ggml vs LlamaIndex

ggml (AI inference at the edge) and LlamaIndex both appear on the Smoower Developer Ecosystem Index.

LlamaIndex (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), LlamaIndex is ahead of ggml. On education (docs, guides and learning material for developers), ggml is ahead of LlamaIndex. On community (issue response, PR reviews and discussion health), ggml is clearly ahead of LlamaIndex. On reach (how visible the ecosystem is beyond its own repos), ggml is clearly ahead of LlamaIndex. On momentum (release cadence and how fast the ecosystem moves), LlamaIndex is clearly 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. LlamaIndex shows 99,809 stars across 135 public repos, 48 active in the last 90 days and 241 external contributors.

ggml is the stronger read for anyone weighting reach. LlamaIndex 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.