Every AI tool you use lives somewhere. The question is whether it lives on your computer or on someone else's server. This distinction — local vs. cloud — has real consequences for your privacy, your costs, and what you can do with AI. Here is a clear breakdown of both, with no marketing spin.
How Cloud AI Works
When you type a message into ChatGPT, here is what physically happens:
Your text leaves your device → travels over the internet → arrives at OpenAI's data centres → gets processed by their model → the response travels back → appears on your screen.
The entire loop typically takes 1-3 seconds. During that time, your text exists on OpenAI's servers. It is logged, it may be reviewed, and depending on your privacy settings, it may be used to train future models. The same applies to every cloud AI service — Claude, Gemini, Copilot, Perplexity.
How Local AI Works
When you type a message into a local AI tool like Skales with Ollama:
Your text stays on your device → gets processed by a model running on your hardware → the response appears on your screen.
Nothing leaves your machine. No transit, no third-party server, no logs on someone else's infrastructure. The processing is slower on average (especially on modest hardware) but the privacy profile is categorically different.
Privacy: The Real Difference
Cloud AI privacy risks fall into three categories. First: breach exposure. Your data exists on servers that can be hacked. Several major tech companies have experienced significant data breaches in the past three years. Second: policy risk. Privacy policies change. Companies get acquired. What is opt-out today may be opt-in tomorrow. Third: inference risk. Even without storing individual conversations, usage patterns and metadata reveal information about you that you may not intend to share.
Local AI eliminates all three categories. Your data never transits, never sits on a third-party server, never contributes to someone else's training dataset. The only risk is the security of your own device — which you already manage for all your other sensitive data.
Cost Comparison
Cloud AI costs: ChatGPT Plus ($20/month), Claude Pro ($20/month), Copilot Pro ($20/month). If you use two or three of these, you are paying $40-60 per month, or $480-720 per year — and that is before any API usage fees for programmatic access.
Local AI costs: Ollama is free. The model weights (Llama, Mistral, Qwen) are free. Skales is free for personal use. Your electricity bill for running the model is a rounding error. If you want access to frontier cloud models on demand (for occasional hard tasks), OpenRouter pay-as-you-go typically runs $3-10 per month with moderate use.
Control and Reliability
Cloud AI can be unavailable (outages), can change its behaviour (model updates), can change its pricing (subscription increases), and can be discontinued (products get shut down). Local AI runs on your hardware. It is always available. It never changes unless you update it. It costs the same in year five as in year one.
When Cloud AI Makes Sense
Cloud AI is the right choice when: you need the absolute best available model quality and accuracy matters more than privacy; you are working on non-sensitive, public information; you have a low-powered machine that cannot run models locally; or you need a capability (like advanced image generation or real-time voice) that local models do not yet match.
When Local AI Makes Sense
Local AI is the right choice when: you are processing personal data, client information, medical records, or anything confidential; you need to work offline; you want predictable costs; or you are in a regulated industry with data residency requirements.
The pragmatic answer for most users is both: local AI for sensitive daily work, cloud AI via pay-as-you-go API for occasional demanding tasks. Skales supports this hybrid approach natively — set Ollama as your default and OpenRouter as your fallback. Read more about privacy-first AI workflows or download Skales free.