Reply vs TabbyML

Reply (AI sales engagement for email, LinkedIn, SMS & calls. Open APIs, SDKs, and MCP server for developers building on Reply. Builders of Jason, the AI SDR.) and TabbyML both appear on the Smoower Developer Ecosystem Index.

TabbyML (rank #569) holds a narrow lead over Reply (rank #662) on the overall Smoower ecosystem score (35 vs 32). The gap of 3 points reflects composite signals across code, docs, community and reach.

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

Reply carries 0 GitHub stars across 3 public repos, with 2 repositories active in the last 90 days and 0 external contributors on record. TabbyML shows 34,010 stars across 18 public repos, 5 active in the last 90 days and 12 external contributors.

Reply is the stronger read for anyone weighting momentum. TabbyML looks better where community 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.