Ever wanted to raise a pup and somehow navigate the mysteries of human dating at the same time? Meet the colourful cast of Rainbow Bay, date a few cuties, and teach a new dog new tricks - maybe even a flip. With the power of dogs and millennial woes on your side, this isn't a game to miss!
所有評論:
無使用者評論
發行日期:
2020 年 5 月 14 日
開發人員:
發行商:

登入以將此項目新增至您的願望清單、關注它,或標記為不感興趣

不支援繁體中文

本產品尚不支援您的目前所在地的語言。購買前請先確認語言支援清單。

此遊戲尚未在 Steam 上推出

預計發行日期: 2020 年 5 月

有興趣嗎?
將這款遊戲加入願望清單,推出時即可收到通知。
新增至您的願望清單
 

關於此遊戲

"Best Friend Forever is the millennial dream." - Forbes

"I did come away surprised, after spending some time with it at PAX West 2019, at how instantly charming the rest of Best Friend Forever is." - IGN

"The pet simulator system is just as enticing as the narrative, combining to make this a one-of-a-kind game full of warm fuzzies." - Nerdist



Step off the bus at Rainbow Bay and start a new life with your furever friend! Adopt a dog, find true love and experience all the wacky hijinks this colourful city has to offer.

Best Friend Forever is the world’s first simulation game to combine pet care and dating (just not necessarily at the same time). Train, pat and play with your very own dog to form a bond that will last the ages. With your four-legged companion by your side, meet, woo and cherish the many cuties of Rainbow Bay’s thriving singles scene.



  • Fall in love with a diverse cast of local singles.
  • Spend quality time with your dog to raise its stats and pass Paws Academy.
  • Go everywhere with your best friend — your dog interacts with you and the narrative as it happens.
  • Experience modern love at its finest! Be whoever you want, love whoever you want.
  • Unwind at the end of a long day by caring for your dog in an optional sandbox mode.

系統需求

    最低配備:
    • 作業系統: Windows 7 SP+1
    • 處理器: 2.2GHz
    • 記憶體: 2 GB 記憶體
    • 顯示卡: DX10 compatible
    • DirectX: 版本:10
    • 儲存空間: 4 GB 可用空間
    • 音效卡: Windows-based sound card
    建議配備:
    • DirectX: 版本:10
此產品無任何評論

您可以撰寫評論來與社群分享您對於本產品的看法。請使用本頁面中位於購買按鈕上方的區塊來進行評論的編寫。