Best AI coding agents
11 tools for agents that plan and finish coding tasks, compared side by side.
The ranked list
Edits files, runs commands and turns GitHub or GitLab issues into pull requests, running locally and calling model APIs directly without a backend server. Max plans start at $100/month with included API credits.
Helps write code in the editor, on the command line and on GitHub, and includes a cloud agent that runs assigned tasks autonomously in the background. Free plan with 2,000 completions per month; Pro from $10/month.
Agents turn ideas into code and take on handed-off tasks, with runs in the terminal and Slack and pull request reviews on GitHub. Free plan includes limited agent requests; Plus is $8/month billed monthly.
Agentic coding reads and writes files and runs shell commands, alongside AWS guidance and Java and .NET application transformation. Free tier includes 50 agentic requests per month; Pro is $19/user/month.
Open-source platform whose agents plan, write and apply code changes across codebases, available as a web GUI, terminal UI or CLI. The Local open-source and Individual plans are both free.
Builds, tests and delivers pull requests in the cloud or on your machine, with parallel cloud agents and automations for bugs and failed CI. Free plan includes a light quota; Pro is $20/month.
Open-source agent for editors and terminals that runs bash commands and coordinates multi-file edits with diffs, checkpoints and undo. Can also be embedded via SDK, and the Open Source tier is free.
Aimed at engineering organizations running a software factory, with pre-built experts for each development lifecycle stage and quality gates that pause work for human review. Standard starts at $20/month.
Droids plan, build, review and ship software across desktop, terminal, web and CLI, with code review on every pull request. Mission Control shows active missions and execution logs; Pro is $20/month.
JetBrains Air is a web app for building software with AI agents, for developers, teams and organizations adopting AI at scale.
Terminal pair programming with LLMs that maps the entire codebase, auto-commits changes through git and lints and tests after each edit. Works with cloud and local models, including Claude, DeepSeek and OpenAI.
