PolyAI vs TabbyML

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

PolyAI (rank #430) holds a narrow lead over TabbyML (rank #569) on the overall Smoower ecosystem score (40 vs 35). The gap of 5 points reflects composite signals across code, docs, community and reach.

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

PolyAI carries 86 GitHub stars across 6 public repos, with 6 repositories active in the last 90 days and 19 external contributors on record. TabbyML shows 34,010 stars across 18 public repos, 5 active in the last 90 days and 12 external contributors. The star gap on its own does not decide the comparison, but TabbyML's footprint is roughly 395.5x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

PolyAI 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.