ggml vs Runway

ggml (AI inference at the edge) and Runway (Building AI to Simulate the World) both appear on the Smoower Developer Ecosystem Index.

ggml (rank #103) holds a modest lead over Runway (rank #317) on the overall Smoower ecosystem score (55 vs 44). The gap of 11 points reflects composite signals across code, docs, community and reach.

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

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. 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 ggml's footprint is roughly 78.6x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

ggml is the stronger read for anyone weighting community. Runway 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.