New to this? You're in the right place. This post assumes you've used something like ChatGPT before, but never built anything with AI yourself. If a word needs explaining, it's explained right where it shows up.
The two words you'll see everywhere
- An AI model is the actual "brain" behind a tool like ChatGPT or Claude — the thing that reads your question and generates an answer. When you chat with ChatGPT in a browser, you're talking to a model through a friendly interface. Different companies (OpenAI, Anthropic, and others) build their own models, and models differ in how good they are, how fast they are, and how much they cost to use.
- An API key is a long, private code string that proves "this request is allowed, and bill it to this account." Instead of typing into a chat window, a program can send a question straight to a model over the internet — the API key is how the model's provider knows who's asking and who to charge.
Why anyone would use two different AI tools on purpose
If you use an AI chat tool casually, you probably use just one. But once AI gets wired into actual repetitive work — reviewing code, drafting routine documents, doing research — the volume of requests goes way up, and a model billed per-use can get expensive fast if every single request goes to the most capable (and most expensive) one.
The fix some people use: send the big, precise, "this really matters" work to the best model you have, and send the repetitive, high-volume, lower-stakes work to something cheaper — sometimes even a model that runs for free on your own computer instead of a paid service at all. You get the quality where it counts and the savings everywhere else.
What "running a model on your own computer" even means
This sounds more exotic than it is. Some AI models are published openly enough that they can be downloaded and run directly on a regular computer, using its own processing power instead of sending the question over the internet to someone else's servers. It's slower and somewhat less capable than the biggest hosted models, but it costs nothing per use once it's set up — you're just using your own computer's electricity, not paying anyone per question.
A terminal-based AI agent is a program that connects a model — hosted or local — to your actual project files, so it can read your work, make edits, and run commands on your behalf, rather than you copy-pasting text back and forth in a chat window.
What this isn't
An honest note, because overselling doesn't help anyone: routing work between two different AI tools isn't magic, and it doesn't happen automatically — a person decides, task by task, which one to send something to, based on how much it matters and how much it costs. And a locally-run model genuinely is less capable than the largest hosted ones for the hardest problems; the savings come with a real quality trade-off for the highest-stakes work, which is exactly why that work stays on the better (and pricier) model.
Ready for the deeper version?
Everything above is the plain-language shape of a real, detailed technical guide to setting up exactly this kind of two-model workflow. If you want the real detail — exact setup commands, both a hosted and a fully local option, and real cost numbers — the full version is here: Cut AI API Costs with Hugging Face + Claude: Hybrid Setup Guide.
If this was your first time thinking about AI models and API keys this way, you now know enough to follow that post — and enough to understand why someone would deliberately use more than one AI tool.