Hardware comparison
NVIDIA RTX 4080 (16GB) vs NVIDIA RTX 5080 (16GB) for local LLMs
How the two stack up for running open-source LLMs locally — memory, bandwidth, price, and how many of the 69 tracked models each one can run.
Scroll sideways to compare both machines. Keyboard: focus the table, then use the arrow keys. Metric names stay visible.
| Hardware | NVIDIA RTX 4080 (16GB) | NVIDIA RTX 5080 (16GB) |
|---|---|---|
| Memory | 16.0 GB | 16.0 GB |
| Bandwidth | 717 GB/s | 960 GB/s (better for this comparison) |
| Price (approx) | $1,549GPU only · host PC required, sold separately | $1,399 (better for this comparison)GPU only · host PC required, sold separately |
| LLMs it runs | 48 of 69 | 48 of 69 |
| Best model it runs | Gemma 4 31BQ2_K · estimated 37–55 tok/s | Gemma 4 31BQ2_K · estimated 48–71 tok/s |
Both prices cover GPU cards only. A host PC is required and its cost is excluded. Prices are approximate catalog estimates; check current configurations and prices before buying.
Both estimated speeds use the same model and quant shown above. Estimates use 4,096 context tokens, llama.cpp and one stream.
The NVIDIA RTX 4080 (16GB) and NVIDIA RTX 5080 (16GB) run the same number of tracked models. Compare their ecosystem and purchase scope before price. The NVIDIA RTX 5080 (16GB) has more memory bandwidth (960 GB/s). Higher bandwidth can help generation speed, but model, quant, architecture and runtime also affect the estimates.