Cohere vs TabbyML

Cohere (Empowering enterprises with private, powerful AI.) and TabbyML both appear on the Smoower Developer Ecosystem Index.

Cohere (rank #278) holds a modest lead over TabbyML (rank #569) on the overall Smoower ecosystem score (46 vs 35). The gap of 11 points reflects composite signals across code, docs, community and reach.

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

Cohere carries 6,555 GitHub stars across 62 public repos, with 17 repositories active in the last 90 days and 15 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 5.2x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

Cohere is the stronger read for anyone weighting education. 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.