NVIDIA GeForce RTX 3060 vs GeForce RTX 4080 Super, AI & Machine Learning Comparison
GeForce RTX 4080 Super wins 6 of 12 benchmarks, averaging 123.9% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
What the numbers say
The gap is widest in Stable Diffusion XL, where GeForce RTX 4080 Super leads by 210% (2.94 vs 9.12 images/min); the closest fight is Llama 3.1 8B (93% apart); VRAM decides part of this one: GeForce RTX 4080 Super runs 6 of our 12 AI workloads while the other card runs 4, models that don't fit score zero.
Benchmark results head-to-head
| Benchmark | NVIDIA GeForce RTX 3060 | GeForce RTX 4080 Super | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 102.04 | 197.53 | -48% |
| Llama 3.1 8B tok/s | 65.36 | 126.29 | -48% |
| Qwen2.5-Coder 14B tok/s | 35.52 | 70.55 | -50% |
| Qwen3 32B tok/s | 0 | 0 | n/a |
| Llama 3.3 70B tok/s | 0 | 0 | n/a |
| Stable Diffusion XL images/min | 2.94 | 9.12 | -68% |
| Z-Image Turbo images/min | 0 | 0.75 | n/a |
| FLUX.1 dev images/min | 0 | 0 | n/a |
| FLUX.1 Kontext dev images/min | 0 | 0 | n/a |
| Qwen-Image-Edit images/min | 0 | 0 | n/a |
| LTX-Video (distilled) frames/s | 0 | 1.42 | n/a |
| Wan 2.2 5B (720p) frames/s | 0 | 0 | n/a |
Whole-job comparison
How long each card takes to finish a complete pipeline, not just one model. NVIDIA GeForce RTX 3060 is faster on 0 of 1; GeForce RTX 4080 Super on 1.
| Workflow | NVIDIA GeForce RTX 3060 | GeForce RTX 4080 Super | Difference | Cost per run |
|---|---|---|---|---|
| Full codebase review | 28.2 min | 14.2 min | GeForce RTX 4080 Super 1.99x faster | $0.016 vs $0.066 |
Renting by the hour, NVIDIA GeForce RTX 3060 finishes 1 of 1 cheaper. The quicker card is not automatically the cheaper way to get the work done.
Cost to rent
| Card | Per hour |
|---|---|
| NVIDIA GeForce RTX 3060 | $0.034 |
| GeForce RTX 4080 Super | $0.280 |
NVIDIA GeForce RTX 3060 is 8.24x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.
Specifications compared
| NVIDIA GeForce RTX 3060 | GeForce RTX 4080 Super | |
|---|---|---|
| VRAM | 12GB | 16GB |
| Transistors | 12,000M | 45,900M |
| Die size | 276 mm² | 378.6 mm² |
| Transistor density | 43.5 M/mm² | 121.2 M/mm² |
| Architecture | Ampere (GA106) | Ada Lovelace |
| Memory bandwidth | 360 GB/s | 736 GB/s |
| Boost clock | 1,777 MHz | 2,505 MHz |
| TDP | 170 W | 320 W |
| Launch MSRP | $329 | $999 |
| Release | 2021-02-25 | 2024-01-31 |
FAQ
- Which is better for ai & machine learning: NVIDIA GeForce RTX 3060 or GeForce RTX 4080 Super?
- GeForce RTX 4080 Super performs better for ai & machine learning, winning 6 of 12 benchmarks in our suite with an average 123.9% advantage.
- What are the main hardware differences between NVIDIA GeForce RTX 3060 and GeForce RTX 4080 Super?
- NVIDIA GeForce RTX 3060 has 12GB VRAM and a 170W TDP, while GeForce RTX 4080 Super has 16GB VRAM and a 320W TDP.
- Does VRAM matter more than speed between NVIDIA GeForce RTX 3060 and GeForce RTX 4080 Super?
- For AI, yes, GeForce RTX 4080 Super fits 2 more of our 12 workloads than NVIDIA GeForce RTX 3060. A model that exceeds VRAM doesn't run slower, it doesn't run at all, so the card that fits the model wins that workload outright.
- Where is the biggest performance difference between NVIDIA GeForce RTX 3060 and GeForce RTX 4080 Super?
- Stable Diffusion XL: GeForce RTX 4080 Super leads by roughly 210% (2.94 vs 9.12 images/min) in our testing.
NVIDIA GeForce RTX 3060 full review · GeForce RTX 4080 Super full review · All AI & Machine Learning rankings