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Model compass

Which AI model for which task?

It is not about the best model but the fitting one. Pick your task — you get the recommendation, the reasoning and an honest caveat.

What do you want to get done with AI?

Recommendation: Customer enquiries and email correspondence

Recommendation

Customer enquiries and email correspondence

The service team answers 50 to 200 customer emails a day. Tone and factual accuracy have to be right; drafts are reviewed before sending.

Why: For customer-facing text what matters is fluency in German and a consistent tone — that is what the general-purpose models from Anthropic and OpenAI are built for, and both explicitly document multilingual capability. Deliberately pick the mid tier (Claude Sonnet 5 or GPT-5.6 Terra): the work is in the tone, not in heavy reasoning. If customer data must not leave the EU, Mistral is the alternative because self-hosting is documented there.

Claude (Anthropic)

First recommendation

Anthropic · USA

EU hosting: partlyDeployment: service only

Sehr lange Dokumente am Stück — und vier Preisstufen, damit nicht jede Aufgabe das Spitzenmodell bezahlt.

Caveat: Kein EU-Datenstandort beim direkten Zugang: Der Parameter für die Inferenz-Region kennt nur die…

GPT (OpenAI)

OpenAI · USA

EU hosting: partlyDeployment: service only

Das breiteste Werkzeug-Sortiment neben dem Text — Bild, Echtzeit-Sprache, Transkription — mit Europa als wählbarer Region.

Caveat: Die EU-Datenresidenz ist nicht self-serve: Sie muss über das OpenAI-Account-Team freigeschaltet…

Mistral

Mistral AI · EU (Frankreich)

EU hosting: availableDeployment: service or self-hostedOpen weights: Apache 2.0 (Teil der Modelle)

Europäischer Anbieter, der den vollständigen Selbstbetrieb dokumentiert — „Nothing leaves your perimeter“.

Caveat: EU-Herkunft ersetzt keine Prüfung: Der Auftragsverarbeitungsvertrag erlaubt ausdrücklich…

Alternative: Mistral

Last reviewed: August 06, 2026Editorially maintained, no automated ranking: every model family carries a source and an explicit caveat. We do not quote benchmark figures we cannot substantiate — models evolve quickly, so check the vendor's current state before deciding.

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