aider vs cline: terminal git commits versus a multi-surface agent
aider is a Python terminal pair programmer that edits your repo and commits each change, so the diff and the git log are the interface. cline is a TypeScript agent engine shipped as a VS Code extension, JetBrains plugin, CLI, Kanban board and Node SDK, with checkpoints and .clinerules as its control surface. They are not the same shape of tool, and for some teams they are complements rather than competitors.
At a glance
| Project | Aider-AI/aider | cline/cline |
|---|---|---|
| Licence | Apache-2.0Permissive: commercial use allowed | Apache-2.0Permissive: commercial use allowed |
| Maintenance | Commits in the last six monthsLast push May 22, 2026 | Commits in the last six monthsLast push September 25, 2026 |
| Language | Python | TypeScript |
| GitHub stars | 49,276 | 69,303 |
| Read more | Our analysisGitHub | Our analysisGitHub |
Which one to choose
Choose aider if you work in a terminal, every project is a git repository, and you want each AI change to land as a discrete commit you can diff, revert or amend with the git commands you already know.
Choose cline if you want a reviewable diff and checkpoint history inside an editor, or you need the same agent engine behind a CLI, a task board and an SDK, and you are prepared to constrain it with .clinerules and human approval.
Where the work happens: git history versus editor surface
The two projects answer a different first question. aider asks where the change should be recorded; cline asks where the change should be reviewed.
aider's README describes it as AI pair programming in your terminal, and its git integration is presented as a feature in its own right: it automatically commits changes with sensible commit messages so you can use familiar git tools to diff, manage and undo AI changes. The commit is the unit of work. If you want to reject an edit, you revert a commit. If you want to see what the model did across a session, you read the log. That is a workflow that assumes git is already the spine of your project.
cline's README leads with the surfaces it ships: a VS Code extension, a JetBrains plugin, a CLI, a Kanban board and a Node SDK, all powered by the same engine. In VS Code and JetBrains, the README states that every edit shows up as a diff you can review, modify or revert, and that all changes are tracked with checkpoints so you can undo the agent's work. The checkpoint is the unit of work. That is a workflow that assumes a human is watching an editor pane and deciding whether to keep each step.
Neither approach is strictly stronger. Commits survive outside the tool; checkpoints live inside it. A commit can be pushed, reviewed in a pull request and bisected. A checkpoint is faster to undo mid-session but is tied to the agent's own history, and the README does not document what happens to checkpoints if you move the project directory or work across machines.
Getting each one running, and what it needs first
aider is installed through pip. The README's getting started block shows `python -m pip install aider-install`, then `aider-install`, then changing into your codebase and starting it with an explicit model and API key, for example `aider --model deepseek --api-key deepseek=<key>` or `aider --model sonnet --api-key anthropic=<key>`. The tool is a wrapper around a model provider. There is no bundled model and no hosted service in the README; you bring the key. Its own documentation lists Claude 3.7 Sonnet, DeepSeek R1 and Chat V3, OpenAI o1, o3-mini and GPT-4o as the models it works best with, while stating it can connect to almost any LLM including local models.
cline is distributed through the channels its README names: install the VS Code extension from the Visual Studio Marketplace, the JetBrains plugin from the JetBrains Marketplace, or run `npm i -g cline` for the terminal. The SDK is installed with `npm install @cline/sdk`. The README's provider table is long: Anthropic, OpenAI, Google, OpenRouter, Vercel AI Gateway, AWS Bedrock, Azure and GCP Vertex, Cerebras and Groq, Ollama and LM Studio, and any OpenAI-compatible endpoint. That breadth matters if your organisation already routes model traffic through a gateway or a cloud account.
The first real difference in setup is the number of moving parts. aider needs Python, pip and a provider key. cline needs Node for the CLI and SDK, an editor for the extension, and a provider or local runtime; if you use the JetBrains plugin, note that the README's product index states plainly that the JetBrains plugins are currently not being open-sourced, so that component is a separate dependency from the rest of the stack. Verify it on its own terms.
How each tool decides what to touch
aider's answer is the repository map. Its README lists mapping your codebase as a headline feature and says the map helps it work well in larger projects. The practical consequence is that context selection is automatic and repo-wide: you do not hand it a list of files, you let it build a map and then ask for a change. That is convenient in a large, conventionally structured repository and less predictable in a monorepo where several unrelated packages share similar names. The README does not document a per-directory scoping mechanism for the map.
cline's answer is rules and skills. The README describes `.clinerules` files that define project-specific rules: coding standards, architecture conventions, deployment procedures, testing requirements. It states that rules are picked up automatically by the CLI, the VS Code extension and the JetBrains plugin, and that skills let the model load specific rules when needed. This is a written contract rather than an inferred one. You can say which directories are off limits, which test command must pass, and what style the code follows. The cost is that someone has to write and maintain those files, and a rule that is vague will not constrain anything.
cline also has a Plan and Act split that aider does not describe in the same terms. In Plan mode, according to the README, cline explores the codebase, asks clarifying questions and lays out a strategy; you then switch to Act mode to execute it. The README states that every file edit and terminal command requires your approval, or you can toggle auto-approve and let it run autonomously. aider's loop is different in kind: it makes changes, then linting and testing run automatically, and the README says aider can fix problems detected by your linters and test suites. One is a gate before the edit; the other is a check after it.
Running it on a team, in CI, and at scale
aider's scaling story is git's scaling story. Because each change is a commit, review happens in whatever your team already uses for code review. There is no server to run and no shared state beyond the repository. The constraint is that aider is an interactive terminal session; the README documents use from within an IDE or editor through its watch mode, where you add comments to your code and aider picks them up, but it does not describe a headless batch mode for unattended runs. If you want an agent working through a queue of tasks overnight, aider's README does not offer that.
cline's README does. The CLI section says it supports interactive chat or fully headless operation for CI/CD and scripting. The Kanban component is described as running many agents in parallel from a web-based task board, where each card gets its own worktree, auto-commit and dependency chains. The SDK is described as the same engine behind the CLI, Kanban, VS Code extension and JetBrains plugin, with custom tools, multi-agent teams, connectors and scheduled automations. That is a much larger operational surface, and it is also more to operate: a task board, worktrees, auto-commit and a Node service are things that can fail independently.
The honest trade is this. aider gives you one process and git. cline gives you an engine you can embed in several places, and the price is that you now own the orchestration, the approval policy and the rules that keep parallel agents from colliding. The README does not document conflict resolution between Kanban cards that touch the same files, so treat parallel worktrees as something to test on your own repository before trusting it.
Where each one is weaker
aider's weakness is that it is a wrapper with no bundled model. If your team cannot get an API key approved, or your privacy policy forbids sending code to a hosted provider, aider is only as usable as the local model you can run, and the README's own list of models it works best with is entirely hosted. Its interface is a terminal, which is a strength for some and a hard stop for others; the README's IDE story is a watch mode, not a full editor integration with inline diffs. The README does not document checkpoint-style undo, so recovery means git, which is fine if you commit often and awkward if you do not.
cline's weakness is surface area. Five components, a plugin API and a Kanban board are more than most teams need, and the README says the JetBrains plugin is not open-sourced, which splits the dependency story. Its default posture is human-in-the-loop: the README states that every edit and command requires approval unless you toggle auto-approve. That is the right default, but it means cline does not save you attention by default, it redirects it. The README also does not document a support contract or a hosted offering, so if you need an SLA, neither project's README provides one.
On maintenance, the two differ noticeably. cline's last push is 2026-09-19, one day before today, and its recent releases include desktop-v0.0.20 on 2026-08-28, v4.1.16 on 2026-08-26 and sdk v0.0.81 on 2026-08-26. aider's last push is 2026-05-22, four months earlier, and its most recent release listed is v0.86.0 from 2025-08-09. Neither repository is archived and both are Apache-2.0. But a four-month gap in pushes and a release cadence that stops in August 2025 is a fact a reader should weigh, not a verdict. Check the release history yourself before standardising on it.
Licence, model terms, and what to verify before committing
Both projects are Apache-2.0, which permits commercial use. That covers the code in each repository. It does not cover the model you connect, and this is where teams most often get surprised.
With aider, the licence question is really a provider question. The tool is a wrapper; your code leaves your machine and reaches whichever endpoint you configured. Apache-2.0 on aider says nothing about Anthropic's, OpenAI's or DeepSeek's retention and training terms. Check each provider's terms separately, and if you use a local model through aider, check the model's own licence, which is not aider's licence.
With cline, there is an extra wrinkle the README states directly: the JetBrains plugins are not open-sourced. Everything else in the product index points at a directory in the repository, but that row does not. So a JetBrains rollout is not simply an Apache-2.0 deployment, and the plugin should be reviewed as a separate dependency with its own terms.
Before adopting either, verify three things on your own machine. For aider: that your team's approved provider is reachable, that a small repository produces a useful repo map, and that your lint and test commands work inside aider's automatic loop. For cline: that your chosen provider is reachable from the machine running the agent, that `cline mcp` can list your MCP servers, and that a test edit is recoverable through the checkpoint history. These are the checks that decide whether the tool fits, and none of them can be settled by reading a README.
Bottom line
Pick aider if your team lives in git and wants AI changes to arrive as reviewable commits with no server to run; pick cline if you want the diff and checkpoint review inside an editor, or you need one agent engine behind a CLI, a task board and an SDK. If you are unsure, start with aider on one repository because its setup is a pip install and a key, then try cline's CLI on the same repository to see whether checkpoints and .clinerules change how you review. Before either becomes a team standard, verify provider terms, confirm the model you intend to use is actually reachable, and test recovery: revert a commit in aider and roll back a checkpoint in cline. The maintenance gap is real, so check the release history yourself rather than assuming either cadence will continue.