Token Index
APRIL 20, 2026
The AI Token IndexAPRIL 20, 2026 REVIEWED
A sourced editorial view of coding-assistant inference spend

Where one month of an AI coding assistant looks cheapest in this model.

We hold one standard month of coding-assistant inference constant, then estimate what that month of inference model spend looks like in different countries. Business electricity is one of the clearest visible reasons the estimate moves.

Scope note: major API list prices are usually global. The country gap shown here is the estimated monthly model spend for the same coding-assistant inference workflow, not a claim that vendors publish different local token prices or retail seat prices for tools like Cursor, ChatGPT, or Claude plans.

Standard Inference Month

For this story, one month means 22 workdays × 10 coding sessions/day × ~45K total tokens/session.

Scenario1 month of a coding-assistant inference workflow
Under the hood9.9M total tokens, modeled as 70% input / 30% output
What changesPower and local price levels
What it is notA local seat-price sheet
Lowest Monthly Estimate
Singapore
$28.42 for one inference month
Highest Monthly Estimate
Germany
$49.43 for one inference month
Estimated Spread
1.7x
from lowest to highest estimate
Main Modeled Lever
Power
electricity is a major modeled cost input
What This Story Tracks

One fixed month of coding help. Different countries. Different cost.

This page asks one simpler question: where does 1 month of a coding-assistant inference workflow land lowest in this estimate? We keep that month fixed at 22 workdays × 10 coding sessions/day × ~45K total tokens/session, compare the same inference workflow across countries, then add a PPP-adjusted second view.

Read It Like This

Start with the country cost, use power to understand why the number moves, then add the PPP view before moving into the economic consequence.

Lens
The Month

22 workdays × 10 coding sessions/day × ~45K total tokens/session. 9.9M total tokens, modeled as 70% input / 30% output.

Lens
Power

One of the clearest country-level reasons the monthly inference estimate changes.

Lens
Affordability

A second view: how that same inference workflow looks after local price-level adjustment.

The Cost Gap

In this model, one coding-assistant inference month lands at different costs by country.

Each country is scored against the same month: 1 month of a coding-assistant inference workflow. Under the hood that means 22 workdays × 10 coding sessions/day × ~45K total tokens/session. What changes is the estimated model spend once business electricity and local price levels are fed into the formula.

Cheap
Expensive
Lowest estimated costSingapore · Saudi Arabia · Egypt
Highest estimated costGermany · Spain · Australia
Figure 1Estimated monthly coding-assistant inference cost
Loading the global cost map…
Cheapest cluster

Lower business-electricity benchmarks tend to pull the monthly coding-assistant inference estimate down.

Middle band

Large developed markets stay competitive, but many do not land at the bottom once power is added.

Most expensive

Higher business-electricity benchmarks and higher price levels push some countries toward the top.

Country Ranking

Cost of the same coding-assistant inference month

This table compares the same coding-assistant inference month across countries. Sort by monthly cost to see where it lands lowest in the estimate, by business electricity to compare a main input, or by PPP-adjusted cost to add the second lens.

Reference tableSame inference month, different country
#CountryRegion
01SingaporeAsia-Pacific$28.42$0.055$17.10
02Saudi ArabiaMEA$29.68$0.074$14.60
03EgyptMEA$29.92$0.097$4.13
04TürkiyeEurope$30.37$0.089$10.70
05NigeriaAfrica$32.01$0.119$3.82
06IndonesiaAsia-Pacific$32.06$0.109$9.60
07ChileAmericas$32.31$0.102$14.92
08ArgentinaAmericas$32.89$0.108$15.10
09MalaysiaAsia-Pacific$33.20$0.120$10.17
10VietnamAsia-Pacific$33.59$0.125$9.67
11UAEMEA$34.01$0.109$21.58
12South KoreaAsia-Pacific$34.27$0.114$20.34
13NorwayEurope$34.47$0.101$29.33
14SwedenEurope$34.50$0.104$27.72
15PolandEurope$35.97$0.137$17.61
16CanadaAmericas$36.61$0.123$30.76
17IsraelMEA$36.73$0.118$34.77
18ChinaAsia-Pacific$36.87$0.146$18.10
19FranceEurope$37.31$0.136$27.51
20FinlandEurope$37.47$0.133$30.58
21South AfricaAfrica$37.88$0.161$15.36
22NetherlandsEurope$38.43$0.144$30.42
23IndiaAsia-Pacific$39.03$0.182$9.53
24MexicoAmericas$39.07$0.165$21.17
25SwitzerlandEurope$39.45$0.136$43.59
26BrazilAmericas$39.60$0.175$18.28
27ItalyEurope$39.99$0.168$25.95
28United KingdomEurope$42.06$0.177$35.70
29KenyaAfrica$42.98$0.217$13.79
30IrelandEurope$43.08$0.190$34.55
31United StatesAmericas$43.34$0.181$43.34
32JapanAsia-Pacific$44.25$0.212$27.61
33AustraliaAsia-Pacific$45.06$0.204$40.63
34SpainEurope$48.95$0.260$29.78
35GermanyEurope$49.43$0.256$37.50
PPP-adjusted cost uses the World Bank price-level ratio. It is a price-level adjustment, not a direct measure of household income.
Power

In this model, cheaper power often lines up with cheaper AI.

The coding-assistant inference month stays fixed. What moves most clearly by country is business electricity. Lower power benchmarks often line up with lower monthly inference cost in the estimate, even though price levels and other factors still matter too.

Figure 2Business power against monthly coding-assistant inference cost
Each dot = 1 country
Dot color = monthly inference cost
LowerHigher
Read it as correlation inside the model, not proof that power alone determines country cost.
Affordability

The lowest dollar estimate is not always the lowest PPP-adjusted estimate.

First, ask where the same coding-assistant inference month lands lowest in dollar terms. Then ask how that same estimate looks after local price-level adjustment. That is what the PPP view adds as a second lens.

What Changes

The rankings overlap, but not perfectly. Some countries look cheap on the raw monthly cost and even cheaper after local price-level adjustment. Others do not. This is still a price-level view inside the model, not a household income measure or a direct wage benchmark.

India is estimated at $39.03 on the dollar view, but falls to $9.53 after PPP price-level adjustment.

United States sits at $43.34 on both views because the U.S. price level is the reference point for the ratio.

Dollar View
Lowest dollar cost

Where the same coding-assistant inference month lands lowest in the raw dollar estimate.

PPP View
Lowest PPP-adjusted cost

Where that same coding-assistant inference estimate lands lowest after local price-level adjustment.

Why It Matters

If this pattern holds, cheaper coding assistance could matter.

Lower coding-assistant inference cost is not just a pricing detail. It could change how often teams use AI while they build software, how widely coding help gets deployed inside companies, and how fast those tools spread through an economy. Over time, cheaper AI help could become a structural advantage, but that implication is broader than this dataset alone can prove.

More experimentation

If each run is cheaper, teams may test more prompts, workflows, and products.

More automation

Lower inference cost could make AI coding help easier to put in the hands of more developers.

Faster adoption

Countries and companies with cheaper AI help may be able to scale usage earlier and more widely.

Trend

The underlying monthly inference model spend has been trending down.

This line shows the broad direction of change for the same standardized coding-assistant inference month between April 2024 and March 2026. It is meant to show directional deflation in the modeled basket, not serve as an audited month-by-month benchmark.

Figure 3Illustrative monthly coding-assistant inference trend
Read this chart as direction rather than exact historical market pricing. The point is broad deflation, not audited monthly precision.
Method

What counts as one month

For clarity, this page uses one fixed comparison unit: 1 month of a coding-assistant inference workflow. The scenario is 22 workdays × 10 coding sessions/day × ~45K total tokens/session, or about 9.9M total inference tokens all-in.

Under the hood, that works out to 9.9M total tokens, modeled as 70% input / 30% output across a coding-focused basket of current OpenAI, Anthropic, and Google inference models.

The Token Index is a sourced model, not a live benchmark. It starts from official model list prices reviewed on April 20, 2026, then adjusts that same month with two cross-country benchmarks: a World Bank business-electricity tariff benchmark from 2019 and a World Bank PPP price-level ratio from 2024.

monthly inference cost = base monthly basket × (0.50 baseline + 0.35 × electricity / median electricity + 0.15 × price level ratio)

Primary sources reviewed: OpenAI pricing, Anthropic pricing, Gemini pricing, and IEA Energy and AI, World Bank indicators API, and World Bank electricity benchmark.

Plain English

We are not claiming that a coding tool has a different retail seat price in each country. We are estimating what the same month of inference model usage would cost under different national cost conditions, then showing a PPP-adjusted second view. This does not include prompt caching, enterprise discounts, or SaaS markup.

Metric
The Month

1 month of a coding-assistant inference workflow. 9.9M total tokens, modeled as 70% input / 30% output.

Metric
Affordability

PPP-adjusted cost. This shows how the same inference workflow looks after local price-level adjustment.

Metric
Power

Median business electricity benchmark: $0.136/kWh.

Data Appendix

Source-backed country inputs

Every country row below uses the same source years: business electricity benchmark from 2019 and price-level ratio from 2024. The coding-focused inference basket centers on $3.92 per 1M tokens, or $38.84 for the standard inference month before country adjustments. The current cross-country average estimate is $37.29.

35 countriesDerived estimate + sourced inputs
CountryMonthly costBusiness powerPrice levelPPP-adjusted
Singapore$28.42$0.0550.60x$17.10
Saudi Arabia$29.68$0.0740.49x$14.60
Egypt$29.92$0.0970.14x$4.13
Türkiye$30.37$0.0890.35x$10.70
Nigeria$32.01$0.1190.12x$3.82
Indonesia$32.06$0.1090.30x$9.60
Chile$32.31$0.1020.46x$14.92
Argentina$32.89$0.1080.46x$15.10
Malaysia$33.20$0.1200.31x$10.17
Vietnam$33.59$0.1250.29x$9.67
UAE$34.01$0.1090.63x$21.58
South Korea$34.27$0.1140.59x$20.34
Norway$34.47$0.1010.85x$29.33
Sweden$34.50$0.1040.80x$27.72
Poland$35.97$0.1370.49x$17.61
Canada$36.61$0.1230.84x$30.76
Israel$36.73$0.1180.95x$34.77
China$36.87$0.1460.49x$18.10
France$37.31$0.1360.74x$27.51
Finland$37.47$0.1330.82x$30.58
South Africa$37.88$0.1610.41x$15.36
Netherlands$38.43$0.1440.79x$30.42
India$39.03$0.1820.24x$9.53
Mexico$39.07$0.1650.54x$21.17
Switzerland$39.45$0.1361.11x$43.59
Brazil$39.60$0.1750.46x$18.28
Italy$39.99$0.1680.65x$25.95
United Kingdom$42.06$0.1770.85x$35.70
Kenya$42.98$0.2170.32x$13.79
Ireland$43.08$0.1900.80x$34.55
United States$43.34$0.1811.00x$43.34
Japan$44.25$0.2120.62x$27.61
Australia$45.06$0.2040.90x$40.63
Spain$48.95$0.2600.61x$29.78
Germany$49.43$0.2560.76x$37.50