Hardware comparison
Mac mini M6 (24GB) vs NVIDIA RTX 5090 (32GB) 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 | Mac mini M6 (24GB) | NVIDIA RTX 5090 (32GB) |
|---|---|---|
| Memory | 24.0 GB | 32.0 GB (better for this comparison) |
| Bandwidth | 170 GB/s | 1792 GB/s (better for this comparison) |
| Price (approx) | $1,099Complete system | $4,399GPU only · host PC required, sold separately |
| LLMs it runs | 49 of 69 | 52 of 69 (better for this comparison) |
| Best model it runs | Gemma 4 31BQ2_K · estimated 8–13 tok/s | Gemma 4 31BQ5_K_M · estimated 50–75 tok/s |
These prices cover different purchases: a GPU card excludes its required host PC; a complete system includes the machine. No price winner is marked. Prices are approximate catalog estimates; check current configurations and prices before buying.
The recommended quants differ. These estimated speeds are not a like-for-like comparison. Estimates use 4,096 context tokens, llama.cpp and one stream.
The NVIDIA RTX 5090 (32GB) runs 3 more of the tracked models (52 vs 49), thanks to its 32.0 GB of memory. The NVIDIA RTX 5090 (32GB) has more memory bandwidth (1792 GB/s). Higher bandwidth can help generation speed, but model, quant, architecture and runtime also affect the estimates.