GeForce RTX 5070 Ti vs GeForce RTX 5090 for Local AI
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Which GPU is better for local AI workloads?
The 5070 Ti is the value 16GB Blackwell card; the 5090 is the 32GB flagship that runs 70B-class LLMs with tight quantization. If your models fit 16GB, the 5070 Ti delivers most of the experience for $749. If you need 24GB+ capacity, only the 5090 (or used/pro alternatives) provides it in current GeForce lineups.
Spec comparison: what actually differs
The table below is computed live from our hardware database. Positive deltas favor the GeForce RTX 5070 Ti.
| Specification | GeForce RTX 5070 Ti | GeForce RTX 5090 | Difference |
|---|---|---|---|
| VRAM | 16 | 32 | -50% |
| Memory bandwidth | 896 | 1792 | -50% |
| Memory type | GDDR7 | GDDR7 | — |
| Memory bus | 256 | 512 | — |
| TDP | 300 | 575 | -48% |
| CUDA cores | 8960 | 21760 | -59% |
| Architecture | Blackwell | Blackwell | — |
| Launch MSRP | $749 | $1,999 | -63% |
| Street price | $749 | $1,999 | -63% |
What about price?
Which one should you buy for LLMs and image generation?
GeForce RTX 5070 Ti
Buy the 5070 Ti for the best 16GB value in the 50-series.
Full specs & benchmarks →GeForce RTX 5090
Buy the 5090 for 32GB-class model work — nothing else current matches it per card.
Full specs & benchmarks →Is it faster for LLM inference?
14B Q8 both; 32B Q4 and 70B IQ-class only on the 5090. Decode ~2× faster on 5090 (1792 vs 896 GB/s).
How does it handle image generation?
Heavy Flux pipelines, batching, and video models favor the 5090's 32GB.
Which AI models fit on each card?
Computed from our model VRAM database at Q4 quantization: GeForce RTX 5070 Ti has 16 GB, GeForce RTX 5090 has 32 GB.
Fit only on the GeForce RTX 5090 (32 GB)
Fit on both cards
Frequently asked questions
What models run on a 5090 but not a 5070 Ti?
32B LLMs at Q4 (~19GB) and tightly quantized 70B variants need the 5090's 32GB; the 5070 Ti's 16GB tops out at 14B Q8.