GeForce RTX 4070 vs GeForce RTX 4070 Ti SUPER for Local AI
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Which GPU is better for local AI workloads?
The capacity jump unlocks 14B models at Q8; the 33% bandwidth jump speeds all shared workloads. The 4070 remains the budget 12GB option. Both are efficient Ada cards (200W/285W).
Spec comparison: what actually differs
The table below is computed live from our hardware database. Positive deltas favor the GeForce RTX 4070.
| Specification | GeForce RTX 4070 | GeForce RTX 4070 Ti SUPER | Difference |
|---|---|---|---|
| VRAM | 12 | 16 | -25% |
| Memory bandwidth | 504 | 672 | -25% |
| Memory type | GDDR6X | GDDR6X | — |
| Memory bus | 192 | 256 | — |
| TDP | 200 | 285 | -30% |
| CUDA cores | 5888 | 8448 | -30% |
| Architecture | Ada Lovelace | Ada Lovelace | — |
| Launch MSRP | $549 | $799 | -31% |
| Street price | $549 | $799 | -31% |
What about price?
Launch MSRP: $549 (4070) versus $799 (4070 Ti SUPER).
Which one should you buy for LLMs and image generation?
NVIDIA · 2024
GeForce RTX 4070 Ti SUPER
Buy the 4070 Ti SUPER for 16GB class — but cross-shop the newer 5060 Ti 16GB/5070 Ti.
Full specs & benchmarks →Is it faster for LLM inference?
14B Q8 only on the Ti SUPER; shared models decode ~33% faster on it.
How does it handle image generation?
Flux workable on Ti SUPER's 16GB; marginal on 12GB.
Which AI models fit on each card?
Computed from our model VRAM database at Q4 quantization: GeForce RTX 4070 has 12 GB, GeForce RTX 4070 Ti SUPER has 16 GB.
Fit only on the GeForce RTX 4070 Ti SUPER (16 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
4070 or 4070 Ti SUPER for 14B models?
Ti SUPER — 14B at Q8 needs ~15GB, exceeding the 4070's 12GB.