Pipecat leads on stars, LiveKit Agents on forks — and Bolna is forked far above its weight
Asked:
“can you compare the amount of stars and fork”
GitHub stars and forks for the eight core voice-AI orchestrators, measured from the GitHub API on 2 September 2026. Stars indicate attention; forks more directly indicate code reuse or experimentation — neither proves production quality.
Stars vs forks per platform
Ordered by stars · exact GitHub API counts, 2026-09-02 · fork bars share the same scale, so their values are labeled
Stars (attention)Forks (reuse / experimentation)
Fork intensity — forks per 100 stars
How heavily each project is forked relative to its visibility
A higher ratio can suggest stronger implementation and self-hosting interest relative to visibility, but it can also reflect deployment workflows (forking as a deploy step) or contributor habits. It is a signal of engagement mix, not a quality score.
Findings
Pipecat has the most stars at 14,952, yet its 2,582 forks trail LiveKit Agents — attention and reuse rank the field differently.
github.comLiveKit Agents leads all eight on forks with 3,646, at 26.9 forks per 100 stars — the highest intensity among the large projects.
github.comBolna is the outlier: 46.8 forks per 100 stars, nearly double the next project, on a small base of 746 stars.
github.comTEN Framework and Patter are the least-forked relative to visibility, at 12.2 and 11.4 forks per 100 stars.
github.com
All eight platforms
| Platform | Repository | Stars | Forks | Forks / 100 stars |
|---|
Data: GitHub API counts for the eight core voice-AI orchestrators from the earlier progress report, 8 rows, measured 2026-09-02. Stars count users who bookmarked a repository; forks count copies made into other accounts. Forks per 100 stars is precomputed in the source data. Adjacent projects outside the core set were deliberately excluded.