Hardware comparison
NVIDIA RTX 4060 (8GB) vs AMD RX 9070 (16GB) 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 RTX 4060 (8GB) | AMD RX 9070 (16GB) |
|---|---|---|
| Memory | 8.0 GB | 16.0 GB (better for this comparison) |
| Bandwidth | 272 GB/s | 645 GB/s (better for this comparison) |
| Price (approx) | $530 (better for this comparison)GPU only · host PC required, sold separately | $569GPU only · host PC required, sold separately |
| LLMs it runs | 23 of 69 | 48 of 69 (better for this comparison) |
| Best model it runs | Gemma 3 12BQ2_K · estimated 34–51 tok/s | Gemma 4 31BQ2_K · estimated 33–50 tok/s |
Both prices cover GPU cards only. A host PC is required and its cost is excluded. 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 AMD RX 9070 (16GB) runs 25 more of the tracked models (48 vs 23), thanks to its 16.0 GB of memory. The AMD RX 9070 (16GB) has more memory bandwidth (645 GB/s). Higher bandwidth can help generation speed, but model, quant, architecture and runtime also affect the estimates.