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Editorial snapshot from September 2026. Prices, models and interface labels may change; this is a practical guide, not a live product feed.

Terminal pair programming with repository maps, editable file context and Git integration.

Coding agent · Aider contributors · macOS · Windows · Linux

Suitable workflows

Small, reviewable code changes while keeping your own editor and model provider.

Limitations and billing

Model quality and context limits vary; inspect automatic Git changes and the selected files.

Capabilities we verified

Agent workflow · CLI surface · Bring your own key · Local models

This is an evidence-based shortlist, not an exhaustive feature inventory. Omitted capabilities have not been checked for this record.

Pricing & usage

See official pricing

Free CLI; model-provider or optional service charges. The cost of metered usage or an external agent can be separate from the subscription.

Models & access

Use supported hosted APIs or local backends such as Ollama and LM Studio.

Verified families: Claude, GPT, Gemini, Grok, DeepSeek, Local.

Install and start the CLI

Python 3.8–3.13 for aider-install; it creates a separate runtime environment.

python -m pip install aider-install
aider-install

Open your project folder in a terminal, then run:

aider

Account and authentication

Configure the API key for your chosen provider, then select its model when launching aider.

Project configuration and tools

Add only the relevant files to the chat. The repository map supplies broader code context.

First task to try

Add one source file and its test, request a fix, then inspect the Git diff and run tests.

Related CLI tools

All AI CLI tools →

OpenCode — An open-source coding agent with a terminal UI and configurable model providers.

Pi — A minimal terminal coding agent with configurable providers, sessions and extension packages.

Claude Code — Anthropic’s coding agent for terminal and editor workflows.

Project evaluation checklist

  1. Open a small, familiar project and confirm that your essential language tooling works.
  2. Give the agent one bounded change with an observable acceptance criterion.
  3. Review the diff, run the project’s checks and compare the result with your current workflow.
  4. Inspect usage after the task. Estimate a month of similar work, including any separate model or agent bill.

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