Quick answer
Start with local AI when the task needs offline use or data kept on a computer you control and a small model can do the job. Choose cloud AI when convenience or a particular hosted model is more useful and sending the material to that provider is acceptable. You can use both for different tasks.
Comparison table
| Question | Local AI | Cloud AI |
|---|---|---|
| Where does inference happen? | On your machine or private infrastructure if configured locally. | On provider infrastructure. |
| Hardware required | A small model can use an existing laptop; larger models need more RAM or VRAM. | A device that can reach the service. |
| Setup burden | Download models and maintain the app and storage. | Manage an account, settings, and internet access. |
| Running cost | Hardware, electricity, and your setup time; existing hardware changes the calculation. | Subscription or usage fees depend on the service. |
| Task quality | Test a fitting model on a representative example. | Choose and test the hosted model and features needed for the task. |
| Privacy control | Potentially stronger, but only if the full workflow stays local. | Depends on provider terms, settings, and product tier. |
| Offline use | Possible after setup for some workflows. | Usually unavailable. |
| Best use | Private drafting, local experiments, offline work, learning, controlled document tests. | Tasks needing a particular hosted model or connected tools, convenience, and cross-device access. |
Choose local AI if
- you want to keep experimentation on hardware you control;
- you need offline-after-setup workflows;
- you are learning how models, runtimes, and RAG work;
- your documents are sensitive enough that provider upload is unacceptable;
- a model that fits your computer can handle the task and you can maintain the setup.
Choose cloud AI if
- you need a particular model or feature that is unavailable in your local setup;
- you want minimal setup;
- you need image/audio/video or advanced tool features;
- your workflow is already approved for the provider;
- your hardware cannot run useful local models.
When to split the workflow
For example, rewrite a private draft with a downloaded local model, then use an acceptable cloud service for a separate task that needs its tools. Keep the inputs separate. Local embeddings, document storage, connected tools, and sync settings still determine where the private draft goes. Compare your own usage in the cost calculator.