LlamaIndex vs TabbyML

LlamaIndex and TabbyML both appear on the Smoower Developer Ecosystem Index.

LlamaIndex (rank #63) holds a meaningful lead over TabbyML (rank #569) on the overall Smoower ecosystem score (59 vs 35). The gap of 24 points reflects composite signals across code, docs, community and reach.

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

LlamaIndex carries 99,809 GitHub stars across 135 public repos, with 48 repositories active in the last 90 days and 241 external contributors on record. TabbyML shows 34,010 stars across 18 public repos, 5 active in the last 90 days and 12 external contributors.

LlamaIndex is the stronger read for anyone weighting momentum. TabbyML makes more sense for teams already using its adjacent tools. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.