I’ve been learning that you can use different AI models for different parts of browser automation. Some are better at reasoning through complex workflows, others are specialized for OCR or analyzing text from screenshots.
But with 400+ models available, I’m honestly not sure how to make smart choices. Do I pick the most powerful model for everything? Do I go cheap? How do I know if a model is actually better suited for a specific task without spending hours testing?
I’m wondering if there’s a practical approach to this or if I should just pick one model and stick with it. What’s your strategy when you have access to a bunch of different AI models?
The practical approach is thinking about what each part of your workflow actually needs. OCR tasks benefit from specialized vision models, not general language models. Complex reasoning about multi-step navigation benefits from stronger reasoning capabilities. Simple form field extraction doesn’t need premium models.
The advantage of having access to many models is you can match the tool to the job. You don’t overpay for expensive reasoning when you need a fast, cheap extraction. You don’t use a weak model when you need genuine problem-solving.
Start by picking the right model for your highest-value task, then optimize from there. Most people find 2-3 models actually cover their needs—one for reasoning, one for vision, one for simple tasks.
I learned this the hard way. I was using the same expensive model for everything because I figured it was the safest choice. Cost was higher than it needed to be.
After testing, I found that the expensive model was genuinely better at reasoning through complex login flows and multi-step navigation. But for simple field extraction? A cheaper model worked just fine. Now I use the expensive model for maybe 10% of my workflow where it matters, and cheaper models for the rest.
The sweet spot was running both in parallel once to compare results, then using what actually worked better for each piece.
Match model capability to task complexity. Reasoning = stronger model. Vision = specialized OCR. Simple extraction = fast model. Test once, configure, move on.