Hardware comparison
NVIDIA DGX Spark (GB10, 128GB) vs NVIDIA RTX 4060 (8GB) 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 | NVIDIA DGX Spark (GB10, 128GB) | NVIDIA RTX 4060 (8GB) |
|---|---|---|
| Memory | 128.0 GB (better for this comparison) | 8.0 GB |
| Bandwidth | 273 GB/s (better for this comparison) | 272 GB/s |
| Price (approx) | $4,699Complete system | $530GPU only · host PC required, sold separately |
| LLMs it runs | 62 of 69 (better for this comparison) | 23 of 69 |
| Best model it runs | Gemma 4 31BQ2_K · estimated 13–20 tok/s | Gemma 3 12BQ2_K · estimated 34–51 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 models differ. These estimated speeds are not a like-for-like comparison. Estimates use 4,096 context tokens, llama.cpp and one stream.
The NVIDIA DGX Spark (GB10, 128GB) runs 39 more of the tracked models (62 vs 23), 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.