Hardware comparison
Mac mini M6 (16GB) vs NVIDIA RTX 4070 (12GB) 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 (16GB) | NVIDIA RTX 4070 (12GB) |
|---|---|---|
| Memory | 16.0 GB (better for this comparison) | 12.0 GB |
| Bandwidth | 153 GB/s | 504 GB/s (better for this comparison) |
| Price (approx) | $899Complete system | $549GPU only · host PC required, sold separately |
| LLMs it runs | 30 of 69 | 30 of 69 |
| Best model it runs | Mistral Small 3.2 24BQ2_K · estimated 10–15 tok/s | Mistral Small 3.2 24BQ2_K · estimated 35–53 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.
Both estimated speeds use the same model and quant shown above. Estimates use 4,096 context tokens, llama.cpp and one stream.
Both run the same number of models, but the Mac mini M6 (16GB) has more memory (16.0 GB), so it can hold larger models at higher quality. The NVIDIA RTX 4070 (12GB) has more memory bandwidth (504 GB/s). Higher bandwidth can help generation speed, but model, quant, architecture and runtime also affect the estimates.