AI model comparison for business
Not just OpenAI versus Claude. Compare models by task, quality, speed, context, monthly cost, privacy, hosting, open weights, data residency, inference location and data sovereignty — with the official source for each model.
What do you want to achieve?
You do not need to know model names, tokens or technical terms. Answer a few straightforward business questions; we translate them into a suitable AI choice.
Choose the option that comes closest. You can add details in your own words afterwards.
This determines whether a low-cost fast model is sufficient, or whether quality and scale matter more.
A marketing concept can tolerate more mistakes than a legal, financial or customer-critical process.
What matters to you?
Technical options — only if you know them
A model choice only creates value when it becomes part of the work.
The Model Guide provides the selection criteria. Powerhouse then uses them in the same loop: understand what is needed, choose the right agent or workflow, execute in your systems and measure the outcome.
Compare models side by side
Filter by provider, status and use. “EU” below only means the catalog identifies a European processing option for this deployment path. It deliberately does not mean full sovereignty.
Sources are vendor documentation. Unknown values are shown as unknown; the Model Advisor does not invent residency or pricing claims.
More than just: “where is my data stored?”
For sensitive business data, assess at least these layers separately. A model can technically run in Europe while still legally falling under a non-European provider.
Storage residency
Where prompts, outputs, files, logs, vector stores and backups are stored at rest — and for how long.
Inference residency
Where GPU/model processing takes place. European storage does not automatically guarantee European inference.
Jurisdiction
Which legal entity and laws govern the provider, including possible extraterritorial obligations.
Deployment control
Native SaaS, EU-region endpoint, your own cloud/VPC or fully on-prem/self-hosted. More control can also mean more operational responsibility.
Retention & training
Zero-data-retention, abuse monitoring, training policies, retention periods and enterprise contracts must be checked separately.
Subprocessors
Which third parties may process data, in which countries and under which transfer safeguards.
Keys & network
Customer-managed keys, private networking, IAM, audit logs and tenant isolation determine how much technical control you actually have.
Lifecycle & lock-in
Deprecated models, APIAn agreed connection point with which two systems can read and write each other's data, without anyone having to type anything over.changes, licenses and portability should be factored into architecture and continuity risk.
Want to translate this choice into your processes and data?
The Model Advisor first provides the substantive comparison for free. Then leave your email address if you want to save the selected model direction and use it as a starting point for a concrete AI or automation path.
The nuance comparison lists often miss
What is the best AI model?
There is no universal answer. A model can be stronger at complex coding yet economically illogical for high-volume classification. The Model Advisor optimizes for your task and constraints.
Why look at cost per task instead of token price alone?
A cheaper model may need more retries or extra tokens. A more expensive model may finish in one run. The current calculator uses a transparent token basis; the Powerhouse loop can later calibrate this with real task outcomes.
Does EU data residency automatically make a model GDPR-compliant?
No. GDPRThe privacy law: which personal data you may process, for what purposes, and how long you retain it.-compliance also depends on purpose, legal basis, processor agreements, data minimization, security, subprocessors, retention and your specific implementation.
Why are preview models ranked lower?
Preview models can be fine for experiments, but lifecycle and stability risks matter in production. The ranking therefore applies a limited preview penalty.
Can one workflow use multiple models?
Yes. Routing is often more economical: a smaller model handles standard work, a stronger model handles difficult cases, and a specialist model handles tasks such as OCR or reranking.
Where does your model run — and who keeps control?
A provider name alone says too little. Compare storage, inference, training, retention, zero-data retention, keys, private networking and self-hosting for each deployment path.
Governance fields depend on deployment and contract terms. Unknown stays unknown; check the official source before sensitive production use.
The amount depends on the number of fields, the number of exceptions and whether business rules need to be included. After one conversation you'll know which half you're in.
The way it works now
- The appointment is in one colleague's mailbox
- Data is manually retyped from one system to another
- The person who knows is on vacation
- No one can see afterwards why this decision was made
As it is
- The agreement is stored with the client, findable for everyone
- Once entered, information flows through to the rest
- Work continues, even if someone is absent
- Every decision has a source, an owner, and a date
What is your next step?
Also good to know: frequently asked questions · security and data · terms and conditions · partners · research and figures · templates · what's changing · where you start
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