Side-by-side simulation · recommended settings
RTX 5070 vs RTX 5070 Ti: Does 4GB matter for local LLMs?
If your chosen model runs out of room in 12GB, check the 5070 Ti's extra 4GB first. For smaller models, weigh the 5070's cost against its speed.
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 5070 12GB
Press Start above to generate the same answer on both devices.
Right
ReadyRTX 5070 Ti 16GB
Press Start above to generate the same answer on both devices.
With these settings, RTX 5070 Ti 16GB finishes the full answer About 1.1× faster.
Compare from input processing to completion of 117 token response.
Which one fits my needs?
Answer completion
RTX 5070 Ti 16GB
At the estimate midpoint, it finishes the same answer about 1.1× faster.
Prompt processing
RTX 5070 Ti 16GB
The estimated input-processing midpoint is higher at 2,005 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 · Blackwell (CC 12.0) · CUDA · MTP · NVMe PLE · single GPU. When runtime paths differ, the speed gap also includes software and model-format differences.
Estimated power draw
RTX 5070 12GB
Estimated LLM power draw is lower at about 275 W. Noise and physical size need a separate check.
Local pricing
RTX 5070 Ti 16GB costs about 60 × KRW 10,000 more at the reference-price midpoint, with an estimated answer time about 13% shorter.
Before choosing hardware
| Measure | RTX 5070 12GB | RTX 5070 Ti 16GB |
|---|---|---|
| Available fast memory | 11GB | 15GB |
| Memory bandwidth | 672GB/s | 896GB/s |
| Estimated total time | 3.8 s | 3.3 s |
| Estimated sustained LLM load | About 275W | About 310W |
| Korean price range (KRW) | 116–129 × KRW 10,000 | 179–185 × KRW 10,000 |
Estimated ranges for one user. Multi-GPU and multi-device results depend on the runtime and interconnect.
The extra 4GB can also serve conversation headroom
VRAM holds both weights and the conversation's KV cache. A model that barely fits in 12GB may run out of room with longer input. Select the same model and increase context in steps to see whether 16GB expands model choice or enables longer conversations with the same model.
Use the same question for heavily compressed larger models
A smaller file can make a larger model runnable. Alongside capacity, check whether its answers preserve the requirements and code your usual questions need. Try both a fast smaller model and a more heavily compressed larger model to choose the combination that suits you.
Consider the next upgrade too
If you plan to keep moving to larger models, compare stopping at 16GB with moving to 24GB or more. Upgrading from a 5070 to a 5070 Ti and quickly hitting capacity again means paying for two changes. Check the model you need now and the one you expect to use soon.