RTX 4090 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 4090 | RTX 4080 Super |
|---|---|---|
| Memory | 24 GB VRAM | 16 GB VRAM |
| Brand | NVIDIA | NVIDIA |
| Compatible models (Q4) | 178 models in the catalog | 143 models in the catalog |
| Largest model (Q4) | Salamandra 40B Instruct (40B) | 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)
Alternative purchase: GMKtec EVO-X2 64 GB / 1 TB (Ryzen AI Max+ 395). A mini PC is a complete machine, not a replacement board; check memory and software compatibility.
Purchase alternative: RTX 5080 16 GB.
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Frequently asked questions
RTX 4090 or RTX 4080 Super for running an LLM locally?
For local use, the VRAM premium. The RTX 4090 (24 GB) runs larger models than the RTX 4080 Super (16 GB).
What’s the largest model that RTX 4090 can run?
Up to Salamandra 40B Instruct (40B) in Q4 quantization, with its 24 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.