In plain English
A model is the trained brain running underneath your AI assistant. GPT, Claude, Gemini and Llama are all models, each trained a bit differently. ChatGPT and Claude are the apps you type into; under the bonnet they run a model, sometimes a few different ones depending on what you pick.
Some models are enormous and live on company servers. Others are small enough to run on your own laptop, called local models. Some only handle text; others do images or voice too. Bigger usually means sharper but needs an internet connection and usually costs money. A local one is private, free and works offline, but noticeably less capable.
The easy way to keep the model and the app apart is to ask who made what. GPT comes from OpenAI, Claude from Anthropic, Gemini from Google and Llama from Meta. Those are models. ChatGPT and Claude are the apps, the window you actually type into. One company’s app can let you pick between several models, so the app stays put while the brain underneath changes.
Models also differ in what they can handle. Some work only with text; others take images or voice as well. So when you’re wondering which model to use, the useful question is what you need it to do. Start from the job, check which models cope with that kind of input, then weigh up the trade-offs above: big and hosted, or small, private and on your own laptop.
A worked example
Imagine you’ve got a confidential document about your business and want AI help going through it. Paste it into a big hosted model and it travels to that company’s servers. Download a small local model onto your own laptop instead and nobody but you ever sees that document. Ask both the same question.
The big one answers in seconds with something sharp and detailed. The small one takes a good while longer and gives you something decent but rougher round the edges. What you actually get is a choice: speed and polish, or privacy and quiet.
The usual mix-up
People assume newer and bigger always wins. It doesn’t. A huge model can be overkill for a simple job and cost more than it needed to, while a small local one does the job fine, quietly, on your own machine.
Where you’ll use it
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