When someone asks me which AI tool they should use, the first thing I ask is: what do you need it for? Because there are two big families of artificial intelligence models, and the difference between them is not just technical: it has real implications for your privacy, your budget and what you can actually do with them.
Let’s talk about both: open-source AI and closed (or proprietary) AI.
What is open-source AI
An open-source AI model is one whose code and, in many cases, its weights (the numbers that make it work) are publicly available. That means any person, company or researcher can download it, run it on their own servers and modify it.
The most well-known examples today are Llama (from Meta), Mistral (a French company), and Gemma (from Google). There are dozens more.
What changes with an open model:
- You can install it on your own computer or server
- Nobody sees your conversations, because the model runs on your own infrastructure
- You can fine-tune it to do exactly what you need (this is called fine-tuning)
- You don’t pay per message you send
What is closed AI
A closed or proprietary model is one whose creator does not share publicly. You use it through their product (the app, the API), but the model itself lives on their servers.
The most used examples: Claude (from Anthropic), ChatGPT (from OpenAI), Gemini (from Google) and Grok (from xAI). Almost all the major AI interfaces people use every day are proprietary.
With a closed model:
- You access it from a browser or an app, without needing to configure anything
- The company maintains it, improves it and handles the infrastructure for you
- You pay a monthly subscription or per use
- The data you send passes through the company’s servers
The difference that matters most: who processes your data
This is where many people make the wrong choice.
If you use a proprietary model like Claude or ChatGPT to analyze client data or draft a sensitive contract, that information passes through Anthropic’s or OpenAI’s servers. Both companies have serious privacy policies and offer modes that don’t use your conversation for training, but the data does leave your infrastructure.
With an open-source model running on your own server, the data stays put: you control everything. That matters for sectors like health, finance, or any company with regulated information.
The advantages of each, straight up
Open source: better for…
- Total privacy (data doesn’t leave your infrastructure)
- Deep customization (you can fine-tune the model for your industry)
- Low long-term costs (no subscriptions, only server costs)
- Research, experimentation and building your own products
Closed source: better for…
- Getting started fast without configuring anything
- High-quality results from a simple prompt
- Support, updates and automatic improvements
- People without technical experience who want results today
So which one is for you?
If you’re someone who wants to use AI for work, learning, creating content or automating everyday tasks, a proprietary model like Claude or ChatGPT is probably your best entry point. They’re easy to use, well maintained and don’t require any technical setup.
If you have a company with sensitive data, a technical team, or you want to build a product without depending on a single company, exploring open-source models makes a lot of sense.
And the answer nobody tells you: you don’t have to choose just one. You can use Claude for your daily work and explore Llama when you need total privacy or specific customization. Many builders do exactly that.
The most important thing
Don’t let the terms “open source” or “closed source” intimidate you. At the end of the day, what matters is whether the tool does what you need, whether it protects the information you give it, and whether it fits your budget.
Start with whichever is most accessible for you right now. You’ll have plenty of time to explore the other when you get there. AI isn’t a fixed destination; it’s a path, and you can move forward at your own pace.
Want these tools compared in depth? Check the unbiased reviews.
