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First read
gradio-app/gradio looks visible enough to matter, active enough to trust for a next pass, and adopted enough to merit checking maintainers, releases, and real integration cost in the source repository.
43.5K public stars in the current GitStar snapshot.
Recognizable in the ecosystem
Last commit Sep 12, 2026.
Fresh activity
pypi gives the strongest production-style signal.
16.5M/week
One or more key signals are partial, so GitStar keeps the interpretation conservative.
Partial snapshot
Snapshot facts
Compare lens
scikit-learn/scikit-learn and keras-team/keras are the closest comparison targets GitStar found. A side-by-side comparison usually tells you more than a single raw rank.
Signal trail
Read the recent motion first. This block is for deciding whether the repository still looks alive, compounding, or flattening before you trust stars alone.
Package reality
GitStar found pypi:gradio. Package traffic can help separate visible repositories from dependencies that are quietly used in real workflows.
Validation note
GitStar can summarize public signals for gradio-app/gradio, but the GitHub repository is still the primary place to confirm release cadence, issue activity, and maintainer intent.
GitStar uses the strongest linked package signal below when it reads Hype vs Reality for this repository.
GitStar surfaces public popularity and package signals. These rankings are not endorsements, security reviews, or investment advice.
Why this rank
This repository stands out because it combines package adoption and fresh update.
Reconstructed from current stars and cached daily/weekly/monthly deltas.
Recent attention and package usage are moving in the same direction.
This usually means the project has both mindshare and a measurable production footprint, which makes it a stronger validation candidate.
Shares the learning category footprint with gradio-app/gradio, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the learning category footprint with gradio-app/gradio, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the learning category footprint with gradio-app/gradio, so the comparison is closer to a same-problem decision than a same-language coincidence.
Shares the learning category footprint with gradio-app/gradio, so the comparison is closer to a same-problem decision than a same-language coincidence.
GitStar picked scikit-learn + keras as the closest next comparison from the related repository set.
[](https://gitstar.space/repo/gradio-app/gradio)<a href="https://gitstar.space/repo/gradio-app/gradio"><img src="https://gitstar.space/api/badge/gradio-app/gradio" alt="GitStar"></a>scikit-learn: machine learning in Python
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This page provides a quick overview of gradio-app/gradio based on GitStar's cached data. The signal chart reconstructs approximate checkpoints from current stars plus cached daily, weekly, and monthly star deltas, so it is best read as directional context rather than as a precise historical audit log.
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