Magical tools for data.
Mage vs Runway
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Mage (Magical tools for data.) and Runway (Building AI to Simulate the World) both appear on the Smoower Developer Ecosystem Index.
Runway (rank #317) holds a narrow lead over Mage (rank #485) on the overall Smoower ecosystem score (44 vs 38). The gap of 6 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Runway is ahead of Mage. On education (docs, guides and learning material for developers), Mage is slightly ahead of Runway. On community (issue response, PR reviews and discussion health), Mage is ahead of Runway. On reach (how visible the ecosystem is beyond its own repos), Runway is ahead of Mage. On momentum (release cadence and how fast the ecosystem moves), Runway is ahead of Mage.
Mage carries 9,079 GitHub stars across 44 public repos, with 8 repositories active in the last 90 days and 22 external contributors on record. Runway shows 2,435 stars across 61 public repos, 16 active in the last 90 days and 0 external contributors. The star gap on its own does not decide the comparison, but Mage's footprint is roughly 3.7x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
Mage is the stronger read for anyone weighting community. Runway looks better where momentum 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 | Mage | Runway |
|---|---|---|
| Ranking | ||
| Overall rank | #485 | #317 |
| Pillars | ||
| Overall | 38 | 44 |
| Code | 34 | 45 |
| Education | 71 | 65 |
| Community | 38 | 22 |
| Reach | 40 | 49 |
| Momentum | 16 | 30 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 9,079 | 2,435 |
| Forks | 1,538 | 551 |
| Public repos | 44 | 61 |
| Active repos (90d) | 8 | 16 |
| External contributors | 22 | 0 |
| Avg polish | 42 | 55 |
| Avg AI-readiness | 15 | 23 |