ggml vs Mage

ggml (AI inference at the edge) and Mage (Magical tools for data.) both appear on the Smoower Developer Ecosystem Index.

ggml (rank #103) holds a modest lead over Mage (rank #485) on the overall Smoower ecosystem score (55 vs 38). The gap of 17 points reflects composite signals across code, docs, community and reach.

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

ggml carries 191,415 GitHub stars across 22 public repos, with 15 repositories active in the last 90 days and 308 external contributors on record. Mage shows 9,079 stars across 44 public repos, 8 active in the last 90 days and 22 external contributors. The star gap on its own does not decide the comparison, but ggml's footprint is roughly 21.1x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

ggml is the stronger read for anyone weighting reach. Mage 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.