ggml vs Johnson & Johnson

ggml (AI inference at the edge) and Johnson & Johnson both appear on the Smoower Developer Ecosystem Index.

ggml (rank #103) holds a meaningful lead over Johnson & Johnson (rank #602) on the overall Smoower ecosystem score (55 vs 34). The gap of 21 points reflects composite signals across code, docs, community and reach.

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

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. Johnson & Johnson shows 168 stars across 48 public repos, 8 active in the last 90 days and 1 external contributors. The star gap on its own does not decide the comparison, but ggml's footprint is roughly 1139.4x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

ggml is the stronger read for anyone weighting community. Johnson & Johnson looks better where code quality 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.