mlc-ai vs TopK

mlc-ai and TopK (Pushing state of the art, one flamegraph at a time.) both appear on the Smoower Developer Ecosystem Index.

mlc-ai (rank #209) holds a modest lead over TopK (rank #536) on the overall Smoower ecosystem score (49 vs 36). The gap of 13 points reflects composite signals across code, docs, community and reach.

On code quality (the state of repositories, tests, releases and polish), mlc-ai is slightly ahead of TopK. On education (docs, guides and learning material for developers), mlc-ai is ahead of TopK. On community (issue response, PR reviews and discussion health), mlc-ai is clearly ahead of TopK. On reach (how visible the ecosystem is beyond its own repos), TopK is ahead of mlc-ai. On momentum (release cadence and how fast the ecosystem moves), TopK is slightly ahead of mlc-ai.

mlc-ai carries 51,532 GitHub stars across 38 public repos, with 15 repositories active in the last 90 days and 45 external contributors on record. TopK shows 87 stars across 12 public repos, 8 active in the last 90 days and 6 external contributors. The star gap on its own does not decide the comparison, but mlc-ai's footprint is roughly 592.3x larger, which usually shows up in downstream signals like inbound issues and third party integrations.

mlc-ai is the stronger read for anyone weighting community. TopK 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.