How to choose an AI model for your business
No model is the best at everything, and the one that suits you today may not be the one six months from now. What does exist is a set of criteria for choosing and a simple way to compare models with your own cases. This guide does not rank models: it gives you the method.
Cloud or open
There are two big families of language models:
- Cloud models (such as OpenAI’s GPT, Anthropic’s Claude, Google’s Gemini or xAI’s Grok): used through an API, paid by usage, with the provider looking after the infrastructure.
- Open models (such as Llama, Mistral, Qwen, DeepSeek or Gemma), the ones whose weights are published and can be downloaded: used through an API from various providers or installed on your own server, where the data does not leave your infrastructure.
Within each family there are sizes: large models, more capable and more expensive, and small ones, faster and cheaper.
The criteria that matter
| Criterion | What to ask yourself |
|---|---|
| The task | Does it have to read long documents, classify messages, extract data or write? Each model performs differently at each. |
| The language | Does it answer well in your customers’ language, with the way you and they write? |
| The cost | What does it cost at your volume? It is calculated by tokens: we explain it in what AI costs to use. |
| The speed | Is a customer waiting for the answer in a chat, where seconds matter, or is it a background process? |
| The context | How much text does it need to read at once? Some accept much longer documents than others. |
| The data | Where is it processed? What do the provider’s terms say about storing or using it? See AI and your business data. |
| The tools | Does it have to use your systems (check stock, create an order)? Not all models do it equally well. |
| Availability | What if the provider has an outage? For critical tasks, a second backup model is worth having. |
How to compare them with your cases
The comparisons going around online measure general things. What matters is how each model answers your cases. A simple test:
- Gather 20 to 50 real cases of the task, with the correct answer for each.
- Run them through two or three models with the same instructions.
- Score each answer: right, right with a tweak, wrong.
- Note each model’s cost and time for that same batch.
The result is often surprising: on a narrow task, a small model gets almost as many right as a large one, for a fraction of the cost. Keep those cases: they let you test again when a new model comes out.
Bigger is not always better
A larger model reasons better on complex tasks, but it is slower and more expensive. To classify a message, extract an invoice’s fields or summarize a short text, a small one is usually enough. One flow can use both: the small one to sort what comes in and the large one only for the hard cases.
Built to be able to switch
Models change every few months: new versions come out, prices drop, some get retired. That is why your system should not depend on just one:
- The instructions and test cases are yours and stay documented.
- The model is switched through configuration, not by rewriting the system.
- The provider account is in your name.
That is how we work in AI for business: we choose the model for each task together, and if another one makes more sense tomorrow, we switch. If you want to test with your cases, tell us about your task.
Frequently asked questions
What is the best AI model?
There is no single best one for everything. It depends on the task, the language, the volume and where the data has to stay. The reliable way to choose is to test two or three with your own cases.
Can I use different models in the same system?
Yes, and it often makes sense: a small, cheap one for simple tasks, such as sorting messages, and a more capable one for the tasks that need it. It also helps to have a backup in case the main one fails.
Is an open model on my own server more private?
The data does not leave your infrastructure, which helps when some information cannot be shared with third parties. In exchange, the server, its security and its updates are up to you.
What if the model I picked is discontinued?
Providers retire old versions with notice. If the system is built to switch models through configuration and you have kept your test cases, the switch is a matter of testing, adjusting and moving on.