diff --git a/src/JuMP.jl b/src/JuMP.jl
index 4a589aa1a83..207c9989996 100644
--- a/src/JuMP.jl
+++ b/src/JuMP.jl
@@ -163,7 +163,7 @@ mutable struct GenericModel{T<:Real} <: AbstractModel
     enable_macro_timing::Bool
     macro_times::Dict{Tuple{LineNumberNode,String},Float64}
     # A cache to track common subexpressions based on their `objectid`.
-    subexpressions::Dict{UInt64,MOI.ScalarNonlinearFunction}
+    subexpressions::Base.IdDict{Any,MOI.ScalarNonlinearFunction}
 end
 
 value_type(::Type{GenericModel{T}}) where {T} = T
@@ -278,7 +278,7 @@ function direct_generic_model(
         Dict{Any,MOI.ConstraintIndex}(),
         false,
         Dict{Tuple{LineNumberNode,String},Float64}(),
-        Dict{UInt64,MOI.ScalarNonlinearFunction}(),
+        Base.IdDict{Any,MOI.ScalarNonlinearFunction}(),
     )
 end
 
diff --git a/src/jump_moi_function.jl b/src/jump_moi_function.jl
index 871788af125..7caa4f044ae 100644
--- a/src/jump_moi_function.jl
+++ b/src/jump_moi_function.jl
@@ -167,10 +167,9 @@ end
 moi_function_type(::Type{<:GenericNonlinearExpr}) = MOI.ScalarNonlinearFunction
 
 function moi_function(model::GenericModel, f::GenericNonlinearExpr{V}) where {V}
-    # key = objectid(f)
-    # if haskey(model.subexpressions, key)
-    #     return model.subexpressions[key]
-    # end
+    if (subexpression = get(model.subexpressions, f, nothing)) !== nothing
+        return subexpression
+    end
     ret = MOI.ScalarNonlinearFunction(f.head, similar(f.args))
     stack = Tuple{MOI.ScalarNonlinearFunction,Int,GenericNonlinearExpr{V}}[]
     for i in length(f.args):-1:1
@@ -182,11 +181,10 @@ function moi_function(model::GenericModel, f::GenericNonlinearExpr{V}) where {V}
     end
     while !isempty(stack)
         parent, i, arg = pop!(stack)
-        # arg_key = objectid(arg)
-        # if haskey(model.subexpressions, arg_key)
-        #     parent.args[i] = model.subexpressions[arg_key]
-        #     continue
-        # end
+        if (subexpression = get(model.subexpressions, arg, nothing)) !== nothing
+            parent.args[i] = subexpression
+            continue
+        end
         child = MOI.ScalarNonlinearFunction(arg.head, similar(arg.args))
         parent.args[i] = child
         for j in length(arg.args):-1:1
@@ -196,9 +194,9 @@ function moi_function(model::GenericModel, f::GenericNonlinearExpr{V}) where {V}
                 child.args[j] = moi_function(model, arg.args[j])
             end
         end
-        # model.subexpressions[arg_key] = child
+        model.subexpressions[arg] = child
     end
-    # model.subexpressions[key] = ret
+    model.subexpressions[f] = ret
     return ret
 end
 
diff --git a/test/test_nlp_expr.jl b/test/test_nlp_expr.jl
index 9992269f68c..caa9e72026d 100644
--- a/test/test_nlp_expr.jl
+++ b/test/test_nlp_expr.jl
@@ -1390,38 +1390,38 @@ function test_custom_array()
     return
 end
 
-# function test_scalar_nonlinear_moi_function()
-#     model = Model()
-#     @variable(model, x)
-#     y1 = atan(x, 2)
-#     y1_moi = MOI.ScalarNonlinearFunction(:atan, Any[index(x), 2])
-#     y2 = y1 + y1
-#     y2_moi = MOI.ScalarNonlinearFunction(:+, Any[y1_moi, y1_moi])
-#     y3 = exp(y2)
-#     y3_moi = MOI.ScalarNonlinearFunction(:exp, Any[y2_moi])
-#     # Test y1
-#     @test isapprox(moi_function(y1), y1_moi)
-#     @test length(model.subexpressions) == 1
-#     @test isapprox(moi_function(model, y1), y1_moi)
-#     @test length(model.subexpressions) == 1
-#     @test isapprox(model.subexpressions[objectid(y1)], y1_moi)
-#     # Test y2
-#     @test isapprox(moi_function(y2), y2_moi)
-#     @test length(model.subexpressions) == 2
-#     @test isapprox(moi_function(model, y2), y2_moi)
-#     @test length(model.subexpressions) == 2
-#     @test isapprox(model.subexpressions[objectid(y1)], y1_moi)
-#     @test isapprox(model.subexpressions[objectid(y2)], y2_moi)
-#     # Test y3
-#     @test isapprox(moi_function(y3), y3_moi)
-#     @test length(model.subexpressions) == 3
-#     @test isapprox(moi_function(model, y3), y3_moi)
-#     @test length(model.subexpressions) == 3
-#     @test isapprox(model.subexpressions[objectid(y1)], y1_moi)
-#     @test isapprox(model.subexpressions[objectid(y2)], y2_moi)
-#     @test isapprox(model.subexpressions[objectid(y3)], y3_moi)
-#     return
-# end
+function test_scalar_nonlinear_moi_function()
+    model = Model()
+    @variable(model, x)
+    y1 = atan(x, 2)
+    y1_moi = MOI.ScalarNonlinearFunction(:atan, Any[index(x), 2])
+    y2 = y1 + y1
+    y2_moi = MOI.ScalarNonlinearFunction(:+, Any[y1_moi, y1_moi])
+    y3 = exp(y2)
+    y3_moi = MOI.ScalarNonlinearFunction(:exp, Any[y2_moi])
+    # Test y1
+    @test isapprox(moi_function(y1), y1_moi)
+    @test length(model.subexpressions) == 1
+    @test isapprox(moi_function(model, y1), y1_moi)
+    @test length(model.subexpressions) == 1
+    @test isapprox(model.subexpressions[y1], y1_moi)
+    # Test y2
+    @test isapprox(moi_function(y2), y2_moi)
+    @test length(model.subexpressions) == 2
+    @test isapprox(moi_function(model, y2), y2_moi)
+    @test length(model.subexpressions) == 2
+    @test isapprox(model.subexpressions[y1], y1_moi)
+    @test isapprox(model.subexpressions[y2], y2_moi)
+    # Test y3
+    @test isapprox(moi_function(y3), y3_moi)
+    @test length(model.subexpressions) == 3
+    @test isapprox(moi_function(model, y3), y3_moi)
+    @test length(model.subexpressions) == 3
+    @test isapprox(model.subexpressions[y1], y1_moi)
+    @test isapprox(model.subexpressions[y2], y2_moi)
+    @test isapprox(model.subexpressions[y3], y3_moi)
+    return
+end
 
 function test_addition_with_zero_Base_sum()
     model = Model()
@@ -1482,4 +1482,15 @@ function test_extension_expression_bedmas_parentheses(
     return
 end
 
+function test_issue_4203()
+    n = 25_000
+    model = Model()
+    @variable(model, x)
+    @constraint(model, cons[i in 1:n], sin(x) * i <= 0)
+    @testset "$i" for i in 1:n
+        @test isequal_canonical(constraint_object(cons[i]).func, sin(x) * i - 0)
+    end
+    return
+end
+
 end  # module