Start with the job, not the model name
Write down the output you need, the acceptable error level, expected volume, and whether the work contains confidential information before comparing AI models.
Understand what happens to your input
Check whether prompts, files, images, or generated outputs are sent to a provider. Look for retention, logging, training-use, and deletion information in the provider documentation and the application privacy policy.
Understand the cost model
A tool can be free to open and still consume paid provider quota. For production work, calculate the cost of a usable result rather than the cost of a single generation.
Test failure modes
Do not test only the best-looking output. Try an ambiguous request, a long input, or a strict formatting task and observe how the tool reports limitations.
Keep human review in the loop
AI-generated copy, images, audio, and video should be checked before publication when accuracy, reputation, rights, or brand rules matter. Verify names, dates, numbers, quotations, and claims.
The evaluation checklist
Ask five questions: What exact task does it solve? What data leaves the device? What does a usable result cost? How does it fail? Who checks the output before publication?