this vertical.

GPU	%	AI Score
AMD Radeon RX 6900 XT	106%	3.3
AMD Radeon RX 7800 XT	106%	3.3
NVIDIA GeForce RTX 4060 Ti 16GB	103%	3.2
GeForce RTX 5070	103%	3.2
NVIDIA GeForce RTX 4070 Super	100%	3.1
NVIDIA GeForce RTX 4070	100%	3.1
NVIDIA GeForce RTX 4070 Ti	97%	3
Intel Arc A770 Limited Edition	94%	2.9
NVIDIA TITAN V	94%	2.9

One tier up: GeForce RTX 5070 (+3%) · compare head-to-head
One tier down: NVIDIA GeForce RTX 4070 (0%) · compare head-to-head
Best value alternative ($349): Intel Arc A770 Limited Edition (-6%)

Same card, other workloads: NVIDIA GeForce RTX 4070 Super Gaming benchmarks

← All AI & Machine Learning GPU rankings

The silicon

Transistors	35,800 million
Die size	294.5 mm²
Process node	4 nm
Fabricated by	TSMC
Transistor density	121.6 million per mm²

Denser than 91% 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	19.5 min	46.03 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), 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).