x>=y or xy

yields True if is determined to be greater than or equal to .


yields True if the form a nonincreasing sequence.



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Basic Examples  (2)

Compare numbers:

Represent an inequality:

Scope  (9)

Numeric Inequalities  (7)

Inequalities are defined only for real numbers:

Compare rational numbers:

Approximate numbers that differ in at most their last eight binary digits are considered equal:

Compare an exact numeric expression and an approximate number:

Compare two exact numeric expressions; a numeric test may suffice to prove inequality:

Proving this inequality requires symbolic methods:

Symbolic and numeric methods used by GreaterEqual are insufficient to prove this inequality:

Use RootReduce to decide the sign of algebraic numbers:

Numeric methods used by GreaterEqual do not use sufficient precision to disprove this:

RootReduce disproves the inequality using exact methods:

Increasing $MaxExtraPrecision may disprove the inequality:

Symbolic Inequalities  (2)

Symbolic inequalities remain unevaluated, since x may not be a real number:

Use Refine to reevaluate the inequality assuming that x is real:

A symbolic inequality:

Use Reduce to find an explicit description of the solution set:

Use FindInstance to find a solution instance:

Use Minimize to optimize over the region defined by the inequality:

Use Refine to simplify under assumptions defined by the inequality:

Properties & Relations  (12)

The negation of two-argument GreaterEqual is Less:

The negation of three-argument GreaterEqual does not simplify automatically:

Use LogicalExpand to express the negation in terms of two-argument Less:

This is not equivalent to three-argument Less:

When GreaterEqual cannot decide an inequality it returns unchanged:

FullSimplify uses exact symbolic transformations to prove the inequality:

NonNegative[x] is equivalent to :

Use Reduce to solve inequalities:

Use FindInstance to find solution instances:

Use RegionPlot and RegionPlot3D to visualize solution sets of inequalities:

Inequality assumptions:

Use Minimize and Maximize to solve optimization problems constrained by inequalities:

Use NMinimize and NMaximize to numerically solve constrained optimization problems:

Integrate a function over the solution set of inequalities:

Use Median, Quantile, and Quartiles to the ^(th) greatest number(s):

Possible Issues  (3)

Inequalities for machine-precision approximate numbers can be subtle:

The result is determined based on extra digits:

Arbitrary-precision approximate numbers do not have this problem:

Thanks to automatic precision tracking, GreaterEqual knows to look only at the first 10 digits:

In this case, inequality between machine numbers gives the expected result:

The extra digits in this case are ignored by GreaterEqual:

Wolfram Research (1988), GreaterEqual, Wolfram Language function, (updated 1996).


Wolfram Research (1988), GreaterEqual, Wolfram Language function, (updated 1996).


Wolfram Language. 1988. "GreaterEqual." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 1996.


Wolfram Language. (1988). GreaterEqual. Wolfram Language & System Documentation Center. Retrieved from


@misc{reference.wolfram_2024_greaterequal, author="Wolfram Research", title="{GreaterEqual}", year="1996", howpublished="\url{}", note=[Accessed: 24-June-2024 ]}


@online{reference.wolfram_2024_greaterequal, organization={Wolfram Research}, title={GreaterEqual}, year={1996}, url={}, note=[Accessed: 24-June-2024 ]}