Replace OpenAI API: How to Migrate Applications to the IONOS AI Model Hub

The IONOS AI Model Hub offers an OpenAI-compatible interface. Many applications can therefore be converted by swapping three things: the address of the interface, the access key, and the model name. The real effort lies in testing the response quality, features that only OpenAI offers, and adapting the instructions to the new model.

Many companies have built their first AI applications with the OpenAI API – often before data protection was clarified. If you want to switch to models from German data centers now, you don't have to start over. This article shows how the switch works.

What "OpenAI compatible" means

The OpenAI interface has become a quasi-standard. OpenAI-compatible means that the provider understands the same requests for chat, embeddings and sometimes images. Tools such as n8n, Open WebUI or common programming libraries can therefore talk to the AI Model Hub without modification.

What's changing

What you need to check

• Response quality: Another model responds differently. Test with real examples.
• Structured output: If your application expects JSON, check that the new model reliably adheres to the format.
• Tool calls (function calling): Not every model supports this equally well.
• Special functions: Functions that are unique to OpenAI (such as certain assistant or voice functions) may not have a counterpart.
• Embeddings: If you change the embedding model, all documents in the search must be re-embedded – old and new vectors do not match.
• Context length: Models process inputs of different lengths.

Transition in five steps

1. Record inventory: Which applications and workflows call OpenAI, with which models?
2. Create test set: 20-50 real inputs per application with expected results.
3. Choose and test the model: Compare two or three models with the test kit.
4. Adjust prompts: Sharpen instructions until the results fit.
5. Switch and observe: First one application, then the next. Keep track of errors and costs in the first few weeks.

The bigger win: interchangeability

Once you clean up the switch, you will have an architecture in which the model is interchangeable. This protects against price increases and dependencies – more on this in the article Avoiding Vendor Lock-in. Switching to Mistral, to your own server or back becomes a question of configuration.

We take care of the switch to the IONOS AI Model Hub or other providers from Germany – including test set, model selection, and adaptation of your workflows.

Counselling and accompanied implementation is eligible for funding: Through INQA coaching, the federal government covers 80% of the consulting costs of up to €1,200 per day for up to 12 days, i.e. up to €11,520 subsidy. In Mecklenburg-Western Pomerania and the other new federal states, BAFA consulting funding is also eligible at 80% until 31.12.2026 (50% in the old federal states). Funding is provided for consulting, not software. The funding check shows which program fits.

Frequently Asked Questions

Can I simply replace the OpenAI API with IONOS?

Technically, often with few changes, because the interface is OpenAI-compatible. However, response quality, structured outputs and special functions should be tested beforehand.

Do I have to re-read my documents?

Only if you also change the embedding model. Vectors of different embedding models are not compatible, so the search must then be rebuilt.

Which IONOS model best replaces GPT?

That depends on the task. gpt-oss-120b and Llama 3.3 70B are suitable for more demanding tasks, Mistral Small 24B for many standard tasks. A test with your own examples is decisive.

Will the switch be more expensive?

Usually not: The prices of the open-top models at IONOS are low. Costs are mainly incurred for tests and adjustments.

Would you like to bring your AI applications to Germany? Write to us via the contact page.