Top 100 Countries by Price of 1GB Mobile Data (USD), 2025

Goal: convert a globally comparable ICT price basket into a simple, usable figure — the standardized price of 1GB of mobile data in USD — and rank the Top 100 cheapest economies.

1) Primary data source

The baseline price inputs come from the ITU ICT price baskets (2025), specifically the data-only mobile-broadband basket (5GB). This basket is designed to make retail mobile data prices comparable across economies by applying consistent rules for plan selection and reporting.

2) What the ITU mobile-broadband basket represents

The data-only mobile-broadband basket is built from the cheapest plan that meets a minimum data allowance threshold, typically sourced from the largest operator, using 3G or more advanced technologies. The 2025 framework uses a basket at at least 5GB monthly data allowance for mobile-broadband price statistics.

3) Standardizing to “USD per 1GB”

The ITU basket price is reported as a monthly price in USD for the qualifying plan. To translate the basket into an intuitive “per-GB” number while keeping the definition consistent, StatRanker uses a strict standardization:

4) Affordability measure (income-adjusted burden)

ITU also reports the same basket as a share of GNI per capita (affordability). StatRanker converts that to a standardized per-GB affordability proxy using the same approach:

5) Ranking rules and scope

• Ranking direction: ascending (cheapest first). The page shows the Top 100 cheapest economies in 2025.
• Coverage: economies with non-missing ITU basket prices and affordability values in the 2025 release.
• Columns: limited to 4 (Rank, Country, USD per 1GB, Affordability) to keep layout clean and mobile-friendly.

6) Taxes, plan details, and technology

ITU basket files include contextual fields such as tax rate, technology, and (in some baskets) allowance and notes. These fields are displayed as context under the country name. The ranking itself is based on the standardized USD figure derived from the basket price as reported by ITU (which may already include taxes depending on the reported methodology).

7) Limitations (what this ranking does and does not claim)

• Not a retail deal finder: it benchmarks basket-consistent entry pricing, not promotional offers or short-term discounts.
• Not a speed/quality score: low cost does not guarantee strong coverage, low latency, or consistent throughput.
• Plan structures differ: unlimited plans, bundles, and multi-SIM offers can’t be perfectly normalized beyond the basket definition.
• Local taxes and fees: may be applied differently across countries; the reported tax rate is shown for transparency.

8) Why not rely only on crowdsourced “1GB price” indexes?

Crowdsourced indexes can be useful, especially for market snapshots, but their plan sampling rules vary (mean vs median, plan inclusion rules, prepaid vs postpaid, promotional prices, etc.). Here, crowdsourced sources can be used as a cross-check, while the primary benchmark remains the ITU basket for methodological consistency.

The spread between the cheapest and most expensive economies is not a mystery of “rich vs poor.” It is usually the result of a few structural forces stacking together. Understanding those forces helps readers interpret the ranking and avoid naïve conclusions like “cheap means good” or “expensive means exploitation.”

1) Market structure and competitive intensity

Countries with multiple operators competing aggressively on prepaid data often compress retail prices. Price wars are especially common where mobile networks are the primary internet channel for households and small businesses. Conversely, markets with limited competition (or small customer bases) can have higher prices because fixed costs are spread across fewer users.

2) Geography, backhaul, and scale

Small islands and remote territories frequently show up in the expensive tail. The reason is not just “high incomes,” but infrastructure constraints: international bandwidth (subsea cables or satellite), redundancy needs, and logistics for equipment and maintenance. Where scale is small, per-user network costs rise.

3) Regulation, taxes, and spectrum costs

Retail prices can embed taxes and regulatory fees directly or indirectly. Spectrum licensing costs, universal service obligations, and sector-specific levies can all influence pricing. That is why tax context is displayed and why affordability can diverge from USD prices.

4) Device and plan bundling norms

Some high-income economies sell data as part of postpaid bundles (often with handset financing, add-ons, and “unlimited” tiers). The basket aims for the cheapest qualifying plan, but consumer behavior may gravitate to bundles that look more expensive in a simple per-GB breakdown. In those markets, the basket is best read as “minimum entry cost,” not “typical bill.”

5) The affordability trap

The most important insight for readers is that affordability and USD price are different concepts. A country can be extremely cheap in USD and still impose a meaningful burden on residents if incomes are low. Conversely, a high USD price can be almost irrelevant for a high-income household. If you are comparing digital inclusion, the affordability column should be your primary lens.

If you are a traveler or remote worker

Use the USD ranking to anticipate whether you can comfortably rely on prepaid data for daily work — but don’t stop there. Combine this table with mobile download speed and 5G coverage. A place can be cheap and still have weak coverage outside major cities, or congested networks at peak hours.

If you are comparing “digital affordability” across countries

Prioritize the affordability column. A policy goal like “1GB should cost less than X% of monthly income” is closer to the reality of digital access than a pure USD threshold. Also remember that households buy more than 1GB — the ranking standardizes a unit for comparability, not to claim that 1GB is sufficient.

If you are doing market research

Prices reflect both demand (how essential mobile data is) and supply constraints (spectrum, infrastructure, scale). Cheap data can coexist with high usage and intense competition; expensive data can signal small market size, infrastructure bottlenecks, or limited competition. Pair this ranking with broadband price baskets and fixed broadband speeds to see whether mobile is substituting for fixed connectivity.

Related StatRanker pages (internal)

1) Is this the exact price you will pay as a tourist?

Not necessarily. The table is a standardized benchmark based on the ITU basket methodology. Tourist SIM options, promotions, and roaming packages can differ. Use it as a reliable baseline comparison, then check local offers for your specific usage.

2) Why do some high-income countries appear expensive?

In some markets, the cheapest qualifying plan may still be priced high due to bundling norms, limited competition, or higher underlying cost structures. The basket is best understood as “minimum entry cost,” not the “typical bundle consumers choose.”

3) Why include affordability if the ranking is in USD?

Because USD prices alone do not capture resident burden. Affordability shows the cost relative to national income. For digital inclusion questions, that is often the more meaningful metric.

4) Does cheaper data mean faster internet?

No. Price and speed are related but not equivalent. Congestion, coverage, spectrum, and backhaul shape performance. Use the related speed and 5G coverage pages to validate quality.

5) Is the “per 1GB” number a true marginal cost of one extra gigabyte?

No. It is a standardized unit derived from a basket price (5GB) to enable comparisons. Real-world marginal pricing depends on plan tiers, caps, “unlimited” rules, and fair-use policies.

6) Why are some islands and small territories so expensive?

Infrastructure scale is limited, international connectivity is costly, and redundancy is harder to build. Those structural factors often dominate over demand-side drivers.

7) How often should this ranking be updated?

Annually is a sensible cadence because ITU releases updated basket statistics and because telecom pricing evolves with competition, taxation, and technology rollouts.

8) Can I reuse this table in reports?

Yes, with proper attribution to the underlying sources. If you cite figures, cite the ITU ICT prices dataset and methodology, and note the standardization step used for “USD per 1GB.”

Official and methodology sources used to construct and interpret the ranking.

• ITU — ICT prices (2025 basket statistics and downloads): ITU ICT prices page
• ITU — ICT Price Basket Statistics Manual (methodology): ITU IPB Manual (2025)
• ITU — Affordability context (interpretation/reporting note): Affordability of ICT services (ITU)
• World Bank — GNI per capita indicator (metadata and series): GNI per capita, Atlas method (current US$)
• Cable.co.uk (crowdsourced cross-check) — methodology document: Worldwide mobile data pricing methodology (PDF)

Note: StatRanker’s ranking uses the ITU basket as the primary benchmark and documents the per-GB standardization explicitly for transparency.