GPU comparison
MacBook Air/Pro M5 (24GB) 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 64 tracked models each one can run.
| MacBook Air/Pro M5 (24GB) | NVIDIA RTX 5080 (16GB) | |
|---|---|---|
| Memory | 24.0 GB | 16.0 GB |
| Bandwidth | 153 GB/s | 960 GB/s |
| Price (approx) | $1,299 | $1,399 |
| LLMs it runs | 45 of 64 | 45 of 64 |
| Best model it runs | Qwen3.8 27B · 9–13 tok/s | Qwen3.8 27B · 54–82 tok/s |
Both run the same number of models, but the MacBook Air/Pro M5 (24GB) has more memory (24.0 GB), so it can hold larger models at higher quality. The NVIDIA RTX 5080 (16GB) has more memory bandwidth (960 GB/s), so it generates tokens faster at the same model and quant.