Most people asking this question are not trying to benchmark Llama on a Sunday. They are trying to decide if they should drop fifteen hundred dollars because the internet said everyone needs an "AI PC."
You probably don't.
If your whole workflow is email, documents, and a browser tab that talks back to you, stop reading and close the shopping cart. The machine you have is fine. Cloud tools are good. That is not a hot take. It is the truth for most knowledge work.
When cloud is the right answer
Cloud wins on simplicity. You open a tab. You type. You get an answer.
- You use AI a few times a week, not all day.
- You do not care whether prompts leave your network.
- You want the newest flagship model on day one without downloading fifty gigabytes.
- You are still figuring out what you would even ask a local model to do.
For that profile, read our local vs cloud cost guide anyway. Not because you are building a rig, but because it names real hourly burn rates. That math is how you avoid guilt-buying a GPU.
When local hardware earns its shelf space
Local is not magic. It is a trade.
- Privacy. Prompts and files stay on hardware you control. That matters for legal, medical, or anything you would not paste into a shared SaaS dashboard.
- Heavy daily use. If you are running assistants across most of the workday, cloud tabs turn into a line item. Local shifts cost to electricity and amortized hardware.
- Offline or flaky internet. Airplanes, rural links, lab networks. If you have lived it, you know.
- Same model, same settings, every time. Reproducibility beats "whatever version the API shipped Tuesday."
None of that requires you to enjoy reading driver release notes. It requires you to know why you are buying silence from the cloud bill.
What enough computer looks like (no jargon wall)
You do not need to memorize quantization on day one. You need a rough bucket. Small chat models (think single-digit billions of parameters) are the on-ramp. Big reasoning models (tens of billions) are the deep end. More parameters generally means more memory, slower responses on modest hardware, and a higher price tag for parts.
Our model pages spell out VRAM-style requirements per format. If you are shopping blind, start there, pick one model you actually care about, then work backward. That order matters. Hardware-first shopping is how people end up with a pretty box that wheezes on the one model they wanted.
When we tell you to wait
If you are not sure what you would run locally, wait. Borrow a machine. Try cloud. Sketch three real tasks. Then decide.
The worst outcome is not "you used ChatGPT." The worst outcome is a $2,000 regret purchase that sits under the desk while you still do everything in a browser.
Next steps: how to read a retail listing, Mac vs Windows for beginners, or how to choose your first AI GPU once you know you are actually building.
