Private LLM vs. ChatGPT: what's the difference?
The core difference is where your data is processed and who controls it. ChatGPT is a public service that processes your input on a third party's infrastructure. A private LLM runs inside your own isolated environment, where your data stays yours and never leaves the EU.
For general work, ChatGPT is fine. If you handle sensitive data, IP or strict compliance requirements, a private LLM gives you control a public service cannot.
The differences at a glance
| Criterion | Private LLM | Public ChatGPT |
|---|---|---|
| Where it runs | Your environment, on-premise or private cloud in the EU | Provider's servers |
| Who sees your data | Only your organisation | The provider processes your input |
| Training on your data | Never, unless you explicitly opt in | Depends on plan and settings |
| Data location | Inside the EU or on-premise | Often outside the EU |
| Customisation | Trained on your documents and terminology | Generic model, limited adaptation |
| Cost model | Upfront investment, lower recurring cost | Ongoing per-user subscription |
Where the real differences lie
Data handling and control. With ChatGPT you hand input to an external service. Even business plans run on a US provider's infrastructure. With a private LLM every data flow stays inside your own environment and you decide who has access.
Compliance. Because your data never leaves your environment, complying with GDPR and the EU AI Act is significantly simpler with a private LLM. With a public service you depend on the provider's terms and data location.
Customisation. A private LLM is trained on your own documents, so it understands your terminology, workflows and context. A public model lacks that context and gives more generic answers.
Read more: Private LLM, GDPR and the EU AI Act
When is ChatGPT enough, and when not?
ChatGPT is a fine choice for general tasks without sensitive information: brainstorming, drafts, public-facing content. The difference matters as soon as business-sensitive data enters the picture.
Choose a private LLM if you work with confidential case files, personal data or valuable intellectual property, or if you operate in a regulated sector where you must control where your data sits.
Read more: Private LLM for enterprises
