NVIDIA GeForce RTX 3090 vs GeForce RTX 5080, AI & Machine Learning Comparison
GeForce RTX 5080 wins 5 of 12 benchmarks, averaging 9.3% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
What the numbers say
The gap is widest in LTX-Video (distilled), where GeForce RTX 5080 leads by 54% (2.17 vs 3.34 frames/s); the closest fight is Llama 3.1 8B (4% apart); VRAM decides part of this one: NVIDIA GeForce RTX 3090 runs 8 of our 12 AI workloads while the other card runs 6, models that don't fit score zero.
Benchmark results head-to-head
| Benchmark | NVIDIA GeForce RTX 3090 | GeForce RTX 5080 | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 206.67 | 215.89 | -4% |
| Llama 3.1 8B tok/s | 144.9 | 150.71 | -4% |
| Qwen2.5-Coder 14B tok/s | 78.79 | 81.97 | -4% |
| Qwen3 32B tok/s | 37.95 | 0 | n/a |
| Llama 3.3 70B tok/s | 0 | 0 | n/a |
| Stable Diffusion XL images/min | 7.46 | 8.86 | -16% |
| Z-Image Turbo images/min | 3.825 | 2.7 | +42% |
| 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 | 2.17 | 3.34 | -35% |
| Wan 2.2 5B (720p) frames/s | 0.22 | 0 | n/a |
Whole-job comparison
How long each card takes to finish a complete pipeline, not just one model. NVIDIA GeForce RTX 3090 is faster on 0 of 1; GeForce RTX 5080 on 1.
| Workflow | NVIDIA GeForce RTX 3090 | GeForce RTX 5080 | Difference | Cost per run |
|---|---|---|---|---|
| Full codebase review | 12.7 min | 12.2 min | GeForce RTX 5080 1.04x faster | $0.015 vs $0.027 |
Renting by the hour, NVIDIA GeForce RTX 3090 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 3090 | $0.069 |
| GeForce RTX 5080 | $0.135 |
NVIDIA GeForce RTX 3090 is 1.96x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.
Specifications compared
| NVIDIA GeForce RTX 3090 | GeForce RTX 5080 | |
|---|---|---|
| VRAM | 24GB | 16GB |
| Transistors | 28,300M | 45,600M |
| Die size | 628.4 mm² | 378 mm² |
| Transistor density | 45 M/mm² | 120.6 M/mm² |
| Architecture | Ampere (GA102) | Blackwell (GB203) |
| Memory bandwidth | 936.2 GB/s | 960 GB/s |
| Boost clock | 1,695 MHz | 2,617 MHz |
| TDP | 350 W | 360 W |
| Launch MSRP | $1,499 | $999 |
| Release | 2020-09-24 | 2025-01-30 |
FAQ
- Which is better for ai & machine learning: NVIDIA GeForce RTX 3090 or GeForce RTX 5080?
- GeForce RTX 5080 performs better for ai & machine learning, winning 5 of 12 benchmarks in our suite with an average 9.3% advantage.
- What are the main hardware differences between NVIDIA GeForce RTX 3090 and GeForce RTX 5080?
- NVIDIA GeForce RTX 3090 has 24GB VRAM and a 350W TDP, while GeForce RTX 5080 has 16GB VRAM and a 360W TDP.
- Does VRAM matter more than speed between NVIDIA GeForce RTX 3090 and GeForce RTX 5080?
- For AI, yes, NVIDIA GeForce RTX 3090 fits 2 more of our 12 workloads than GeForce RTX 5080. 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 3090 and GeForce RTX 5080?
- LTX-Video (distilled): GeForce RTX 5080 leads by roughly 54% (2.17 vs 3.34 frames/s) in our testing.
NVIDIA GeForce RTX 3090 full review · GeForce RTX 5080 full review · All AI & Machine Learning rankings