| --- |
| license: cc-by-4.0 |
| pretty_name: Mobile Data Usage Estimates |
| size_categories: |
| - n<1K |
| task_categories: |
| - other |
| tags: |
| - mobile-data |
| - esim |
| - travel |
| - usage |
| - estimates |
| - trip-planning |
| configs: |
| - config_name: activities |
| data_files: activity_mb_per_hour.csv |
| - config_name: presets |
| data_files: daily_presets.csv |
| --- |
| |
| # Mobile Data Usage Estimates |
|
|
| The activity-level MB/hour assumptions and daily presets used by the open-source [trip-data-budget](https://nxtlsim.github.io/trip-data-budget/) and [team-data-planner](https://nxtlsim.github.io/team-data-planner/) tools — published so other apps and agents can reuse the same transparent numbers. |
|
|
| **Every figure is an estimate, not a measurement.** |
|
|
| ## Tables |
|
|
| ### `activities` (8 rows) |
|
|
| | activity_id | activity | MB / hour | |
| | --- | --- | ---: | |
| | maps | Maps & navigation | 8 | |
| | msg | Messaging & email | 10 | |
| | web | Web browsing | 60 | |
| | music | Music streaming | 70 | |
| | social | Social media (with video) | 150 | |
| | call | Video calls | 500 | |
| | video | Video streaming (SD) | 700 | |
| | hot | Laptop via hotspot | 300 | |
| |
| ### `presets` (4 rows) |
| |
| Hours/day mixes that the tools ship with, plus the daily total after a **1.1×** buffer for background updates and sync: |
| |
| | preset | est. MB / day (with buffer) | |
| | --- | ---: | |
| | light | 59.4 | |
| | normal | 349.8 | |
| | heavy | 1718.2 | |
| | remote | 2219.8 | |
| |
| Streaming assumes **standard-definition** video; HD can use several times more. Real use varies with app settings and network conditions. |
| |
| ## Example uses |
| |
| - **In-app data budget calculator:** reuse the same MB/hour table so your UX matches the public tool. |
| - **AI agent:** when a user says "I'll navigate all day and do two hours of calls", multiply the rows instead of inventing rates. |
| - **Education / blog:** cite a small, versioned table rather than hand-waving "about a gig a day". |
| |
| ### Quick load |
| |
| ```python |
| from datasets import load_dataset |
| acts = load_dataset("nxtl-esim/mobile-data-usage-estimates", "activities", split="train") |
| presets = load_dataset("nxtl-esim/mobile-data-usage-estimates", "presets", split="train") |
| print({r["activity_id"]: r["mb_per_hour"] for r in acts}) |
| ``` |
| |
| ```python |
| import pandas as pd |
| acts = pd.read_csv("activity_mb_per_hour.csv").set_index("activity_id")["mb_per_hour"] |
| hours = {"maps": 1, "msg": 3, "web": 1, "music": 1, "social": 1} # "normal" mix |
| mb = sum(acts[k] * h for k, h in hours.items()) * 1.1 |
| print(round(mb, 1), "MB/day estimate") |
| ``` |
| |
| ## Methodology |
| |
| Copied from the constants embedded in `trip-data-budget` (`ACTS`, `PRE`, 10% buffer). No separate lab measurement was performed for this release. Where a figure is used in product copy it is labelled as an estimate. |
| |
| ## Limitations |
| |
| - Not a substitute for measuring your own apps on your own network. |
| - No per-app breakdown (Instagram vs TikTok, Zoom vs Meet, etc.). |
| - Video is SD-only in the table; there is no HD/4K row. |
| - Presets are starting points, not personas backed by survey data. |
| |
| ## Licence and credit |
| |
| **CC BY 4.0.** Attribute "NXTL mobile data usage estimates". |
| |
| Live tool: [trip-data-budget](https://nxtlsim.github.io/trip-data-budget/) · sibling planner: [team-data-planner](https://nxtlsim.github.io/team-data-planner/) · published by [NXTL eSIM](https://nxtlsim.com/) |
| |
| ## Citation |
| |
| ``` |
| @misc{nxtl_mobile_data_usage_estimates_2026, |
| title = {Mobile Data Usage Estimates}, |
| author = {NXTL}, |
| year = {2026}, |
| howpublished = {Hugging Face dataset}, |
| note = {Assumptions from trip-data-budget / team-data-planner} |
| } |
| ``` |
| |
