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sMiles: Bitcoin Rewards

sMiles: Bitcoin Rewards

Standapp inc.

Health & Fitness免费v12.6
App Store
评分

4.5

4,655 条评分

星级

★★★★★

最近更新

2026年5月7日

发布日期

2020年12月18日

更新内容

v12.6

- New: Tasks - New: Link Cash App - New stores with Bitcoin cashback - Custom referral codes - Other improvements If you enjoy sMiles, please leave a review on the App Store! We always appreciate your feedback. For any other questions, X / Telegram / FB / IG @smilesbitcoin

应用信息

开发者
Standapp inc.
分类
Health & Fitness
价格
免费
版本
12.6
App ID
1492458803

简介

Bitcoin rewards are for everyday! sMiles turns your everyday activity into real Bitcoin rewards. Walk, shop, play games, complete surveys, or shop your favorite brands. sMiles rewards the actions you already take with sats you can actually use. Powered by the Lightning Network, sMiles lets you stack Bitcoin and withdraw it to any Lightning wallet. No confusing points. No hidden value. Just real Bitcoin. More Steps Connect sMiles to HealthKit and automatically earn rewards for your daily steps. Track your progress directly on Apple Watch and see your activity at a glance. Shop and Earn Buy from your favorite stores and earn Bitcoin cashback. Premium subscribers unlock higher reward rates. Play and Learn Play Bitcoin games, complete chess puzzles, and explore interactive lessons about innovative companies. Have fun and earn rewards! Explore Tasks Discover local tasks, locations, and special reward opportunities around you. Unlock new ways to earn as you explore. Withdraw Anytime Stack sats and send them to any Lightning wallet. sMiles Premium Upgrade to Premium to unlock: • Up to 5X more Bitcoin rewards • Up to 2 free monthly tasks that other users can complete • Early access to new features • Leaderboard visibility • Custom app icons • Verified badge • And more Start stacking sats today. Follow us: @smilesbitcoin Terms and Conditions: https://www.smilesbitcoin.com/terms-conditions

下载量预测

专业 · 预览

预估总下载量

423K310K665K
保守估计乐观估计

5K

低 / 月

6K

预估 / 月

10K

高 / 月

基于4,655 条评分
假设评分率1.1%
应用年龄66 个月

基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。