Less 
Details
- Less is also known as strong inequality or strict inequality.
- Less gives True or False when its arguments are real numbers.
- Less does some simplification when its arguments are not numbers.
- For exact numeric quantities, Less internally uses numerical approximations to establish numerical ordering. This process can be affected by the setting of the global variable $MaxExtraPrecision.
Examples
open all close allBasic Examples (2)
Scope (9)
Numeric Inequalities (7)
Inequalities are defined only for real numbers:
I < 03 / 2 < 5 / 3Approximate numbers that differ in at most their last eight binary digits are considered equal:
1. < 1. + 2 ^ 7 10 ^ -161. < 1. + 2 ^ 8 10 ^ -16Compare an exact numeric expression and an approximate number:
N[Pi, 20] < PiN[Pi, 20] < Pi(1 + 2 ^ 12 10 ^ -20)Compare two exact numeric expressions; a numeric test may suffice to prove inequality:
Pi ^ E < E ^ PiDisproving this inequality requires symbolic methods:
Sqrt[2] + Sqrt[3] < Sqrt[5 + 2Sqrt[6]]Symbolic and numeric methods used by Less are insufficient to disprove this inequality:
Sqrt[2] + Sqrt[3] < Root[# ^ 4 - 10# ^ 2 + 1&, 4]Use RootReduce to decide the sign of algebraic numbers:
RootReduce[%[[1]] - %[[2]]] < 0Numeric methods used by Less do not use sufficient precision to prove this inequality:
Sqrt[2] + Sqrt[3] < Root[# ^ 4 - 10# ^ 2 + 1&, 4] + 10 ^ -100
RootReduce proves the inequality using exact methods:
RootReduce[%[[1]] - %[[2]]] < 0Increasing $MaxExtraPrecision may also prove the inequality:
Block[{$MaxExtraPrecision = 100}, Sqrt[2] + Sqrt[3] < Root[# ^ 4 - 10# ^ 2 + 1&, 4] + 10 ^ -100]Symbolic Inequalities (2)
Symbolic inequalities remain unevaluated, since x may not be a real number:
x < xUse Refine to reevaluate the inequality assuming that x is real:
Refine[%, Element[x, Reals]]ineq = 1 < x ^ 2 + y ^ 2 < 2Use Reduce to find an explicit description of the solution set:
Reduce[ineq, {x, y}]Use FindInstance to find a solution instance:
FindInstance[ineq, {x, y}]Use Minimize to optimize over the inequality-defined region:
Minimize[{x ^ 2 - y ^ 2, ineq}, {x, y}]Use Refine to simplify under the inequality-defined assumptions:
Refine[Sqrt[(2 - x ^ 2) ^ 2], ineq]Properties & Relations (12)
The negation of two-argument Less is GreaterEqual:
Not[x < y]The negation of three-argument Less does not simplify automatically:
Not[x < y < z]Use LogicalExpand to express it in terms of two-argument GreaterEqual:
LogicalExpand[%]This is not equivalent to three-argument GreaterEqual:
LogicalExpand[x ≥ y ≥ z]When Less cannot decide inequality between numeric expressions it returns unchanged:
a = Log[Sqrt[2] + Sqrt[3]];
b = Log[5 + 2Sqrt[6]] / 2;
a < bFullSimplify uses exact symbolic transformations to disprove the inequality:
FullSimplify[%]Negative[x] is equivalent to
:
Negative /@ {-1, 0, 1, I}Use Reduce to solve inequalities:
Reduce[x ^ 5 - 3x + 2 < 0, x]Reduce[y ^ 2 - 4x ^ 2 + 4x ^ 4 < 0, {x, y}]Use FindInstance to find solution instances:
FindInstance[y ^ 2 - 4x ^ 2 + 4x ^ 4 < -z ^ 2, {x, y, z}]Use RegionPlot and RegionPlot3D to visualize solution sets of inequalities:
RegionPlot[y ^ 2 - 4x ^ 2 + 4x ^ 4 < 0, {x, -1, 1}, {y, -1, 1}]RegionPlot3D[y ^ 2 - 4x ^ 2 + 4x ^ 4 < -z ^ 2, {x, -1, 1}, {y, -1, 1}, {z, -1, 1}]Refine[Sqrt[x ^ 2], x < 0]Limit[a ^ n, n -> Infinity, Assumptions -> -1 < a < 1]Use Minimize and Maximize to solve optimization problems constrained by inequalities:
Minimize[{x - y, y ^ 2 - 4x ^ 2 + 4x ^ 4 < 0}, {x, y}]Use NMinimize and NMaximize to numerically solve constrained optimization problems:
NMinimize[{x - y, 1 < Tan[x] + Tan[y] < 2}, {x, y}]Integrate a function over the solution set of inequalities:
Integrate[x ^ 2 Boole[1 < x ^ 2 + y ^ 2 < 2], {x, -Infinity, Infinity}, {y, -Infinity, Infinity}]Use Median, Quantile, and Quartiles to the ![]()
greatest number(s):
{x1, x2, x3} = {1, 2, 3};x1 < x2 < x3Median[{x2, x3, x1}]Possible Issues (3)
Inequalities for machine-precision approximate numbers can be subtle:
0.00001 < 2.00006 - 2.00005The strict inequality is based on extra digits:
2.00006 - 2.00005//InputFormArbitrary-precision approximate numbers do not have this problem:
0.00001`16 < 2.00006`16 - 2.00005`16Thanks to automatic precision tracking, Less knows to look only at the first 10 digits:
Precision[2.00006`16 - 2.00005`16]In this case, inequality between machine numbers gives the expected result:
0.1 < 2.6 - 2.5The extra digits in this case are ignored by Less:
2.6 - 2.5//InputFormTech Notes
Related Guides
History
Introduced in 1988 (1.0) | Updated in 1996 (3.0)
Text
Wolfram Research (1988), Less, Wolfram Language function, https://reference.wolfram.com/language/ref/Less.html (updated 1996).
CMS
Wolfram Language. 1988. "Less." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 1996. https://reference.wolfram.com/language/ref/Less.html.
APA
Wolfram Language. (1988). Less. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/Less.html
BibTeX
@misc{reference.wolfram_2026_less, author="Wolfram Research", title="{Less}", year="1996", howpublished="\url{https://reference.wolfram.com/language/ref/Less.html}", note=[Accessed: 12-June-2026]}
BibLaTeX
@online{reference.wolfram_2026_less, organization={Wolfram Research}, title={Less}, year={1996}, url={https://reference.wolfram.com/language/ref/Less.html}, note=[Accessed: 12-June-2026]}