GPU comparison
MacBook Air/Pro M4 (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 64 tracked models each one can run.
| MacBook Air/Pro M4 (16GB) | NVIDIA RTX 5080 (16GB) | |
|---|---|---|
| Memory | 16.0 GB | 16.0 GB |
| Bandwidth | 120 GB/s | 960 GB/s |
| Price (approx) | $1,199 | $1,399 |
| LLMs it runs | 27 of 64 | 45 of 64 |
| Best model it runs | Devstral Small 2 24B · 8–12 tok/s | Qwen3.8 27B · 54–82 tok/s |
The NVIDIA RTX 5080 (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 5080 (16GB) has more memory bandwidth (960 GB/s), so it generates tokens faster at the same model and quant.