AI model ranking

How to read the AI model ranking

The ranking organizes language models along four axes that in practice determine your choice of tool. Intelligence is the Artificial Analysis Intelligence Index, a composite score from multiple benchmarks (reasoning, code, math, knowledge), reduced to a single number: the higher, the better. It's a good starting point, but not an oracle, because a model with a lower index can win at a specific, narrow task.

Price per 1M tokens tells you how much you'll pay per million tokens processed (that's roughly 700 thousand words). At large scale, the difference between a model at three dollars versus twenty can impact your entire project budget more than a few index points. Speed (tokens per second) and time to first token matter everywhere a user waits for a live response: in chat, in a voice assistant, in a code editor. Context is how much text the model accepts at once; a large window lets you drop in entire documentation or a long file without splitting it into chunks.

There's no single "best" model, only the best for your task and budget. For mass, cheap text processing you'll choose differently than for difficult reasoning or code generation, and something else again if you care about running the model on your own hardware (the open-weights column). That's why instead of memorizing one name, it's worth returning to a fresh comparison, because positions change with every new release.