Graded F on resilience. In Vannus's assessment it has not disclosed which model it runs — a thin layer over someone else's foundation model.
Managed serverless inference plus managed vector databases from IONOS Cloud, serving open-source models (Qwen, Llama, Mistral, FLUX.1/FLUX.2, embedding models) on token-based pricing with no licence fees. IONOS documentation states "data processing is confined within Germany", that "all data processing complies with German and European data protection regulations", and that "Your input data remain
Not disclosed. IONOS AI Model Hub does not publish which model it runs, so this criterion is excluded and the grade rests on what we could verify. We say so rather than guess.
This is a separate question from the grade above. The grade measures resilience — whether the tool endures and whether you could leave it. This measures who can compel your data. A tool can score modestly on one and strongly on the other, and many do.
The vendor's published or catalog-recorded posture — the concrete facts this grade is built from. A full audit verifies each against the vendor's current documentation.
Vannus grades IONOS AI Model Hub against nine dimensions of trust — data sovereignty, training privacy, compliance posture, operational resilience, exit portability, and more. The heaviest criterion asks whether the tool builds its own AI or resells someone else's model; where the vendor discloses it, the grade cites the vendor's own documentation. No paid placements — scoring is walled off from affiliate revenue. See the methodology →