RTX 5080 vs. RTX 4080 Super: which GPU for local AI?
Focused comparison Local LLM : we're looking at what really matters for running models—VRAM above all, then generation speed and price. Purchase verdict at the end.
Updated on 09/10/2026
Comparison at a glance
| Criterion | RTX 5080 | RTX 4080 Super |
|---|---|---|
| Memory | 16 GB VRAM | 16 GB VRAM |
| Brand | NVIDIA | NVIDIA |
| Compatible models (Q4) | 143 models in the catalog | 143 models in the catalog |
| Largest model (Q4) | Qwen 3.8 27B Obliterated (28B) | Qwen 3.8 27B Obliterated (28B) |
Which one should you choose to run an LLM?
Golden rule: with the same budget, always choose the GPU with the most VRAM. A model that exceeds the VRAM limit collapses in speed (CPU offloading). VRAM determines the size of the model; computing power mainly dictates the Speed.
Where to buy (up-to-date pricing and stock)
Purchase alternative: RTX 5080 16 GB.
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Frequently asked questions
RTX 5080 or RTX 4080 Super for running an LLM locally?
For local use, the VRAM prime. The RTX 5080 (16 GB) runs larger models than the RTX 4080 Super (16 GB).
What is the largest model RTX 5080 can run?
Up to Qwen 3.8 27B Obliterated (28B) with Q4 quantization, using 16 GB.
Should you buy used?
For LLMs, a used GPU with more VRAM often beats a newer card with less memory. Check its condition and warranty.