Local vs cloud AI: when to run models on your own rig
Run AI local for privacy, no per-use eddies, and offline work if your rig is chromed up, or jack into the cloud when you want the most capable models with zero setup, choom.
The short version: run AI on your own rig when privacy, cost, or offline use matter most and your chrome can hang. Jack into the cloud when you want the most capable models with no setup and do not mind that your data deltas off your machine. Most chooms end up running both, picking the right one for each job.
Neither choice wins in every way. They trade off different things, and once you clock the trade-offs the call gets easy. Let us lay them side by side, choom.
What is the difference between local and cloud AI?
A local model runs entirely on your own rig. Nothing you type leaves the machine, there is no per-use fee, and it keeps running with the net off. The catch is that it needs reasonably chromed hardware, and even preem local models are usually less capable than the very best cloud ones.
A cloud model runs on a megacorp’s servers and you reach it over the net. These are the most capable assistants going and they need no special chrome from you. The trade-offs are that your data deltas off your machine and heavy usage can burn eddies.
How do local and cloud AI compare?
| What matters | Local (your rig) | Cloud (over the net) |
|---|---|---|
| Privacy | Strong, data stays on your device | Data leaves your machine |
| Cost | No per-use fee once set up | Usage can burn eddies |
| Offline | Works with no net | Needs a connection |
| Hardware needed | Needs a decent rig | None, runs on their servers |
| Capability | Good, usually below the best cloud models | The most capable available |
When should I run a model locally?
Go local when the work is sensitive or routine. If you are summarising private notes, drafting something you would rather keep off some other crew’s servers, or running somewhere with patchy net, a local model is a nova fit. It also shines for high-volume little tasks, since there is no bill that grows with use, so your eddies stay in your pocket.
Getting started is easier than it sounds. Rigs like Ollama and LM Studio handle the fiddly parts and let you pull down and jack in a model in a few clicks. You will want a fairly modern machine with enough memory, but you do not need to be a netrunner.
When is cloud AI the better choice?
Reach for the cloud when you want the strongest possible answer or the smoothest setup. For hard reasoning, careful writing, or complex problems, the best cloud assistants like Claude still lead the pack, and there is nothing to install. If you only jack in now and then, the convenience usually outweighs the cost.
Just remember the privacy trade-off and keep your secrets out of the corpo box. Plenty of chooms mix both: a local model for private or repetitive jobs, and a cloud model when they need the top tier. If you want a wider set of practical picks, the everyday AI toolkit gathers more rigs worth knowing.
The takeaway: there is no single winner, choom. Match the rig to the job, lean local for privacy and offline work, and lean cloud for raw capability and convenience.