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Community Analytics

Real-time model popularity data from HuggingFace and community activity

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// READOUT

This page tracks what the local-AI community actually runs — live download and like counts from HuggingFace, refreshed hourly. Use it to spot momentum, but remember popularity isn't fit: read how to read these numbers before you pick.

01 Model Popularity Dashboard

Top 10 Most Downloaded Models (Last 30 Days)
via HuggingFace Hub API · sorted by download count
Top 10 Most Liked Models
via HuggingFace Hub API · sorted by community likes

02 How to Read These Numbers

These charts pull live numbers from the HuggingFace Hub — but raw popularity needs a little interpretation before you act on it.

Downloads

Last-30-day pulls — a strong usage signal, but inflatable. CI pipelines, mirrors, and automated runs all count, so a spike isn't always human adoption.

Likes

Cumulative manual endorsements — a slower, more deliberate signal of approval than downloads. Harder to game, but it lags new releases.

Recency

Fresh releases spike then settle; long-stable models show steady numbers. A model at the top of “trending” hasn't necessarily proven itself yet.

Blind spots

Gated, private, and renamed repos undercount. And popularity ≠ quality or fit — the most-downloaded model may not run on your VRAM or suit your task.

Popularity is a starting point, not a verdict. To turn it into a pick that fits your hardware, run the Model Targeting System or the Stack Builder.

03 Data Sources & Methodology

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Model Downloads & Likes

Fetched in real-time from the HuggingFace Hub API. These numbers represent actual downloads in the last 30 days and cumulative community likes. Data refreshes every hour when you visit this page.

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Hardware Stack Builder

Our Hardware Stack Builder lets you select your GPU or Apple Silicon, see which models fit in your VRAM, estimate inference speeds, and save configurations locally in your browser — never sent to any server.