diff --git a/src/nlp_expr.jl b/src/nlp_expr.jl
index 7d3f87c141f..e77e9cd09da 100644
--- a/src/nlp_expr.jl
+++ b/src/nlp_expr.jl
@@ -383,6 +383,11 @@ for f in (:+, :-, :*, :^, :/, :atan, :min, :max)
     end
 end
 
+# Base has unary methods `min(x::Real) = x` and `max(x::Real) = x`, so I guess
+# we need to replicate them.
+Base.min(x::AbstractJuMPScalar) = x
+Base.max(x::AbstractJuMPScalar) = x
+
 function _MA.operate!!(
     ::typeof(_MA.add_mul),
     x::GenericNonlinearExpr,
diff --git a/test/test_nlp_expr.jl b/test/test_nlp_expr.jl
index 1c28c9ed6d0..e07dc1ed036 100644
--- a/test/test_nlp_expr.jl
+++ b/test/test_nlp_expr.jl
@@ -954,6 +954,9 @@ function test_operator_min()
     @variable(model, x)
     @test isequal_canonical(min(x, 1), NonlinearExpr(:min, Any[x, 1.0]))
     @test isequal_canonical(min(1, x, x^2), min(min(1.0, x), x^2))
+    for f in (x, 1.0 * x + 2.0, x^2, sin(x))
+        @test min(f) === f
+    end
     return
 end
 
@@ -962,6 +965,9 @@ function test_operator_max()
     @variable(model, x)
     @test isequal_canonical(max(x, 1), NonlinearExpr(:max, Any[x, 1.0]))
     @test isequal_canonical(max(1, x, x^2), max(max(1.0, x), x^2))
+    for f in (x, 1.0 * x + 2.0, x^2, sin(x))
+        @test max(f) === f
+    end
     return
 end