AI inference at the edge
ggml vs NVIDIA Corporation
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
ggml (AI inference at the edge) and NVIDIA Corporation both appear on the Smoower Developer Ecosystem Index.
ggml (rank #103) holds a narrow lead over NVIDIA Corporation (rank #189) on the overall Smoower ecosystem score (55 vs 50). The gap of 5 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), NVIDIA Corporation is ahead of ggml. On education (docs, guides and learning material for developers), NVIDIA Corporation is slightly ahead of ggml. On community (issue response, PR reviews and discussion health), ggml is clearly ahead of NVIDIA Corporation. On reach (how visible the ecosystem is beyond its own repos), ggml is clearly ahead of NVIDIA Corporation. On momentum (release cadence and how fast the ecosystem moves), NVIDIA Corporation is ahead of ggml.
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. NVIDIA Corporation shows 314,588 stars across 762 public repos, 84 active in the last 90 days and 342 external contributors.
ggml is the stronger read for anyone weighting reach. NVIDIA Corporation 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 | ggml | NVIDIA Corporation |
|---|---|---|
| Ranking | ||
| Overall rank | #103 | #189 |
| Pillars | ||
| Overall | 55 | 50 |
| Code | 47 | 60 |
| Education | 78 | 79 |
| Community | 80 | 55 |
| Reach | 90 | 38 |
| Momentum | 34 | 54 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 191,415 | 314,588 |
| Forks | 28,215 | 49,823 |
| Public repos | 22 | 762 |
| Active repos (90d) | 15 | 84 |
| External contributors | 308 | 342 |
| Avg polish | 50 | 67 |
| Avg AI-readiness | 32 | 43 |