browserbase vs ggml
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
browserbase and ggml (AI inference at the edge) both appear on the Smoower Developer Ecosystem Index.
ggml (rank #103) holds a narrow lead over browserbase (rank #152) on the overall Smoower ecosystem score (55 vs 52). The gap of 3 points reflects composite signals across code, docs, community and reach.
On education (docs, guides and learning material for developers), browserbase is slightly ahead of ggml. On community (issue response, PR reviews and discussion health), ggml is clearly ahead of browserbase. On reach (how visible the ecosystem is beyond its own repos), ggml is clearly ahead of browserbase. On momentum (release cadence and how fast the ecosystem moves), browserbase is slightly ahead of ggml.
browserbase carries 34,643 GitHub stars across 65 public repos, with 27 repositories active in the last 90 days and 69 external contributors on record. ggml shows 191,415 stars across 22 public repos, 15 active in the last 90 days and 308 external contributors. The star gap on its own does not decide the comparison, but ggml's footprint is roughly 5.5x larger, which usually shows up in downstream signals like inbound issues and third party integrations.
browserbase is the stronger read for anyone weighting education. ggml looks better where reach 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 | browserbase | ggml |
|---|---|---|
| Ranking | ||
| Overall rank | #152 | #103 |
| Pillars | ||
| Overall | 52 | 55 |
| Code | 47 | 47 |
| Education | 83 | 78 |
| Community | 53 | 80 |
| Reach | 45 | 90 |
| Momentum | 38 | 34 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 34,643 | 191,415 |
| Forks | 3,000 | 28,215 |
| Public repos | 65 | 22 |
| Active repos (90d) | 27 | 15 |
| External contributors | 69 | 308 |
| Avg polish | 46 | 50 |
| Avg AI-readiness | 41 | 32 |