AI Coding Assistants Compared: Claude Code, Cursor, Copilot, Codex

Comparing AI coding assistants in 2026 mostly comes down to where you want the AI to work. Claude Code and OpenAI Codex are agent-first tools that live in the terminal and extend to IDEs, desktop and cloud. Cursor and Devin Desktop (formerly Windsurf) are AI-native editors. GitHub Copilot is built into GitHub and the major IDEs. Open-source agents such as Cline, Continue and OpenCode let you bring your own model. All of them can now run multi-step agentic tasks, so the real differences are workflow fit, pricing model, model choice and security controls.

Everything below reflects the vendors’ own documentation as of September 2026. Features and prices in this category change monthly, so check the linked pages before you buy.

The main AI coding assistants at a glance

Tool	Where it runs	Models	Pricing model	Standout strength
Claude Code	Terminal, VS Code, JetBrains, desktop app, web, Slack, CI	Anthropic Claude models (API also via cloud providers)	Paid Claude plans, or pay-per-token via the API	Deep agentic work, customisation with skills, hooks, subagents and MCP
OpenAI Codex	CLI (open source, Apache 2.0), IDE extension, cloud, ChatGPT app	OpenAI models	ChatGPT plans, or API key	Terminal and cloud agent tightly tied to the ChatGPT ecosystem
Cursor	Its own VS Code-based editor, cloud agents, GitHub	Many vendors’ models plus its own	Free Hobby tier; individual plans from $20/month; Teams $40/user/month; Enterprise custom; usage beyond allowance billed on demand	Polished editor experience, fast autocomplete, parallel cloud agents
GitHub Copilot	VS Code, Visual Studio, JetBrains, Xcode, Eclipse, GitHub.com, CLI	Models from Anthropic, OpenAI, Google and others	Free tier; Pro $10, Pro+ $39, Max $100 per month; Business and Enterprise for organisations; agent and chat usage draws on included AI credits	Native GitHub integration: assign an issue, get a pull request
Devin Desktop (formerly Windsurf)	Its own editor plus Devin cloud agents	Its own agent; can host other ACP-compatible agents	See vendor	Managing many local and cloud agents from one place
Gemini CLI	Terminal (open source, Apache 2.0)	Google Gemini models	Free tier with a personal Google account; paid via API or Google plans	Generous free usage and long context
Open-source: Cline, Continue, OpenCode	IDE extensions and/or terminal	Bring your own: any API or a self-hosted model	Free software; you pay for model usage	Full control, including fully self-hosted setups

Tool by tool

Claude Code

Anthropic’s agentic coding tool reads your codebase, edits files, runs commands and works with git. It started in the terminal and now also runs in VS Code and JetBrains, a desktop app, the browser and Slack, with GitHub Actions and GitLab CI integrations for automated review and triage.

Where it shines:

• Long, multi-step tasks such as refactors, test-writing campaigns and dependency upgrades.
• Team customisation: a CLAUDE.md file for project conventions (it can also read AGENTS.md), reusable skills, hooks that run your formatter or linter automatically, and subagents that work in parallel.
• Tools via MCP, so it can reach issue trackers, docs and internal systems. See our MCP servers guide.
• Scripting: it can be piped and run headless in CI.

Consider: it is Claude-only, and the best results come from investing in project instructions and fast tests.

OpenAI Codex

Codex is OpenAI’s coding agent, available as an open-source CLI, an IDE extension, a cloud environment and inside the ChatGPT app. Access comes through ChatGPT plans or an API key. It suits teams already standardised on OpenAI, and the open-source CLI is useful if you want to inspect or extend the harness.

Cursor

Cursor is a VS Code-based editor built around AI: fast Tab autocomplete, an in-editor agent, cloud agents that run in parallel, Bugbot for pull request review, project rules and MCP support. It lets you choose between frontier models from several vendors. Pricing combines a monthly plan with an included usage allowance and on-demand billing beyond it, so heavy agent use needs a budget owner. Privacy mode, which keeps your code from being used for training, is available, and Teams plans can enforce it team-wide along with SSO.

GitHub Copilot

Copilot’s advantage is that it lives where your code already is. Beyond completions and chat in all major IDEs, the Copilot cloud agent can be assigned an issue (or mentioned with @copilot), work in an ephemeral GitHub Actions environment, and open a pull request for review. It respects branch protections and works on one repository per task. On paid plans, completions are unlimited, while chat, agents and code review draw on monthly AI credits. For organisations already on GitHub Enterprise, the admin and policy controls are a strong argument.

Devin Desktop (formerly Windsurf)

In June 2026 Cognition rebranded the Windsurf editor as Devin Desktop. It keeps the Windsurf editor and adds an agent command centre for managing local and cloud agents, and supports the Agent Client Protocol so other compatible agents can run inside it. Existing Windsurf users were moved over automatically.

Open-source and bring-your-own-model tools

Cline, Continue and OpenCode are actively maintained open-source coding agents. Their big advantage is model freedom: point them at any API or at a model you host yourself, which matters when code must not leave your network. Pair them with a self-hosted model from our open-weight LLMs guide. The trade-off is more setup and less polish.

Choosing by workflow

If your team…	Start with
Lives in the terminal and wants an agent for large tasks	Claude Code or Codex CLI
Wants the best AI-native editor experience	Cursor or Devin Desktop
Is standardised on GitHub and wants issue → PR automation with admin controls	GitHub Copilot
Must keep code on its own infrastructure	Cline, Continue or OpenCode with a self-hosted model
Is budget-constrained and experimenting	Free tiers: Copilot Free, Cursor Hobby, Gemini CLI
Wants AI review on every pull request	Copilot code review, Cursor Bugbot, or Claude Code in CI

Many teams combine two: an editor tool for daily work and a terminal or cloud agent for bigger jobs. The underlying model matters too; see best LLM for coding in 2026.

Security considerations

AI coding assistants read your source code and can run commands. Treat rollout like any privileged tool.

• Data use and retention. Check whether your plan allows prompts and code to be used for training, how long data is kept, and where it is processed. Business and enterprise tiers usually offer stronger terms; get them in writing.
• Secrets. Keep .env files and credentials out of the agent’s reach. Use ignore files and secret scanning, and never paste production keys into a chat.
• Command permissions. Require approval for shell commands, network access and file deletion, at least until you trust the setup. Prefer sandboxes or containers for autonomous runs.
• Prompt injection. Issues, pull request comments, web pages and dependency READMEs can contain instructions aimed at the agent. Limit what an agent can do after reading untrusted content.
• MCP servers and extensions. They are code with access to your systems. Vet them, pin versions and grant minimal scopes.
• Review everything. AI-written code goes through the same pull request review, tests and security scanning as human code. Our web app security checklist is a useful baseline.
• Licensing and provenance. Check your vendor’s policy on code that matches public repositories, if that matters for your product.

How to trial assistants fairly

1. Pick two or three tools that fit your workflow.
2. Use them for two weeks on real tickets, not toy examples.
3. Track tasks completed, review time, defects found later and cost.
4. Ask developers what they would keep. Adoption beats benchmarks.
5. Write down the configuration that worked (instructions files, rules, allowed commands) so the whole team gets it.

Key takeaways

• All major assistants now do agentic, multi-file work; choose by workflow fit, not hype.
• Claude Code and Codex are agent-first and terminal-native; Cursor and Devin Desktop are AI-native editors; Copilot is strongest inside GitHub.
• Pricing mixes subscriptions with usage allowances or credits. Heavy agent use needs a budget and monitoring.
• Open-source tools with self-hosted models are the answer when code cannot leave your network.
• Lock down secrets, command permissions and MCP servers, and review AI code like any other code.

Rolling out AI coding tools in your team

Getting value from these tools takes more than licences: project instructions, safe permissions, CI integration and sometimes a self-hosted model for sensitive code. Our technical consulting service helps teams choose, configure and secure AI coding assistants for how they actually work. If you’d like help planning a rollout, contact us.