Side-by-side simulation · recommended settings
RTX 3090 vs RTX 5090 local LLM performance and electricity rate comparison
If cost-effectiveness is a priority within 24GB, the 3090 is advantageous, and if 27B speed and 32GB storage space are important, the 5090 is advantageous.
Choose devices and a model
Expand comparison settings
Same 117output tokens. Only evidence-qualified acceleration is selected automatically; runtime formats are shown on each device.
Left
ReadyRTX 3090 24GB
Press Start above to generate the same answer on both devices.
Right
ReadyRTX 5090 32GB
Press Start above to generate the same answer on both devices.
With these settings, RTX 5090 32GB finishes the full answer About 2.7× faster.
Compare from input processing to completion of 117 token response.
Which one fits my needs?
Answer completion
RTX 5090 32GB
At the estimate midpoint, it finishes the same answer about 2.7× faster.
Prompt processing
RTX 5090 32GB
The estimated input-processing midpoint is higher at 6,710 tok/s.
Image and video generation
Check the media model
LLM speed does not tell you media-generation performance. Choose the image or video model and resolution separately.
Runtime
Settings for your hardware
Strata 0.1.28 · IQ3_S · MTP · SSD PLE / Strata 0.1.41 · IQ3_S · MTP-6 · INT8 KV · SSD PLE. When runtime paths differ, the speed gap also includes software and model-format differences.
Estimated power draw
RTX 3090 24GB
Estimated LLM power draw is lower at about 420 W. Noise and physical size need a separate check.
Local pricing
RTX 5090 32GB costs about 675 × KRW 10,000 more at the reference-price midpoint, with an estimated answer time about 63% shorter.
Before choosing hardware
| Measure | RTX 3090 24GB | RTX 5090 32GB |
|---|---|---|
| Available fast memory | 22.5GB | 30.5GB |
| Memory bandwidth | 936GB/s | 1792GB/s |
| Estimated total time | 3.3 s | 1.2 s |
| Estimated sustained LLM load | about 420W | about 620W |
| Korean price range (KRW) | 239–239 × KRW 10,000 | 899–929 × KRW 10,000 |
Estimated ranges for one user. Multi-GPU and multi-device results depend on the runtime and interconnect.