Chonkist

Chonkist

Trust your neighbors.

1 ratings
Free

Rating summary
1
0
0
0
0

Details

  • Released
  • Updated
  • January 16, 2026
  • February 3, 2026

Features

Chonkist screenshot #1 for iPhone
Chonkist screenshot #2 for iPhone
Chonkist screenshot #3 for iPhone
iphone
ipad
🖼️Get Icon
Icons↘︎

About

Discover hyper-local dining recommendations in specific neighborhoods. Connect with locals who have similar tastes to get insider tips for the best dining experiences.

✓Hyper-local dining reviews
✓Neighborhood-specific recommendations
✓Match with locals
✓Connect with reviewers
✓Get insider tips
Show original description

What's New in Chonkist

1.0.65

February 3, 2026

News articles in news feed. Google Auth fix.

FAQ

What neighborhoods does Chonkist cover?

Chonkist focuses exclusively on hyper-local dining reviews for Williamsburg and Greenpoint. This allows for highly specific and relevant recommendations within these areas.

How does Chonkist help me find good restaurants?

Chonkist connects you with locals who share your taste, enabling you to talk to real reviewers. This provides insider tips and recommendations that can help you get seated at popular spots.

Is Chonkist free to use?

Yes, Chonkist is available for free. There are no costs associated with downloading or using the app's core features.

What devices can I use Chonkist on?

Chonkist is supported on iPhone, iPad, and iPod devices. It is designed for Apple's mobile operating system.

How often is Chonkist updated?

The latest version of Chonkist is 1.0.65, and it was last updated on February 3, 2026. This indicates a recent update and ongoing development.

What is the age rating for Chonkist?

Chonkist has an age rating of 12+. This suggests that the content is generally suitable for users aged 12 and above.

Does Chonkist have ads?

No, Chonkist does not contain advertisements. Users can enjoy a completely ad-free experience while discovering local dining options.

What makes Chonkist different from other review apps?

Chonkist differentiates itself by focusing on hyper-local areas and matching users with neighbors who have similar tastes. This aims to provide more personalized and trustworthy recommendations than broader platforms.