NVIDIA GeForce RTX 3060 vs NVIDIA GeForce RTX 3080, AI & Machine Learning Comparison
NVIDIA GeForce RTX 3080 wins 10 of 22 benchmarks, averaging 82.7% faster.
Both cards' numbers are anchored estimates calibrated against our measured cards, pending first-party measurement. Treat small gaps as ties.
What the numbers say
The gap is widest in Qwen3 14B, where NVIDIA GeForce RTX 3080 leads by 95% (36.45 vs 71.02 tok/s); the closest fight is Stable Diffusion XL (62% apart); VRAM decides part of this one: NVIDIA GeForce RTX 3080 runs 34 of our 12 AI workloads while the other card runs 14, models that don't fit score zero.
Benchmark results head-to-head
| Benchmark | NVIDIA GeForce RTX 3060 | NVIDIA GeForce RTX 3080 | Difference |
|---|---|---|---|
| MiniCPM5 2B tok/s | 167.64 | 272.23 | -38% |
| LFM2.5 2.6B tok/s | 154.94 | 279.55 | -45% |
| Nemotron 3 Nano 4B tok/s | 100.43 | 189.44 | -47% |
| Qwen3 4B tok/s | 102.04 | 184.08 | -45% |
| Llama 3.1 8B tok/s | 65.36 | 125.85 | -48% |
| Qwen3 8B tok/s | 63.84 | 120.85 | -47% |
| Ornith 1.5 9B tok/s | 56.51 | 107.51 | -47% |
| Gemma 4 12B tok/s | 41.02 | 76.61 | -46% |
| Qwen2.5-Coder 14B tok/s | 35.52 | 0 | n/a |
| Qwen3 14B tok/s | 36.45 | 71.02 | -49% |
| Gemma 4 26B A4B tok/s | 0 | 0 | n/a |
| Qwen3 30B A3B tok/s | 0 | 0 | n/a |
| Gemma 4 31B tok/s | 0 | 0 | n/a |
| 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 | 4.76 | -38% |
| Z-Image Turbo images/min | 0 | 0 | n/a |
| FLUX.1 Kontext dev images/min | 0 | 0 | n/a |
| FLUX.1 dev images/min | 0 | 0 | n/a |
| Qwen-Image-Edit images/min | 0 | 0 | n/a |
| LTX-Video (distilled) frames/s | 0 | 0 | n/a |
| Wan 2.2 5B (720p) frames/s | 0 | 0 | n/a |
Cost to rent
| Card | Per hour |
|---|---|
| NVIDIA GeForce RTX 3060 | $0.056 |
| NVIDIA GeForce RTX 3080 | $0.109 |
NVIDIA GeForce RTX 3060 is 1.95x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.
Specifications compared
| NVIDIA GeForce RTX 3060 | NVIDIA GeForce RTX 3080 | |
|---|---|---|
| VRAM | 12GB | 10GB |
| Transistors | 12,000M | 28,300M |
| Die size | 276 mm² | 628.4 mm² |
| Process node | 8 nm | 8 nm |
| Transistor density | 43.5 M/mm² | 45 M/mm² |
| Architecture | Ampere (GA106) | Ampere (GA102) |
| Memory bandwidth | 360 GB/s | 760 GB/s |
| Boost clock | 1,777 MHz | 1,710 MHz |
| TDP | 170 W | 320 W |
| Launch MSRP | $329 | $699 |
| Release | 2021-02-25 | 2020-09-17 |
FAQ
- Which is better for ai & machine learning: NVIDIA GeForce RTX 3060 or NVIDIA GeForce RTX 3080?
- NVIDIA GeForce RTX 3080 performs better for ai & machine learning, winning 10 of 22 benchmarks in our suite with an average 82.7% advantage.
- What are the main hardware differences between NVIDIA GeForce RTX 3060 and NVIDIA GeForce RTX 3080?
- NVIDIA GeForce RTX 3060 has 12GB VRAM and a 170W TDP, while NVIDIA GeForce RTX 3080 has 10GB VRAM and a 320W TDP.
- Does VRAM matter more than speed between NVIDIA GeForce RTX 3060 and NVIDIA GeForce RTX 3080?
- For AI, yes, NVIDIA GeForce RTX 3080 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 NVIDIA GeForce RTX 3080?
- Qwen3 14B: NVIDIA GeForce RTX 3080 leads by roughly 95% (36.45 vs 71.02 tok/s) in our testing.
NVIDIA GeForce RTX 3060 full review · NVIDIA GeForce RTX 3080 full review · All AI & Machine Learning rankings