AI Code Review in 2026: CodeRabbit vs Greptile vs What You Already Pay For

An AI reviewer that finds one real bug a week is worth the money. The same reviewer leaving eleven confident comments about naming conventions on every pull request costs you something that does not appear on an invoice: it teaches the team to scroll past review comments, including the ones a human wrote.

That is the whole evaluation. Everything else is pricing structure, and pricing structure at least is knowable. Prices below came off vendor pages, re-checked on 2 September 2026. Two things changed since I first wrote this: CodeRabbit renamed its plans, and I added Kodus, which sells the same thing on a third pricing structure.

What each one charges

CodeRabbit is $24 per developer per month on Essentials with annual billing and $48 on Team, which adds multi repository analysis, custom pre merge checks, and post merge actions. An Advanced tier sits above those at $72. Monthly billing costs 20 percent more on every tier. Essentials and Team were called Pro and Pro Plus until recently, so any comparison you read that names those tiers is describing a price list that no longer exists. Public repositories are reviewed for free, which is a genuinely useful way to see the output style before paying. Self hosting exists on Enterprise only.

Greptile prices differently: $30 per seat per month on Pro, but seats carry 50 credits and one credit is one standard review, with extra credits at $1 each. The free Starter tier gives a single developer 50 credits a month across unlimited repositories. Self hosting is an Enterprise option.

The unit difference matters more than the $6. A per seat plan with unlimited reviews encourages you to run the reviewer on everything, including the one line dependency bump. A credit plan makes you decide which pull requests are worth a dollar, which is either healthy discipline or an annoying meeting, depending on your team.

Kodus is on neither axis. Its Community tier is $0 with unlimited pull requests and unlimited users, self hosted through Docker Compose or Helm or run on their servers, and you supply the model key and pay the provider directly at list price. Teams is $10 per developer per month for the hosted version with the limits lifted. What the free tier caps is not volume but configuration: ten custom rules and three plugins. That cap lands on exactly the part that decides whether these tools are worth having, because rules are what move a reviewer from noisy to useful, and ten runs out faster than it sounds once you start writing them per path.

The code is on GitHub as kodustech/kodus-ai under AGPL-3.0, with an open core split written into the license: anything carrying .ee. in its filename or living under an ee/ directory is commercial and needs a paid license. The repository had 1,346 stars and a commit from that morning when I checked on 2 September 2026. I have not run it. Everything in this section came off the pricing page, the license file, and the GitHub API, not from a month of its comments landing on my own pull requests, and the thing I cannot tell you is the only thing that matters: whether its output is worth reading.

If you already pay for GitHub Copilot, you have one more option that costs no additional subscription. Copilot’s review draws down the same credit balance as its other agent features, where one credit is one cent, so it is metered rather than free but it arrives inside a bill you already approved.

What they are actually good at

The strength of a repository aware reviewer is context a linter cannot have. It can notice that the function you changed is called from three places that assume the old return shape, that this migration has no down path when every other migration in the repository does, or that the error you are swallowing is the one the retry logic upstream depends on seeing.

The weakness is confidence without stakes. These tools do not know which parts of the codebase are load bearing and which are a script somebody runs twice a year, so severity is flat. A style nit and a race condition arrive in the same voice, in the same list, on the same pull request.

That flatness is why the configuration work matters more than the vendor choice. Turning off entire comment categories, restricting the reviewer to certain paths, and setting a minimum severity are what move the tool from noisy to useful. All three support custom rules, and the teams that get value out of any of them are the ones that spent an afternoon writing those rules rather than accepting defaults.

The measurement nobody runs

Before renewing any of these, the number worth having is the fraction of comments that led to a change. It is tedious to collect and it settles the argument immediately.

A reviewer whose comments get acted on a third of the time is doing better than most human reviewers on a large diff. One that lands under a tenth is training your team to ignore the review surface, and the correct response is to narrow its scope rather than to cancel it, because a narrow reviewer that only comments on error handling and migrations is a genuinely good tool.

Where it fits next to the security scanners

An AI reviewer is not a replacement for dependency and secret scanning, and the overlap is smaller than the marketing suggests. The scanners answer a different question: is there a known vulnerable version in the tree, did somebody commit a key, does this dependency do something new since the last release. That is pattern matching against a database, and it is more reliable than a model’s judgment because it is not judgment.

Run both, and expect them to disagree about what matters. The security scanner comparison covers that side; this one is about the reviewer that reads intent.

Picking

Small team, mostly public repositories or a single codebase, wants to try before paying: CodeRabbit’s free public repository reviews, then Essentials at $24 if the comments hold up.

Many repositories and a preference for paying per review rather than per person: Greptile, and the credit model will make you selective, which is not the worst outcome.

Wants the reviewer on its own infrastructure without an Enterprise contract, or objects to a per seat charge stacked on top of model tokens already being bought: Kodus, with the ten rule ceiling on the free tier arriving sooner than the pricing page suggests.

Already paying for Copilot across the team and unsure whether AI review is worth a separate contract: use what you have for a month, look at the credit draw, and let that decide. It is the cheapest experiment available and it uses the tooling everyone already has installed.

Whichever you pick, turn off two thirds of what it wants to comment on in the first week. The tools are configured by default to demonstrate value, which is not the same thing as providing it.