Sourcegraph vs TabbyML

Sourcegraph (Helping developers search, understand, and write code in complex codebases with AI) and TabbyML both appear on the Smoower Developer Ecosystem Index.

Sourcegraph (rank #152) holds a modest lead over TabbyML (rank #569) on the overall Smoower ecosystem score (52 vs 35). The gap of 17 points reflects composite signals across code, docs, community and reach.

On code quality (the state of repositories, tests, releases and polish), Sourcegraph is clearly ahead of TabbyML. On education (docs, guides and learning material for developers), Sourcegraph is ahead of TabbyML. On community (issue response, PR reviews and discussion health), Sourcegraph is slightly ahead of TabbyML. On reach (how visible the ecosystem is beyond its own repos), TabbyML is slightly ahead of Sourcegraph. On momentum (release cadence and how fast the ecosystem moves), Sourcegraph is clearly ahead of TabbyML.

Sourcegraph carries 33,115 GitHub stars across 601 public repos, with 68 repositories active in the last 90 days and 17 external contributors on record. TabbyML shows 34,010 stars across 18 public repos, 5 active in the last 90 days and 12 external contributors.

Sourcegraph is the stronger read for anyone weighting momentum. TabbyML looks better where reach is the deciding factor. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.