Duolingo vs Loom
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Duolingo and Loom (Async Video Messaging for Work) both appear on the Smoower Developer Ecosystem Index.
Duolingo (rank #338) holds a modest lead over Loom (rank #693) on the overall Smoower ecosystem score (43 vs 31). The gap of 12 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Duolingo is slightly ahead of Loom. On education (docs, guides and learning material for developers), Loom is slightly ahead of Duolingo. On community (issue response, PR reviews and discussion health), Duolingo is clearly ahead of Loom. On reach (how visible the ecosystem is beyond its own repos), Duolingo is clearly ahead of Loom. On momentum (release cadence and how fast the ecosystem moves), Duolingo is slightly ahead of Loom.
Duolingo carries 1,721 GitHub stars across 12 public repos, with 8 repositories active in the last 90 days and 11 external contributors on record. Loom shows 50 stars across 32 public repos, 5 active in the last 90 days and 1 external contributors. The star gap on its own does not decide the comparison, but Duolingo's footprint is roughly 34.4x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
Duolingo is the stronger read for anyone weighting reach. Loom looks better where education 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.
Side-by-side metrics
| Metric | Duolingo | Loom |
|---|---|---|
| Ranking | ||
| Overall rank | #338 | #693 |
| Pillars | ||
| Overall | 43 | 31 |
| Code | 44 | 37 |
| Education | 47 | 52 |
| Community | 37 | 11 |
| Reach | 49 | 3 |
| Momentum | 38 | 30 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 1,721 | 50 |
| Forks | 267 | 13 |
| Public repos | 12 | 32 |
| Active repos (90d) | 8 | 5 |
| External contributors | 11 | 1 |
| Avg polish | 51 | 32 |
| Avg AI-readiness | 30 | 34 |