aicommits vs opencommit: AI-Generated Git Commit Messages Compared

You stage a change, type git commit, the cursor blinks, and for the third time today you write “fix stuff.” Two open-source CLIs want to take that decision off your hands by reading your staged diff and drafting the message: aicommits and opencommit. Both install as a global npm package, both wrap a large language model, and both can hook into git so a plain git commit triggers them. The differences show up in three places: where your diff gets sent, how much the tool lets you configure, and what happens when the generated message is wrong.

We installed both, pointed them at real staged diffs across a TypeScript repo and a Go service, and compared how they behave on the parts that actually matter day to day.

How each one works

aicommits (by Hassan El Mghari, published under the Nutlope account) keeps the surface deliberately small. You install it with npm install -g aicommits, set a key with aicommits config set OPENAI_KEY=sk-..., stage your changes, and run aicommits (the aic alias is shorter). It reads the staged diff, sends it to OpenAI, and prints a single message you accept or reject. aicommits --generate 3 returns three candidates to choose between instead of one. aicommits config set type=conventional switches the output to Conventional Commits format (feat:, fix:, and so on). To make it automatic, aicommits hook install adds a prepare-commit-msg git hook, after which a normal git commit is intercepted and the generated message is pre-filled into your editor.

opencommit (the oco command, by Dima Sukharev) runs the same core loop — stage, run oco, accept the suggestion — but exposes far more knobs. The headline difference is provider support. Out of the box it can talk to OpenAI, Anthropic, Azure, Google Gemini, and crucially Ollama for local models, selected with oco config set OCO_AI_PROVIDER=ollama. It can prefix messages with GitMoji emoji via OCO_EMOJI=true, write the message body in a non-English language with OCO_LANGUAGE, and — the feature most teams care about — read your existing commitlint config so generated messages obey rules you already enforce in CI. Its hook installs with oco hook set.

The practical upshot: aicommits is a focused tool that does one thing with minimal configuration. opencommit is a configurable platform that bends to an existing team workflow.

The real divide: who controls the model

Most head-to-head comparisons stop at “both write commit messages,” but the decision actually hinges on provider flexibility.

aicommits is OpenAI-first. That keeps setup short — one key, one provider, sensible defaults — and the generated messages were consistently clean and conventional in our runs. The cost is lock-in: if your employer bans sending source to OpenAI, or you’d rather run a local model, aicommits doesn’t have a first-class answer.

opencommit treats the model as a swappable backend. Point OCO_AI_PROVIDER at ollama and your staged diff never leaves your laptop — it goes to a local model like llama3 or qwen2.5-coder running on your own machine. For anyone working in a regulated codebase, or just allergic to per-token API bills, that single capability is the deciding factor. The tradeoff is quality: a small local model writes blander, less precise messages than a frontier API model, and you’ll feel that on large or subtle diffs.

Quality, speed, and the editing tax

Neither tool removes you from the loop, and that’s the right design. Both pre-fill a message you can edit before the commit lands — think of the output as a strong first draft, not a final answer. On small, single-purpose diffs (a renamed function, a bug fix in one file) both produced messages we’d accept verbatim. On large multi-file diffs, both tend to over-summarize into a vague “update multiple components,” because the model is compressing a lot of unrelated change into one line. The fix there is a discipline problem, not a tool problem: stage smaller, more atomic changes and the generated messages get sharper immediately.

Latency is similar — a round trip to a hosted model adds a second or two before your editor opens. With opencommit on a local model, speed depends entirely on your hardware; on an Apple-silicon laptop it was comfortably fast, on older machines noticeably slower.

Which one to install

Pick aicommits if you want the shortest path from install to working commits, you’re already an OpenAI user, and you don’t need emoji, local models, or commitlint integration. It does less, and that’s a feature — there’s almost nothing to configure and almost nothing to break.

Pick opencommit if any of these is true: your code can’t be sent to a hosted API (use the Ollama backend), your team enforces commitlint rules you want respected, you want GitMoji or non-English messages, or you simply want the freedom to swap models later without changing tools.

For most individual developers on personal projects, aicommits is the faster yes. For teams and privacy-sensitive work, opencommit’s flexibility earns its slightly heavier configuration.

If you’re already leaning on AI inside your editor, AI commit messages are a small extension of the same workflow — the assistant that wrote the diff can describe it too.