AI inference at the edge
ggml vs LiveKit
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
ggml (AI inference at the edge) and LiveKit (Open source WebRTC and realtime AI infrastructure) both appear on the Smoower Developer Ecosystem Index.
LiveKit (rank #63) holds a narrow lead over ggml (rank #103) on the overall Smoower ecosystem score (59 vs 55). The gap of 4 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), LiveKit is ahead of ggml. On education (docs, guides and learning material for developers), LiveKit is slightly ahead of ggml. On community (issue response, PR reviews and discussion health), ggml is clearly ahead of LiveKit. On reach (how visible the ecosystem is beyond its own repos), ggml is clearly ahead of LiveKit. On momentum (release cadence and how fast the ecosystem moves), LiveKit 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. LiveKit shows 39,530 stars across 108 public repos, 59 active in the last 90 days and 247 external contributors. The star gap on its own does not decide the comparison, but ggml's footprint is roughly 4.8x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
ggml is the stronger read for anyone weighting reach. LiveKit 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.
Side-by-side metrics
| Metric | ggml | LiveKit |
|---|---|---|
| Ranking | ||
| Overall rank | #103 | #63 |
| Pillars | ||
| Overall | 55 | 59 |
| Code | 47 | 62 |
| Education | 78 | 85 |
| Community | 80 | 46 |
| Reach | 90 | 48 |
| Momentum | 34 | 49 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 191,415 | 39,530 |
| Forks | 28,215 | 9,312 |
| Public repos | 22 | 108 |
| Active repos (90d) | 15 | 59 |
| External contributors | 308 | 247 |
| Avg polish | 50 | 62 |
| Avg AI-readiness | 32 | 60 |