Cline vs Aider vs Continue: Which AI Coding Assistant to Use

Cline is the best fit if you want an agent inside VS Code or JetBrains that asks before every change. Aider is the best fit if you live in the terminal and want every AI edit committed to git. Continue is the one to be careful with: its repository is now read-only and no longer actively maintained. All three are open source (Apache-2.0) and work with your own model API key, so the real cost is the model usage, not the tool.

A note on the name: the old title of this post said “AIDR”. The tool is called Aider (aider.chat), and this version of the post uses the correct name. Details below were checked against each project’s official site and GitHub page in October 2026. These tools change fast, so check the docs before you commit to one.

Quick comparison

	Cline	Aider	Continue
Where it runs	VS Code extension, JetBrains plugin, CLI, desktop app	Terminal (can also work alongside an editor)	VS Code extension, JetBrains plugin, CLI (cn)
Style	Agent: reads files, edits, runs commands, uses a browser	Pair programmer in a chat prompt	Chat, edit, autocomplete and agent modes
Safety model	Asks approval for each edit and command by default; checkpoints to undo	Auto-commits each change to git; you undo with git	Depends on the mode you use
Models	Anthropic, OpenAI, Gemini, OpenRouter, Bedrock, Azure, Ollama, LM Studio, any OpenAI-compatible API	Most cloud and local models	Configurable providers and model roles
License	Apache-2.0	Apache-2.0	Apache-2.0
Status	Active	Active	Repo read-only, no longer actively maintained

Cline

Cline is a coding agent. Instead of only completing the line you are typing, it can explore your project, edit several files, run terminal commands and use a browser. It runs as a VS Code extension, a JetBrains plugin, a CLI (npm i -g cline) and a desktop app.

• Plan and Act modes. In Plan mode it reads the codebase, asks questions and outlines a strategy. In Act mode it carries the plan out.
• Approval by default. Each file edit and terminal command needs your OK unless you switch on auto-approve. Edits show up as diffs, and checkpoints let you roll back.
• Bring your own model. It supports Anthropic, OpenAI, Gemini, OpenRouter, AWS Bedrock, Azure, Ollama and LM Studio, plus any OpenAI-compatible API. Cline also sells its own usage-billed access and a subscription called ClinePass ($9.99 per month as of October 2026).
• MCP. You can connect it to databases, APIs and other systems through MCP servers.

Trade-offs. Agents burn tokens: a task that reads many files and loops on failing commands can cost far more than a single chat question. Approving every step is safe but slow, and turning on auto-approve removes the safety net, so use it on a branch you can throw away.

Aider

Aider is “AI pair programming in your terminal”. You cd into your repo, start aider with a model, add the files you want changed, and describe the change in chat.

python -m pip install aider-install
aider-install
cd my-project
aider

• Git is the safety net. Aider commits each change with a generated message, so reviewing is git diff and git log, and undoing is a normal git operation (inside Aider, /undo reverts its last commit).
• Repo map. It builds a map of your whole codebase so it can work on projects larger than the files you added by hand.
• Lint and test. It can run your linter and tests after changes and try to fix what fails.
• Extras. Voice input, images and web pages as context, and over 100 languages.

Trade-offs. There is no graphical diff review unless you use your editor’s git tools, and the workflow of choosing which files to add takes some getting used to. If you do not like a terminal-first workflow, you will not like Aider.

Continue

Continue was an open-source assistant for VS Code and JetBrains with four modes: chat, edit (change code without leaving the file), autocomplete, and agent mode. It also has a CLI, cn, and is configured through a config.yaml where you choose models, MCP servers, rules and prompts.

The catch. As of October 2026 the GitHub repository (continuedev/continue) says it is no longer actively maintained and is read-only. The final 2.0.0 release removed anonymous telemetry, dropped authentication and fixed bugs. It still works, and it is Apache-2.0, so you can use or fork it. But you should not expect new model support, new features or quick fixes. If you want inline autocomplete with your own model, check whether that gap is acceptable before you build a workflow on it.

Which one should you pick?

• You want an agent in your editor that does multi-file work with approval: Cline.
• You like the terminal and want small, reviewable git commits: Aider.
• You want a free, self-hosted chat plus autocomplete setup and accept an unmaintained project: Continue, ideally pinned to a known version.
• You want to keep code on your machine: all three can talk to local models through tools such as Ollama, but quality depends on the model you can run. Check where each setting sends your code before you rely on it.

You do not have to choose one forever. They are all bring-your-own-key, so trying two on the same small task costs a few cents to a few dollars of model usage, and shows you more than any feature list.

Common mistakes when using AI coding assistants

1. Accepting code you have not run. Assistants write plausible code that is subtly wrong. Here is a typical example: you ask for a function that removes duplicates from a list, and you get this.

   def dedupe(items):
       return list(set(items))
   
   def test_keeps_order():
       assert dedupe([3, 1, 3, 2, 1]) == [3, 1, 2]
   
   try:
       test_keeps_order()
       print("pass")
   except AssertionError:
       print("fail:", dedupe([3, 1, 3, 2, 1]))

   It prints fail: [1, 2, 3], because a set does not keep the original order. A one-line test caught it. The fix is list(dict.fromkeys(items)), which keeps first-seen order and returns [3, 1, 2] here.

2. Giving no context. Name the files, the function, the expected behavior and how to run the tests. Vague prompts get generic code.
3. Letting an agent run on your only copy. Work on a branch, commit before you start, and review the diff before merging.
4. Skipping the fundamentals. If you cannot read the code the tool writes, you cannot review it. This matters most in coding interviews, where you will not have an assistant at all.

If you are learning to code or preparing for interviews

Use these tools to explain code you do not understand, and to review your solution after you have written it yourself. Do not use them to produce the solution first, because the skill you need in an interview is the one you skip. Practice problems such as Pair Count and Container with Most Water are good tests: solve them on your own, then ask an assistant for a critique and compare. For more on how these tools affect concentration, see what AI coding agents do to your flow state, and for a related comparison, Claude, GitHub Copilot and Visual Studio Code integration. If you want guided practice without AI writing the answers for you, AlgoCademy offers step-by-step coding lessons, which is a different job from what the three tools above do.