OpenAI vs TabbyML

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

OpenAI (rank #55) holds a meaningful lead over TabbyML (rank #569) on the overall Smoower ecosystem score (60 vs 35). The gap of 25 points reflects composite signals across code, docs, community and reach.

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

OpenAI carries 824,906 GitHub stars across 263 public repos, with 48 repositories active in the last 90 days and 524 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 OpenAI's footprint is roughly 24.3x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

OpenAI 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.