Side-by-side simulation · recommended settings
RTX 5080 vs RTX 5090: Is 16GB enough for local AI?
The central choice is the capacity difference between 16GB and 32GB. Compare the 5080 first for smaller models; check the 5090's headroom when combining larger quantized files with long conversations.
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 5080 16GB
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 2.6× 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 2.6× 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 · Blackwell (CC 12.0) · CUDA · MTP · NVMe PLE · single GPU / 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 5080 16GB
Estimated LLM power draw is lower at about 352 W. Noise and physical size need a separate check.
Local pricing
RTX 5090 32GB costs about 679 × KRW 10,000 more at the reference-price midpoint, with an estimated answer time about 61% shorter.
Before choosing hardware
| Measure | RTX 5080 16GB | RTX 5090 32GB |
|---|---|---|
| Available fast memory | 15GB | 30.5GB |
| Memory bandwidth | 960GB/s | 1792GB/s |
| Estimated total time | 3.1 s | 1.2 s |
| Estimated sustained LLM load | About 352W | about 620W |
| Korean price range (KRW) | 231–239 × 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.
Exceeding 16GB changes the execution path
If the 5080 runs out of memory, options include a smaller quantization or moving part of the model to system RAM. File choice, CPU and RAM then matter together. Check whether the same file fits in the 5090's VRAM to judge how much its price premium reduces offloading.
Compare small and large models separately
Start with a model that runs on both cards and compare short-answer generation. Switch to the larger model you actually want and inspect placement and first response. Finally increase context to check conversation headroom after loading. This separates a speed upgrade from a capacity upgrade.
Include costs outside the graphics card
Even a card-only upgrade requires checking PSU capacity, cables and case space. Include a planned RAM upgrade too. Distinguish card prices below from the cost of a finished PC, and compare sustained power if the machine will stay on for long periods.