GPU comparison
MacBook Air/Pro M5 (32GB) vs NVIDIA RTX 4080 (16GB) for local LLMs
How the two stack up for running open-source LLMs locally — memory, bandwidth, price, and how many of the 34 tracked models each one can run.
| MacBook Air/Pro M5 (32GB) | NVIDIA RTX 4080 (16GB) | |
|---|---|---|
| Memory | 32.0 GB | 16.0 GB |
| Bandwidth | 153 GB/s | 717 GB/s |
| Price (approx) | $1,499 | $1,549 |
| LLMs it runs | 25 of 34 | 18 of 34 |
| Best model it runs | Gemma 4 31B · 6–9 tok/s | Gemma 4 26B-A4B (MoE) · 141–212 tok/s |
The MacBook Air/Pro M5 (32GB) runs 7 more of the tracked models (25 vs 18), thanks to its 32.0 GB of memory. The NVIDIA RTX 4080 (16GB) has more memory bandwidth (717 GB/s), so it generates tokens faster at the same model and quant.