Comparing AI assistants for programming by typing questions into a chat window measures the wrong thing. In 2026 most of the work happens in an editor extension, a terminal agent or a review bot attached to a repository, and those tools differ far more than the chat interfaces do.
This page compares the tools rather than the chat products, and stops short of claiming any one writes better code, because that depends on your stack and is not something a comparison page can establish for you.
Nearly every vendor now offers several of these. The shape determines how much of your workflow the tool touches, which matters more than the underlying model for day to day use.
In the editor
Suggestions as you type, plus a chat panel with the current file in context. The lowest friction shape and the one most developers start with.
Check: which editors are supported, and whether your organisation permits the extension.
In the terminal
An agent that reads the repository, edits files, runs commands and iterates. Anthropic ships Claude Code in this shape; competing vendors ship comparable tools.
Check: what it is permitted to run without asking, and how that is configured.
In the repository
Automated review comments, description drafting and issue triage attached to your hosting provider.
Check: how noisy it is on a real repository before enabling it for the whole team.
In the browser
Pasting code into a chat product. Still useful for explanation, debugging a snippet and learning, and increasingly not where the main work happens.
Check: whether the free tier covers what you actually use it for.
Described at the level that stays true between releases. Model names and version numbers change quickly and are deliberately not listed.
These are the questions that determine whether a tool fits, and none of them is about model quality.
Every tool in this category produces code that looks right and sometimes is not. Confident output is not verified output, and review remains the developer's job whichever product generated the diff.
Agents are also poor judges of when to stop. Given a vague instruction they will keep changing files, so scoping the task narrowly does more for the result than choosing between vendors.
No benchmark figures appear on this page. Coding benchmarks shift with every model release, often measure isolated puzzle style tasks, and rarely predict behaviour in a large existing codebase, which is where most professional work happens.
Current pricing, inclusions and supported platforms are published by each vendor: Anthropic, GitHub, OpenAI, Google.
Independence, accuracy and scope. This page is published independently for general informational purposes. It is not affiliated with, endorsed by, sponsored by or authorised by Anthropic, OpenAI, Google, Microsoft, GitHub or any other company named, and it is not a reseller, partner or agent for any product described. Trademarks and product names belong to their respective owners and are used solely to identify the products discussed. No vendor has reviewed, sponsored or approved this content, no compensation has been received, and no testimonials, endorsements, ratings, awards or benchmark scores appear anywhere on this page. Descriptions reflect general publicly available information at the time of writing and may be incomplete or out of date; product names, plan inclusions, supported platforms and pricing change frequently and vary by region. Prices mentioned are approximate United States figures excluding tax. Nothing here is technical, security, licensing or purchasing advice, and no code quality, productivity gain, cost saving or other outcome is promised or implied. Confirm current details with each vendor, and check your own organisation's policy, before installing or subscribing to any tool.