Hardware comparison
Mac mini M6 (24GB) vs AMD RX 7900 XTX (24GB) 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) | AMD RX 7900 XTX (24GB) |
|---|---|---|
| Memory | 24.0 GB | 24.0 GB |
| Bandwidth | 170 GB/s | 960 GB/s (better for this comparison) |
| Price (approx) | $1,099Complete system | $949GPU only · host PC required, sold separately |
| LLMs it runs | 49 of 69 | 51 of 69 (better for this comparison) |
| Best model it runs | Gemma 4 31BQ2_K · estimated 8–13 tok/s | Gemma 4 31BQ3_K_M · estimated 40–60 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 AMD RX 7900 XTX (24GB) runs 2 more of the tracked models (51 vs 49). With the same nominal memory, more of it is usable for model weights on this architecture. The AMD RX 7900 XTX (24GB) has more memory bandwidth (960 GB/s). Higher bandwidth can help generation speed, but model, quant, architecture and runtime also affect the estimates.