Apps Like 贴贴-期待每一次相遇 for iPhone and iPad
贴贴-期待每一次相遇 screenshots
Ranked alternatives
Showing 1–20 of 519 ranked alternatives.









豆瓣
Beijing Douwang Technology Company Limited
Share content, join groups, explore interests
Share reviews and ratings for books, movies, and music. Explore curated lists and discover new content based on preferences. Join interest-based groups to connect with like-minded users.


Nico-多元人格与深度交友
Wuhan Rare Technology Co., Ltd.
Meet new people with personality matches
Facilitates social connections through personality-based matching, allowing users to view detailed personality profiles and compatibility scores. Features location-based matching, voice chat groups, and a community platform for sharing content.


百度贴吧-聊兴趣,上贴吧
Beijing Baidu Netcom Science & Technology Co.,Ltd
Join interest groups and discuss topics
Connect with others through interest-based communities. Join sports forums for match discussions and news, access game guides for strategy and tips, and participate in humor and meme discussions.


时光网-超级IP娱乐空间
Beijing Mtime Network Technology Co., Ltd
Discover IP, Stars, and More
The app offers content discovery and consumption around celebrity IP, film and television, and trendy merchandise. Users can browse celebrity and IP content, explore official recommendations, and access movie news and event updates.

百变大侦探-剧本杀,我是推理谜案王
Beijing JiuYaoYao Tech CO.,LTD
Chat with friends and play roles together
Roleplay and deduction game allows users to join voice chat rooms for script-based gameplay. Access a variety of original and high-quality offline scripts. Explore detailed maps with scene-based clues and private messaging.

MOMO陌陌-视频交友与语音聊天平台
Beijing Momo Technology Group Co., Ltd.
Meet new people and chat anonymously
Browse nearby profiles and dynamic updates to meet local users. Watch live streams with interactive chat and virtual gifts. Send anonymous messages in private circles. Chat anonymously with random matches using text or voice.
How we rank alternatives
Apps are ranked by functional similarity, category fit, rating confidence, and popularity.