GeForce RTX 5080 vs GeForce RTX 5090 for Local AI
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Which GPU is better for local AI workloads?
The 5090's 32GB runs 70B LLMs at Q4 and 32B models at Q8 — impossible on the 5080's 16GB. Its 1792 GB/s decodes tokens roughly twice as fast. The 5080 at $999, 360W, and standard two-slot sizing is the practical enthusiast pick; the 5090 at 575W and $1999 is the no-compromise local-AI flagship.
Spec comparison: what actually differs
The table below is computed live from our hardware database. Positive deltas favor the GeForce RTX 5080.
| Specification | GeForce RTX 5080 | GeForce RTX 5090 | Difference |
|---|---|---|---|
| VRAM | 16 | 32 | -50% |
| Memory bandwidth | 960 | 1792 | -46% |
| Memory type | GDDR7 | GDDR7 | — |
| Memory bus | 256 | 512 | — |
| TDP | 360 | 575 | -37% |
| CUDA cores | 10752 | 21760 | -51% |
| Architecture | Blackwell | Blackwell | — |
| Launch MSRP | $999 | $1,999 | -50% |
| Street price | $999 | $1,999 | -50% |
What about price?
Which one should you buy for LLMs and image generation?
GeForce RTX 5080
Buy the 5080 unless you specifically need 70B-class local models.
Full specs & benchmarks →GeForce RTX 5090
Buy the 5090 if 70B at Q4 or maximum image throughput justifies $1999 and a 575W, multi-slot build.
Full specs & benchmarks →Is it faster for LLM inference?
70B at Q4 fits only on the 5090 (32GB). At 16GB the 5080 tops out at 14B Q8 / 32B Q4-tight. Where both run the same model, the 5090 decodes ~1.9× faster on bandwidth.
How does it handle image generation?
Flux and SDXL with heavy LoRA stacks are effortless on 32GB; the 5080 handles them well with occasional offloading.
Which AI models fit on each card?
Computed from our model VRAM database at Q4 quantization: GeForce RTX 5080 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
Can the RTX 5080 run 70B models?
Not fully in VRAM — 70B at Q4 needs about 40GB. It offloads to system RAM with a large speed penalty. The 5090's 32GB holds 70B Q4 only with tight quantization (IQ2/IQ3).
Is the 5090 twice as fast as the 5080 for AI?
On bandwidth-bound LLM decode, close: 1792 vs 960 GB/s is 1.87×. On image generation the gap is smaller because compute, not just bandwidth, is shared.
What PSU does each need?
Plan 850W+ for the 575W 5090 and 650–750W for the 360W 5080 in single-GPU builds.