Compare AI coding agents
Every tool here is the same shape: it reads your project, proposes changes, writes them to real files, and you review what happened. So the question is not which is best — it is which seat you want to sit in.
Claude Code vs Cursor
Both write real code into real files. The difference is where you sit while it happens: a terminal next to your tests, or an editor with changes shown in place.
Claude Code vs Codex
The most similar pair here: two terminal agents with nearly the same workflow. What separates them is Codex's remote mode and which ecosystem you are already paying for.
Claude Code vs Gemini CLI
Two agents in the same seat. The real question is not which is smarter but whether your problems are local or spread across the codebase.
Claude Code vs Kimi
These are not competing products. One is an agent you run; the other is a model you point an agent at. Knowing which you are choosing saves the argument.
Cursor vs Codex
The widest gap of the three: one keeps you inside the file watching every edit, the other takes the task away and brings back a branch.
The uncomfortable answer
You will learn more from two weeks with one of these than from any comparison, including these. They share a shape, so whichever you learn transfers to the rest in an afternoon — which means picking wrong costs you an afternoon, and deliberating costs you the month.
What you will not find here: model versions, prices, context-window sizes or benchmark tables. They are the four things every other comparison measures, and the four things that are wrong a month later. For what each vendor shipped most recently — the part that really does need a date — we maintain agents-compared , where a weekly job keeps it current instead of a person remembering to.