AssemblyAI vs sgl-project

AssemblyAI (Advanced Speech-to-Text) and sgl-project both appear on the Smoower Developer Ecosystem Index.

sgl-project (rank #278) holds a narrow lead over AssemblyAI (rank #401) on the overall Smoower ecosystem score (46 vs 41). 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), sgl-project is ahead of AssemblyAI. On education (docs, guides and learning material for developers), AssemblyAI is slightly ahead of sgl-project. On community (issue response, PR reviews and discussion health), sgl-project is clearly ahead of AssemblyAI. On reach (how visible the ecosystem is beyond its own repos), AssemblyAI is clearly ahead of sgl-project. On momentum (release cadence and how fast the ecosystem moves), sgl-project is clearly ahead of AssemblyAI.

AssemblyAI carries 1,025 GitHub stars across 67 public repos, with 8 repositories active in the last 90 days and 11 external contributors on record. sgl-project shows 38,333 stars across 26 public repos, 20 active in the last 90 days and 349 external contributors. The star gap on its own does not decide the comparison, but sgl-project's footprint is roughly 37.4x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

AssemblyAI is the stronger read for anyone weighting reach. sgl-project 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.