Hardware comparison
NVIDIA RTX 4070 (12GB) vs NVIDIA RTX 4090 (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 | NVIDIA RTX 4070 (12GB) | NVIDIA RTX 4090 (24GB) |
|---|---|---|
| Memory | 12.0 GB | 24.0 GB (better for this comparison) |
| Bandwidth | 504 GB/s | 1008 GB/s (better for this comparison) |
| Price (approx) | $549 (better for this comparison)GPU only · host PC required, sold separately | $2,999GPU only · host PC required, sold separately |
| LLMs it runs | 30 of 69 | 51 of 69 (better for this comparison) |
| Best model it runs | Mistral Small 3.2 24BQ2_K · estimated 35–53 tok/s | Gemma 4 31BQ3_K_M · estimated 41–62 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 and quants differ. These estimated speeds are not a like-for-like comparison. Estimates use 4,096 context tokens, llama.cpp and one stream.
The NVIDIA RTX 4090 (24GB) runs 21 more of the tracked models (51 vs 30), thanks to its 24.0 GB of memory. The NVIDIA RTX 4090 (24GB) has more memory bandwidth (1008 GB/s). Higher bandwidth can help generation speed, but model, quant, architecture and runtime also affect the estimates.