PR Review Cost

AI PR review cost is not one prompt. The useful unit is one reviewed pull request, including every model pass, diff context, repo retrieval, reranking, cache behavior, infra overhead, and any monthly repo-index refresh that supports the reviewer.

Question

How do I estimate AI PR review cost per pull request?

Quick answer

Formula: repo_refresh_share_usd = repo_refresh_monthly_usd / monthly_pr_reviews

Formula: cost_per_pr_review_usd = generation + retrieval + reranking + repo_refresh_share_usd + vector_db + cache + infra

Formula: optional_margin_pct = (review_price_or_chargeback_usd - cost_per_pr_review_usd) / review_price_or_chargeback_usd * 100

Assumption: one PR review can include multiple model requests, not only the final review comment.
Assumption: diff tokens, retrieved repo context, and reranked candidate files should stay visible as separate drivers.
Assumption: repo refresh is a fixed monthly term amortized across monthly PR reviews.

Example: if generation, retrieval, reranking, repo refresh share, vector, cache, and infra sum to $0.09 per reviewed PR, a $0.50 internal chargeback leaves $0.41 gross profit per review before human review time is considered.

Worked Example

A practical first pass is three model requests per PR: one diff summary, one risk scan with repo context, and one final review-comment pass. If the diff is large, the first cost lever is usually context width, not the per-token price row. Trim repeated rubric text and irrelevant files before switching model tier.

What To Compare Next

Use PR Review Cost for the unit cost per reviewed pull request. Use AI Coding Agent Cost when the buying unit is an active developer-month. Use AI Coding Plan Comparison when the question is which fixed plan or usage-priced lane should fund the workflow.

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Model review passes, diff context, repo retrieval, and refresh cost before packaging AI PR review or comparing coding-tool plans.

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