Hardware comparison
MacBook Air/Pro M5 (24GB) vs NVIDIA DGX Spark (GB10, 128GB) 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 | MacBook Air/Pro M5 (24GB) | NVIDIA DGX Spark (GB10, 128GB) |
|---|---|---|
| Memory | 24.0 GB | 128.0 GB (better for this comparison) |
| Bandwidth | 153 GB/s | 273 GB/s (better for this comparison) |
| Price (approx) | $1,299 (better for this comparison)Complete system | $4,699Complete system |
| LLMs it runs | 49 of 69 | 62 of 69 (better for this comparison) |
| Best model it runs | Gemma 4 31BQ2_K · estimated 8–11 tok/s | Gemma 4 31BQ2_K · estimated 13–20 tok/s |
Both prices cover complete systems. 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.
The NVIDIA DGX Spark (GB10, 128GB) runs 13 more of the tracked models (62 vs 49), thanks to its 128.0 GB of memory. The NVIDIA DGX Spark (GB10, 128GB) has more memory bandwidth (273 GB/s). Higher bandwidth can help generation speed, but model, quant, architecture and runtime also affect the estimates.