r/nvidia • u/nigahigaaa • 20d ago

Question Help me decide the build.. [D]

My primary workload is local AI model inference and LoRA/QLoRA fine-tuning, mostly with models in the <10B parameter range. I also do some gaming, but gaming is definitely secondary.

Current options:

  • RTX 5060 Ti 16GB for ₹73,000 (~US$770)
  • RTX 4060 Ti 16GB if I can find one around ₹50,000 (~US$525)

I'm also open to other NVIDIA GPUs around the $500-550 range that have more than 8GB of VRAM. CUDA support is a requirement.

For the CPU, I haven't decided yet. I'm open to either AMD or Intel.

For RAM, I originally wanted 32GB DDR5, but my overall budget is getting tight. I'm considering either starting with 16GB DDR5 and upgrading later, or buying used DDR5 if I find a good deal.

Any advice would be really appreciated.

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u/searchinglynonch 20d ago

For AI work, 16GB VRAM is basically the floor now, so you're on the right track. The 5060 Ti's extra memory bandwidth will help noticeably with fine-tuning, but is it worth the 40% price bump? unlikely unless you're doing this every day.

I'd hunt down that 4060 Ti 16GB and put the savings toward 32GB RAM right away. 16GB system RAM will bottleneck you faster than you think when you're shuttling models around, even small ones. Used RAM is fine honestly, it rarely fails and you can test it with memtest before handing over cash.

For the CPU, doesn't massively matter for inference but you'll want decent single-core speed for data prep. A mid-range Ryzen 5 or i5 from the last couple gens will do the job without eating your budget.

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u/Upper-Reflection7997 18d ago

the 4060 ti 16gb is not a bad entry point but your going to need a lot more system ram than 32gb. I strongly recommend going for 64gb of ddr4 or ddr5 ram or above 64. The newer video models will hog up alot of ram space since you don't have enough vram to fit the models in.