Local AI or cloud AI: what makes sense for you?

If you want to draft text, summarize a document or brainstorm, you can run a model on your own computer or use an online service. Local AI gives you control over the device and can work without an internet connection after the model is downloaded. Cloud AI avoids managing models and hardware, but depends on a connection, an account and the provider’s terms. There is no single best option; the right choice depends on your work and the data you enter.

What does local AI mean?

The model runs on your computer, usually through an app such as LM Studio or Ollama. LM Studio says that, once downloaded, a model can be used offline and prompts and documents stay on the device during local inference. Downloads, updates and features that reach the internet still need a connection. The app’s settings and integrations also matter. LM Studio offline operation.

For a concrete downloadable model, Ollama lists several Qwen 3.5 variants, including a 4B version with a download size shown between 3.3 and 4 GB. That file size is not the same as the RAM required to run it: the runtime, context length and weight format need additional memory. A model listing is a starting point, not a promise of speed or answer quality on your computer. what NPU TOPS ratings tell you Qwen 3.5 variants in Ollama.

What does cloud AI offer?

With a cloud chatbot or API, the provider’s servers do the computing. Your computer mainly needs a browser or app and an internet connection; you do not have to download the model or maintain its runtime. Answer quality depends on the chosen service and model, which can change over time.

Pricing may be part of a subscription or based on usage, such as input and output tokens. The Gemini API pricing page is one example of usage-based pricing. Before choosing a service, check the current plan, limits, retention terms and privacy controls. These details depend on the product, account type and settings.

Privacy is more than where the model runs

With local inference, your prompt does not need to go to a remote API to generate an answer. You should still consider app telemetry, plug-ins, file synchronization, backups and the security of your computer. An online service receives requests on the provider’s infrastructure; check the settings and retention rules for your account. Avoid entering confidential information until you have checked the service terms and your organization’s policies.

Performance and total cost

A small local model may feel responsive on a suitable computer and slow on a less powerful laptop. Larger models need more memory and compute. Answers can also differ in capability, available tools and freshness. Unless the same hardware, model, prompt and task have been tested, it is not accurate to say that one option is generally faster or more accurate.

Local costs include the computer or an upgrade, electricity, storage and maintenance time. Cloud services reduce technical upkeep but may involve a subscription, usage limits or per-use charges. For occasional work, an online plan you already have may be simpler. If you regularly handle documents you do not want to upload, or need to work offline, a local model may fit better once you have checked performance and software policies.

Choosing for everyday work

For light tasks, start with an accessible model you already have. For sensitive documents, decide which data you can enter and where it will be processed. For offline work, confirm that the model and required features are already on the device. For consequential tasks, review the answers yourself: neither local nor cloud models guarantee accuracy.

Main sources

• LM Studio — offline operation
• Ollama — Qwen 3.5 models
• Google AI for Developers — API pricing