diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 8517f10..ed76da2 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -32,6 +32,13 @@ jobs:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
       - uses: julia-actions/cache@v1
+      - name: dev
+        shell: julia --project=@. {0}
+        run: |
+          using Pkg
+          Pkg.add([
+              PackageSpec(name="MathOptInterface", rev="bl/nonlinear_model"),
+          ])
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
         with:
diff --git a/Project.toml b/Project.toml
index b3919b8..c2b5857 100644
--- a/Project.toml
+++ b/Project.toml
@@ -3,6 +3,7 @@ uuid = "76087f3c-5699-56af-9a33-bf431cd00edd"
 version = "1.2.1"
 
 [deps]
+ArrayDiff = "c45fa1ca-6901-44ac-ae5b-5513a4852d50"
 CEnum = "fa961155-64e5-5f13-b03f-caf6b980ea82"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 NLopt_jll = "079eb43e-fd8e-5478-9966-2cf3e3edb778"
diff --git a/ext/NLoptMathOptInterfaceExt.jl b/ext/NLoptMathOptInterfaceExt.jl
index 050b86c..2552647 100644
--- a/ext/NLoptMathOptInterfaceExt.jl
+++ b/ext/NLoptMathOptInterfaceExt.jl
@@ -5,6 +5,7 @@
 
 module NLoptMathOptInterfaceExt
 
+import ArrayDiff
 import MathOptInterface as MOI
 import NLopt
 
@@ -31,7 +32,7 @@ mutable struct Optimizer <: MOI.AbstractOptimizer
     variables::MOI.Utilities.VariablesContainer{Float64}
     starting_values::Vector{Union{Nothing,Float64}}
     nlp_data::MOI.NLPBlockData
-    nlp_model::Union{Nothing,MOI.Nonlinear.Model}
+    nlp_model::Union{Nothing,MOI.Nonlinear.Model,ArrayDiff.Model}
     ad_backend::MOI.Nonlinear.AbstractAutomaticDifferentiation
     sense::Union{Nothing,MOI.OptimizationSense}
     objective::Union{
@@ -598,7 +599,7 @@ function _init_nlp_model(model)
         if !(model.nlp_data.evaluator isa _EmptyNLPEvaluator)
             error("Cannot mix the new and legacy nonlinear APIs")
         end
-        model.nlp_model = MOI.Nonlinear.Model()
+        model.nlp_model = ArrayDiff.model(model.ad_backend)
     end
     return
 end
diff --git a/test/MOI_wrapper.jl b/test/MOI_wrapper.jl
index 63e38f6..a0d3a5c 100644
--- a/test/MOI_wrapper.jl
+++ b/test/MOI_wrapper.jl
@@ -361,6 +361,30 @@ function test_ListOfSupportedNonlinearOperators()
     return
 end
 
+function test_ScalarNonlinearFunction_SymbolicMode()
+    # Test that the AutomaticDifferentiationBackend is used when building the
+    # evaluator. SymbolicMode is a built-in alternative to SparseReverseMode.
+    model = NLopt.Optimizer()
+    MOI.set(model, MOI.RawOptimizerAttribute("algorithm"), :LD_LBFGS)
+    MOI.set(
+        model,
+        MOI.AutomaticDifferentiationBackend(),
+        MOI.Nonlinear.SymbolicMode(),
+    )
+    x = MOI.add_variable(model)
+    MOI.set(model, MOI.VariablePrimalStart(), x, 2.0)
+    # min (x - 1)^2 => x* = 1
+    f = MOI.ScalarNonlinearFunction(
+        :^,
+        Any[MOI.ScalarNonlinearFunction(:-, Any[x, 1.0]), 2.0],
+    )
+    MOI.set(model, MOI.ObjectiveSense(), MOI.MIN_SENSE)
+    MOI.set(model, MOI.ObjectiveFunction{MOI.ScalarNonlinearFunction}(), f)
+    MOI.optimize!(model)
+    @test isapprox(MOI.get(model, MOI.VariablePrimal(), x), 1.0; atol = 1e-4)
+    return
+end
+
 end  # module
 
 TestMOIWrapper.runtests()