Catch AI trends before they break out

Indie Signals monitors Hugging Face, GitHub, Replicate, and Hacker News to surface fast-rising models, spaces, open-source projects, and discussions.

Workflow

How Indie Signals works

From raw data to actionable signals in four steps:

1

Collect signals

Ingest fresh data from Hugging Face, GitHub, Replicate, and Hacker News.

2

Normalize metrics

Standardize stars, likes, runs, and points into comparable growth signals.

3

Rank momentum

Score 24h/7d growth to surface breakouts before they are obvious.

4

Validate and act

Open source trends, compare Topic Hubs, and turn signals into ideas.

Why Indie Signals?

Cut through the noise and capture early momentum.

Cross-platform coverage

See models, spaces, repos, and stories together in one dashboard.

Momentum tracking

Monitor growth signals to validate real demand and adoption.

Topic discovery

Spot emerging categories with automated topic clustering.

24H Hot

24H Hot

Fastest movers across platforms in the last 24 hours.

Updated every 8 hours

Qwen/Qwen-Image-2.1

Hugging Face Model

Hugging Face Model
1.3Klikes
90824h

convaiinnovations/laya

Hugging Face Model

Hugging Face Model
1.6Klikes
84224h

gpt-image-2

Generate images from text prompts with strong instruction following and detailed editing.

Replicate
28.1Mruns
130K24h

jev-ultrafast

GitHub

GitHub
14.8Kstars
5K24h

ZCode

GitHub

GitHub
5.3Kstars
3.1K24h

laya-mlx

GitHub

GitHub
3.1Kstars
2.8K24h

observantdistressed/wan2-2-i2v-v3

Hugging Face Space

Hugging Face Space
289likes
8124h

Pepe104/MiniMax-H3-Turbo-Lora-UNCENSORED

Hugging Face Space

Hugging Face Space
564likes
6224h

z-image-turbo

Fast text-to-image model generates photorealistic images in seconds.

Replicate
55.2Mruns
128.2K24h

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What moved on GitHub, Hugging Face, Replicate, and Hacker News — plus the evidence and one build / watch / ignore call.

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Frequently Asked Questions

Quick answers on how signals are computed and how to read the trends.