CodeRabbit vs Greptile — per-seat or per-review, and which flips first

The short version

• Large team, few PRs → Greptile (headcount is not billed)
• Small team, many PRs → CodeRabbit (seats are fixed, volume is not)
• Public repositories only → CodeRabbit (free on public repos)
• You also want stacked-PR tooling → Graphite

1. Pricing side by side

Work the break-even. A team of ten opening 100 PRs a month pays $240 on CodeRabbit Essentials; on Greptile, 100 Base reviews is $100. The more people you have, the better Greptile looks.

Reverse it: three people opening 300 PRs a month pay $72 on CodeRabbit and $300 on Greptile. Small teams that ship frequently are cheaper on seats. Count your actual PR volume before comparing anything else.

2. The reviews are not the same shape

CodeRabbit optimises for the readability of a single pull request: a summary of the change, a walkthrough, line-level comments, and fix suggestions you can apply in one click. It fits the role of clearing obvious problems before a human reviewer arrives, not of being the reviewer.

Greptile optimises for whole-codebase context. It is more likely to surface that the change contradicts an existing implementation in another file, or that the same logic already exists elsewhere. The credit tiers (Base, Plus, Apex) control how deeply it reads.

Neither replaces human review. Whether the design is sound and whether it matches the specification stay with people. What the AI reliably catches is the layer below that: type mismatches, missing error handling, inconsistent naming.

3. What you can use free, indefinitely

If you publish open source, CodeRabbit is free on public repositories. For a solo developer with public repos that is review at no cost.

Greptile's free Starter tier gives 50 credits a month for one developer with unlimited repositories — 50 Base reviews a month. Non-commercial open-source projects can apply for free access, and pre-Series-A startups under $2M of trailing twelve-month revenue are offered 500 credits a month for six months.

4. What decides whether it sticks

Immediately after adoption there are too many comments, people try to address all of them, and pull requests stall. Run the first two weeks with the rule that comments are advisory and acting on them is optional, and use that time to work out which categories are genuinely useful.

The opposite failure is leaving it alone until nobody reads the bot. Unread automated comments actively harm review by burying the human ones. After two weeks, decide which categories to disable and put that in the configuration. Whether a team does this tuning is what separates the tool becoming an asset from it becoming noise.

Frequently asked questions