GPU comparison
MacBook Air/Pro M5 (16GB) 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 64 tracked models each one can run.
| MacBook Air/Pro M5 (16GB) | NVIDIA RTX 4080 (16GB) | |
|---|---|---|
| Memory | 16.0 GB | 16.0 GB |
| Bandwidth | 153 GB/s | 717 GB/s |
| Price (approx) | $1,099 | $1,549 |
| LLMs it runs | 27 of 64 | 45 of 64 |
| Best model it runs | Devstral Small 2 24B · 10–15 tok/s | Qwen3.8 27B · 42–63 tok/s |
The NVIDIA RTX 4080 (16GB) runs 18 more of the tracked models (45 vs 27). With the same nominal memory, more of it is usable for model weights on this architecture. The NVIDIA RTX 4080 (16GB) has more memory bandwidth (717 GB/s), so it generates tokens faster at the same model and quant.