Model families and why they differ

The model picker beside the send button lists every model this server offers, grouped by family. The two main families are Claude, made by Anthropic, and GPT, made by OpenAI. Each family has bigger and smaller models, such as Claude Opus and Haiku.

Why families differ

Each company trains its models in its own way, with its own choices about how they should behave. So models from different families develop different habits, a bit like two capable colleagues trained at different firms. Both are good. They just read the same brief differently.

The main difference: literal or gap-filling

• GPT models are literal. They do what you wrote, and little more. If something matters, you have to say it.
• Claude models fill gaps. They work out what you probably meant, and often do more than you asked.

The same request, two results

Imagine sending both families this: "Check the budget spreadsheet in my files."

• A literal model may check it and tell you what it found, and stop there. It did exactly what you asked.
• A gap-filling model may check it, fix the errors, tidy the formatting and add a summary sheet. Helpful, unless you did not want the file changed.

Neither is wrong. Each did a reasonable thing with a short request. The fix is the same for both: say what you want. But what you most need to add is different for each, and that is what the next two lessons cover.