AI inference at the edge
ggml vs Guild AI
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
ggml (AI inference at the edge) and Guild AI both appear on the Smoower Developer Ecosystem Index.
ggml (rank #103) holds a meaningful lead over Guild AI (rank #763) on the overall Smoower ecosystem score (55 vs 29). The gap of 26 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 Guild AI. On education (docs, guides and learning material for developers), ggml is ahead of Guild AI. On community (issue response, PR reviews and discussion health), ggml is clearly ahead of Guild AI. On reach (how visible the ecosystem is beyond its own repos), ggml is clearly ahead of Guild AI. On momentum (release cadence and how fast the ecosystem moves), ggml is clearly ahead of Guild AI.
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. Guild AI shows 1,003 stars across 29 public repos, 0 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 190.8x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
ggml is the stronger read for anyone weighting reach. Guild AI 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.
Side-by-side metrics
| Metric | ggml | Guild AI |
|---|---|---|
| Ranking | ||
| Overall rank | #103 | #763 |
| Pillars | ||
| Overall | 55 | 29 |
| Code | 47 | 34 |
| Education | 78 | 65 |
| Community | 80 | 31 |
| Reach | 90 | 9 |
| Momentum | 34 | 0 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 191,415 | 1,003 |
| Forks | 28,215 | 111 |
| Public repos | 22 | 29 |
| Active repos (90d) | 15 | 0 |
| External contributors | 308 | 1 |
| Avg polish | 50 | 39 |
| Avg AI-readiness | 32 | 15 |