AMD and NVIDIA both want the same headline: local AI on a $299 GPU. The RX 9060 XT and RTX 5060 landed within weeks of each other. Same sticker price at 8 GB. Very different software reality.
8 GB at $299
| GPU | VRAM | Bandwidth | Street | Viable models* |
|---|---|---|---|---|
| RX 9060 XT 8GB | 8 GB | 256 GB/s | $299 | 16 |
| RTX 5060 8GB | 8 GB | 448 GB/s | $299 | 32 |
*Viable model configs in our compatibility matrix (fits in VRAM, not rated not_viable). Counts include estimated RTX 5060 rows until independent benchmarks replace them.
NVIDIA ships higher memory bandwidth at the same 8 GB price point (448 GB/s vs 256 GB/s). In practice NVIDIA's stack is the default recommendation in every beginner guide for a reason. You will spend fewer evenings debugging why a quant file loads on CUDA but not ROCm.
16 GB tier: different math
NVIDIA splits 16 GB across the RTX 5060 Ti at $429. AMD keeps 16 GB on the RX 9060 XT at $349. That $80 delta buys CUDA peace of mind, not extra VRAM.
| GPU | TDP | Backend | Viable models* |
|---|---|---|---|
| RX 9060 XT 16GB | 150 W | Vulkan / ROCm (beta) | 46 |
| RTX 5060 Ti 16GB | 180 W | CUDA (production) | 30 |
When AMD wins
- You already run Linux and enjoy tuning ROCm or Vulkan flags.
- You want 16 GB under $400 and VRAM matters more than plug-and-play.
- You accept that some new models launch CUDA-first and arrive on AMD weeks later.
When NVIDIA wins
- You are new to local AI and want Ollama to "just work."
- You use Windows and do not want to maintain separate driver stacks.
- You value estimated matrix coverage today over theoretical bandwidth on paper.
Still undecided? Start on the GPU buying guide and filter by the models you actually plan to run. The card that fits your model list beats the card that wins a spec sheet.
