# Lo查查 vs 花衣手帖

The clearest difference is device support: Lo查查 at 3 against 花衣手帖's 1. Lo查查 also leads on iOS requirement (15.1 vs 17.0). On price, ads and in-app purchases there is nothing between them.

Both are free to download. Neither carries in-app purchases, so what you see is what you pay.

## The numbers

| Metric | Lo查查 | 花衣手帖 |
| --- | --- | --- |
| Price | Free | Free |
| Rating | **[5.0 (2 ratings)](https://appshunter.io/ios/app/lo/id6768183370/reviews)** | — |
| Number of ratings | **2** | — |
| Positive reviews | 36.8% of reviews | — |
| In-app purchases | No | No |
| Ads | No | No |
| Update frequency | Fortnightly | — |
| Monetization | Free | — |
| Size | 88 MB | 74 MB |
| Requires iOS | **15.1** | 17.0 |
| Devices | **iPhone, iPad, iPod** | iPhone |
| Age rating | 4+ | 4+ |
| Developer | [凯 邵](https://appshunter.io/developer/1896537477) | [Shanghai Wenbenyue Technology Co., Ltd](https://appshunter.io/developer/1896554798) |

## What reviewers say

### Lo查查

[App page](https://appshunter.io/ios/app/lo/id6768183370)

This app helps Lolita fashion enthusiasts find and track dress styles, brands, and prices. It allows users to manage their virtual wardrobe, view market trends, and identify potential transaction risks. The tool aims to simplify the process of discovering and collecting Lolita fashion items.

**Highlights:** Style, brand, and series lookup, Price trend and market reference, Personal wardrobe management, Transaction risk identification, Favorite style collection

**Features:** macOS Compatibility, Apple Wallet, Vision Pro support

**In-app purchases:** none


### 花衣手帖

[App page](https://appshunter.io/ios/app/id6796517775)

**Features:** macOS Compatibility, Vision Pro support

**In-app purchases:** none


## Frequently asked questions

### Is Lo查查 free?

Lo查查 is free to download, with no in-app purchases.

### Is 花衣手帖 free?

花衣手帖 is free to download, with no in-app purchases.

### Do Lo查查 or 花衣手帖 have ads?

Neither Lo查查 nor 花衣手帖 shows ads.

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*Compared by [AppsHunter](https://appshunter.io/) from daily US App Store data. Review summaries are generated from verbatim App Store reviews.*