Compare / CodeRabbit

arnx and CodeRabbit do different jobs.

One reviews the pull request. One tests the change before it.

CodeRabbit is a hosted AI reviewer that comments on pull requests for a whole team, in any language, on the common code hosts. It also has an IDE extension and a CLI. arnx is an open-source CLI that a developer or their coding agent runs on their own machine once a change is finished. It writes tests for what looks broken, runs them in Docker, reruns each failure on the code before the change, and reports the tests that failed.

So the question is rarely which one to pick. CodeRabbit covers every pull request with review comments. arnx covers one change at a time with executed tests, in three languages, and lets you keep the useful tests as regression checks. They fit at different points of the same workflow.

Side by side

arnx 0.1.11 and CodeRabbit, from each product's own documentation on 2026-11-12
	arnx	CodeRabbit
Where review happens	On the developer's machine, after a change is finished and before the commit or pull request. Run by the developer or by their coding agent.	Pull requests, plus an IDE extension and a CLI: Review uncommitted changes as you code, apply fixes instantly, integrate seamlessly with your AI coding agents, or run reviews in CI/CD pipelines.
Installation	`npm install -g @arnx-dev/arnx` or a standalone binary, then `arnx init`. Needs Docker. No code-host app.	Sign up with a Git platform account and add repositories (quickstart). The CLI installs with `curl -fsSL https://cli.coderabbit.ai/install.sh \| sh`, then `cr auth login` (CLI docs).
Output	A local report, `review.md`, where each finding is a test file you can run, with its failure output. arnx posts no pull request comments.	Review comments on the pull request, with summaries, security findings, improvement suggestions and one-click fixes.
Test generation and execution	Always. It writes tests for what looks broken and runs each one 3 times in a local Docker sandbox with no network.	On request, on the Team plan and above, in open beta: Receive tests in a separate PR or as a new commit; your CI runs them. Linters and analyzers run automatically in secure sandboxed environments. A separate beta feature, runtime verification, runs a guide in an isolated test environment that it prepares for the scanned commit. We did not find in their documentation that a pull request review runs your project's test suite.
Before and after comparison by running code	Yes. Each failing test is rerun on the code before the change. The report says whether it is a regression, was already failing, or covers new code.	We did not find this in their documentation.
Developer triage	`arnx triage`: mark each issue real, intended, noise or rewrite, and answer arnx's questions. A second model confirms or disputes each finding first.	Reply in the pull request. Replies become learnings: it learns your team's code-review preferences based on chat interactions. Commands pause, resolve or rerun a review.
Keeping regression tests	`arnx accept` keeps the tests of real issues in `.arnx/tests/`, pinned by sha256. `arnx check` reruns them with no model calls.	Generated unit tests land in the repository as a commit or pull request. Custom pre-merge checks are natural language instructions that run in a secure, read-only sandbox.
Languages and platforms	Python (pytest), JavaScript and TypeScript (vitest, jest, node:test, bun), Rust (cargo-nextest, early). macOS and Linux; Windows through WSL 2. Any Git repository, no code host needed.	CodeRabbit works with all programming languages, with varying proficiency. GitHub, GitLab, Bitbucket and Azure DevOps (platforms).
Where code is processed	Tests and tool calls run locally. The diff, the files the reviewer reads, the tests and their output go to your own model providers, or to arnx Cloud if you choose it.	Hosted: Sandboxed cloud execution with your full repository cloned. Your code is shared with OpenAI and/or Anthropic for reviewing purposes only. Self-hosting is for Enterprise customers with 500 or more user seats.
Cost model	Open source (Apache-2.0) with your own model keys: you pay providers per review, capped by `review_usd` ($3.00 by default). Our own reviews ranged from $0.17 to $3.19. Or prepaid arnx Cloud credit.	Per seat. From the plans page: Essentials $24 per developer per month billed annually, or $30 month-to-month, Team $48 or $60, Advanced $72 or $90, Enterprise custom. The Free plan covers PR summarization only, with reviews through the VS Code extension and CLI. Open-source projects receive Team features with no paid subscription required.

Both products can generate tests. The difference is the default. CodeRabbit writes tests when you ask and its review output is comments. arnx's only output is tests it ran.

When CodeRabbit is the better choice

You want every pull request reviewed for a whole team without anyone running a command.
Your code is not Python, JavaScript, TypeScript or Rust. CodeRabbit states it works with all programming languages.
You want comments in the pull request, on GitHub, GitLab, Bitbucket or Azure DevOps, with fixes you can apply there.
You want linters and security scanners in the same pass. Its architecture page describes 50+ static analyzers, linters and SAST tools.
You want a reviewer that learns team preferences from replies, and links to issues in GitHub, Jira or Linear.
You do not want to run Docker or manage model keys. It is a managed service with per-seat pricing, and free Team features for open-source projects.

When arnx is the better choice

You want a finding you can run: a test, its failure, and whether it passed before the change.
You want to check a coding agent's work before a pull request exists. The arnx skill lets the agent run the review and fix the code against the accepted tests.
You want to keep the tests. Accepted tests are pinned and rerun by arnx check on later changes with no model calls.
You want open source (Apache-2.0), your own model keys, prompts you can edit, and tests that run only on your machine.
You pay per review, not per seat, and set the cap yourself.

Using both

Run arnx on your machine when the change is done: triage the findings, fix what is real, and commit the accepted tests with the fix. Then open the pull request and let CodeRabbit review it for the team. arnx does not replace a pull request reviewer, and it posts nothing there. One example of arnx on a repository that already used an automated pull request reviewer is the Hummingbot case study.

What arnx does not do

Three languages only: Python, JavaScript and TypeScript, and Rust (early). It works best on single-package Python and TypeScript repositories.
It needs Docker and a project with an existing test suite. Code in no such project is reported as not reviewed. Tests that run only in a browser are not run.
A review takes minutes, not seconds, and the first one also sets up the test environment (it stops at 10 minutes). Changes over 200 KB are refused; review a long branch in parts.
It posts nothing to a pull request. The report is a local file.
Findings can be wrong. A failing generated test shows an assertion fails, not that the code is wrong, and the second model can agree with a wrong test. Our own counts are in AI code review findings on unfamiliar repositories. Deciding stays with the developer.

Sources

Last reviewed 2026-11-12. Every statement about the other product comes from its own pages below, as they read that day. Products and prices change: check the vendor's pages before you decide. Found an error? Open an issue and we will correct it.

Last reviewed 2026-11-12 against arnx 0.1.11. The release documentation is canonical for your installed version.