Comparison

Built different from
CodeRabbit and CodeAnt

Not just cheaper — fundamentally more trustworthy. Every finding has a source.

FeatureGrapeRootCodeRabbitCodeAntGreptile
Graph-proven findingsReal import edgesLLM guessLLM guessPartial
Cross-repo blast radius
Committable suggestions
Rate limitsNone5–10/hr (Pro)NoneNone
Self-hosted at Pro tierEnterprise onlyEnterprise onlyEnterprise only
Free for open source5 reviews/moUnlimited100% discountQualified OSS
Price / user / month$15$24$24–30$30
BYOK (your API key)Self-hosted
Code leaves your serverNeverYesYesYes

“Every finding is graph-proven — we cite the exact import chain, not a guess.”

The one claim no competitor can match. CodeAnt's headline stat is 87.6% F1. GrapeRoot's is 0 graph-fabricated findings — because the graph either has the edge or it doesn't.

What a graph citation looks like

Graph-proven blast radius

index_set.go → compactor.go → shipper.go → store/chunk_store.go

vs token compression

GrapeRoot vs Headroom

Headroom (30k+ stars) compresses context after you select it. GrapeRoot selects the right context before you ever read a file. They solve different problems — and work best together.

DimensionGrapeRootHeadroom
What it doesSelects which context to sendCompresses context after selection
Works atUpstream (selection)Downstream (compression)
Knows your codebaseYes — graph of every symbol/edgeNo — stateless per request
Finds the right 8 filesYes — graph traversal queryNo — compresses whatever it receives
Cross-file relationshipsYes — import edges, call graphsNo — AST within a single file only
LosslessYes — original code untouchedNo — lossy by design (CCR recovery)
Token savings mechanismRead 8 relevant files not 40Shrink those 40 files by 60–92%
Open sourceNoYes — Apache 2.0, 30k+ stars
Works together?Yes — complementaryYes — complementary

“Headroom shrinks 40 files down. GrapeRoot tells you it's only 8 files you need.”

Token compression and context selection are complementary — not competitive. Run GrapeRoot to pick the right files, then Headroom to compress them. Together they give you the lowest possible token spend with the highest signal.