Belarus vs Zimbabwe: Crude steelmaking capacity

Belarus
3 Tonnes
in 2025
Zimbabwe
2.6 Tonnes
in 2025
Belarus rank
42nd
Zimbabwe rank
44th

Crude steelmaking capacity over time

  • Belarus
  • Zimbabwe
11.522.53200020122025

How they compare

Belarus currently reports 3 Tonnes against 2.6 Tonnes in Zimbabwe, a difference of 0.4 Tonnes.

That makes Belarus's figure about 1.2 times Zimbabwe's.

Across all 26 years both countries report, Belarus has been ahead every year.

Belarus ranks 42nd and Zimbabwe ranks 44th of 115 countries.

Belarus has averaged higher in every one of the 3 decades both report.

Head to head by decade

Decade Belarus Zimbabwe Difference Ahead
2000s 2.8 Tonnes 0.833 Tonnes 1.97 Tonnes Belarus
2010s 2.92 Tonnes 0.833 Tonnes 2.09 Tonnes Belarus
2020s 3 Tonnes 1.73 Tonnes 1.27 Tonnes Belarus

Averages of every year both report within each decade.

Frequently asked questions

Which has higher crude steelmaking capacity, Belarus or Zimbabwe?
Belarus, at 3 Tonnes against 2.6 Tonnes in Zimbabwe as of 2025.
What is the difference in crude steelmaking capacity between Belarus and Zimbabwe?
0.4 Tonnes, with Belarus ahead.
How many years of comparable data are there for Belarus and Zimbabwe?
26 years are reported by both, from 2000 to 2025.
How do Belarus and Zimbabwe rank globally for crude steelmaking capacity?
Belarus ranks 42nd and Zimbabwe ranks 44th of 115 countries.
Where does this data come from?
Organisation for Economic Co-operation and Development, published as Crude steelmaking capacity. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Belarus vs Zimbabwe: Crude steelmaking capacity. Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 22 August 2026, from https://urban.statizoid.com/compare/crude-steelmaking-capacity/belarus/zimbabwe/

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About this data

Indicator
Crude steelmaking capacity
Unit
Tonnes
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
132 places, 3,432 data points, 2000–2025
Last refreshed

This dataset provides information on crude steelmaking capacity for 132 OECD Member countries and non-OECD economies over the period 2000–2025. Definitions Steelmaking capacity Nominal crude steelmaking capacity is defined as the maximum theoretical output of installed steelmaking equipment. This definition does not account for yield losses, maintenance downtime, or other factors affecting actual production. As a result, the steelmaking capacity figures provided by the OECD should not be interpreted as effective capacity. Capacity is expressed in million metric tonnes (mmt). Annual capacity figures reflect all steelmaking capacity existing at the end of each calendar year. Steelmaking equipment Steelmaking equipment includes all equipment used to produce crude steel. The definition excludes ironmaking equipment, which is considered upstream, as well as casting, rolling, and finishing equipment, which are considered downstream. Specifically, crude steelmaking equipment includes electric arc furnaces (EAF), induction furnaces (IF) and LD basic oxygen furnaces (BOF). Methodology Steelmaking capacity developments are derived from data on existing capacity, investments, and closures. Capacity changes reflect new additions and permanent closures and therefore represent net changes. In some cases, capacity may be overestimated due to the assumption that projects classified as underway with expired start dates have become operational. Only permanent closures are included in capacity calculations, although some closures cannot be clearly classified due to limited available information. Data sources OECD calculations based on desk research, company websites, publicly available news sources and information exchanges within the OECD Steel Committee. Cite this dataset OECD (2025). Crude steelmaking capacity dataset. Accessed on [Day Month Year]. Further information OECD Steel Outlook 2025 OECD Steel Committee Global Forum on Steel Excess Capacity For questions or comments regarding this dataset, please contact Maika Sakamoto (Maika.SAKAMOTO@oecd.org) or Masanobu Nakamizu (Masanobu.NAKAMIZU@oecd.org).