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Nomad eSIM: Prepaid Data Plan

Nomad eSIM: Prepaid Data Plan

LotusFlare

Travel免费v10.13.0
App Store
评分

4.8

14,408 条评分

星级

★★★★★

最近更新

2026年5月15日

发布日期

2020年12月15日

更新内容

v10.13.0

- Introducing Nomad Pass: “Always-On” Data Subscription for Europe Regional eSIM

应用信息

开发者
LotusFlare
分类
Travel
价格
免费
版本
10.13.0
App ID
1521602300

简介

Stay connected wherever you go with Nomad eSIM! Your Best Travel Companion | Affordable | Convenience | Choice Enjoy fast, flexible eSIM data without contracts. Forget about traditional SIM cards – connect in just 5 minutes with our easy-to-use eSIM! Nomad offers eSIM services in over 200+ destinations and 10 regions. Access affordable international data plans at near-local rates in Europe, North America, Asia, Africa, and more. Choose from regional and country-specific eSIM plans designed for every traveler. Exclusive for New Users. Try Nomad for free! Redeem a FREE eSIM and stay connected in 48 destinations before you even take off. If you're new to Nomad or unsure about eSIM, try us out and rid your worries! Every new user gets 1 free trial eSIM! Why Choose Nomad eSIM? - No Contracts: No hidden fees or surprise data roaming charges. - Fast Connection: Activate your eSIM in just 5 minutes – no more waiting at airport SIM counters. - Max Convenience: Keep your main SIM for calls and texts. Travel light, stay connected. Key Features of Nomad eSIM: - Seamless installation via QR code or one-click activation. - Choose from a variety of eSIM plans – from 1 GB to Unlimited Plans. - eSIM data packs for 200+ destinations - Multi-currency payments - Support for 13 languages - Data usage tracking Bring a friend, get USD 5 off! Share your Nomad eSIM referral code: earn a $5 discount with each successful referral. Friends also enjoy $5 off on their first eSIM purchase. For more information, visit: https://www.getnomad.app For queries, visit: https://www.getnomad.app/help-center

下载量预测

专业 · 预览

预估总下载量

1.1M720K2.1M
保守估计乐观估计

11K

低 / 月

16K

预估 / 月

31K

高 / 月

基于14,408 条评分
假设评分率1.4%
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。