NVIDIA GeForce RTX 4090 vs GeForce RTX 5080, AI & Machine Learning Comparison
NVIDIA GeForce RTX 4090 wins 8 of 12 benchmarks, averaging 58.3% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
What the numbers say
The gap is widest in Z-Image Turbo, where NVIDIA GeForce RTX 4090 leads by 175% (7.425 vs 2.7 images/min); the closest fight is Llama 3.1 8B (14% apart); VRAM decides part of this one: NVIDIA GeForce RTX 4090 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 4090 | GeForce RTX 5080 | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 260.54 | 215.89 | +21% |
| Llama 3.1 8B tok/s | 171.29 | 150.71 | +14% |
| Qwen2.5-Coder 14B tok/s | 95.12 | 81.97 | +16% |
| Qwen3 32B tok/s | 44.28 | 0 | n/a |
| Llama 3.3 70B tok/s | 0 | 0 | n/a |
| Stable Diffusion XL images/min | 16.28 | 8.86 | +84% |
| Z-Image Turbo images/min | 7.425 | 2.7 | +175% |
| 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 | 4.7 | 3.34 | +41% |
| Wan 2.2 5B (720p) frames/s | 0.43 | 0 | n/a |
Whole-job comparison
How long each card takes to finish a complete pipeline, not just one model. NVIDIA GeForce RTX 4090 is faster on 1 of 1; GeForce RTX 5080 on 0.
| Workflow | NVIDIA GeForce RTX 4090 | GeForce RTX 5080 | Difference | Cost per run |
|---|---|---|---|---|
| Full codebase review | 10.5 min | 12.2 min | NVIDIA GeForce RTX 4090 1.16x faster | $0.027 vs $0.027 |
Renting by the hour, NVIDIA GeForce RTX 4090 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 4090 | $0.155 |
| GeForce RTX 5080 | $0.135 |
GeForce RTX 5080 is 1.15x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.
Specifications compared
| NVIDIA GeForce RTX 4090 | GeForce RTX 5080 | |
|---|---|---|
| VRAM | 24GB | 16GB |
| Transistors | 76,300M | 45,600M |
| Die size | 608.5 mm² | 378 mm² |
| Process node | 4 nm | 4 nm |
| Transistor density | 125.4 M/mm² | 120.6 M/mm² |
| Architecture | Ada Lovelace | Blackwell (GB203) |
| Memory bandwidth | 1008 GB/s | 960 GB/s |
| Boost clock | 2,520 MHz | 2,617 MHz |
| TDP | 450 W | 360 W |
| Launch MSRP | $1,599 | $999 |
| Release | 2022-10-12 | 2025-01-30 |
FAQ
- Which is better for ai & machine learning: NVIDIA GeForce RTX 4090 or GeForce RTX 5080?
- NVIDIA GeForce RTX 4090 performs better for ai & machine learning, winning 8 of 12 benchmarks in our suite with an average 58.3% advantage.
- What are the main hardware differences between NVIDIA GeForce RTX 4090 and GeForce RTX 5080?
- NVIDIA GeForce RTX 4090 has 24GB VRAM and a 450W TDP, while GeForce RTX 5080 has 16GB VRAM and a 360W TDP.
- Does VRAM matter more than speed between NVIDIA GeForce RTX 4090 and GeForce RTX 5080?
- For AI, yes, NVIDIA GeForce RTX 4090 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 4090 and GeForce RTX 5080?
- Z-Image Turbo: NVIDIA GeForce RTX 4090 leads by roughly 175% (7.425 vs 2.7 images/min) in our testing.
NVIDIA GeForce RTX 4090 full review · GeForce RTX 5080 full review · All AI & Machine Learning rankings