A new LLM has outperformed competitors at coding — but will it handle a bug in your repository? A fresh article breaks down how to choose and test a model for work tasks: Claude, GPT, Gemini, and others. The authors remind readers: a model that's great at analyzing documents may stumble on tables with refunds. The same tool can be strong at code but fail at spreadsheets. So you should test LLMs on your own real tasks. Bottom line: don't pick a model based on a single benchmark — test it on the data you actually work with.
Source: habr.com · post in Telegram