GeForce RTX 5070 vs GeForce RTX 4070 for Local AI
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Which GPU is better for local AI workloads?
Both are 12GB cards — enough for 8B–12B LLMs, SDXL, and Whisper, short of 14B at Q8. The 5070's 672 GB/s versus 504 GB/s makes every workload that fits run faster. TDP rises slightly from 200W to 250W.
Spec comparison: what actually differs
The table below is computed live from our hardware database. Positive deltas favor the GeForce RTX 5070.
| Specification | GeForce RTX 5070 | GeForce RTX 4070 | Difference |
|---|---|---|---|
| VRAM | 12 | 12 | — |
| Memory bandwidth | 672 | 504 | +33% |
| Memory type | GDDR7 | GDDR6X | — |
| Memory bus | 192 | 192 | — |
| TDP | 250 | 200 | +25% |
| CUDA cores | 6144 | 5888 | +4% |
| Architecture | Blackwell | Ada Lovelace | — |
| Launch MSRP | $549 | $549 | — |
| Street price | $549 | $549 | — |
What about price?
Both launched at $549 MSRP.
Which one should you buy for LLMs and image generation?
Is it faster for LLM inference?
Same capacity, faster decode on the 5070 by roughly the bandwidth gap.
How does it handle image generation?
SDXL faster on 5070; Flux marginal on both 12GB cards.
Which AI models fit on each card?
Computed from our model VRAM database at Q4 quantization: GeForce RTX 5070 has 12 GB, GeForce RTX 4070 has 12 GB.
Fit on both cards
FLUX.1 dev
Llama 3.1 8B
Stable Diffusion 3.5 Large
Stable Diffusion XL 1.0
Whisper large-v3
Coqui XTTS-v2
Frequently asked questions
5070 vs 4070 — which for local LLMs?
The 5070: both have 12GB, but 672 vs 504 GB/s bandwidth means faster token generation on the same models.