How I choose an AI model
Start with the work you need the model to do. A good response to a random demo says little about how it will work in your project.
In this guide
1Use the same task
Create a small, representative task with clear requirements. Give each model the same information so you can compare the results fairly.
2Define a good result
For code, this may mean that the solution runs, handles errors and is easy to change. For writing, it may mean that the facts are correct and the reader understands what to do.
3Consider the total cost
Include waiting, retries and the time you spend correcting the result. A cheap request is not always a cheap finished task. Try small tasks before letting a model work on its own for a long time.
4Consider your data too
Check where requests go and which terms apply to your account or API. Use fictional data when trying a new setup. Verify prices and model names with the provider before deciding.