diff --git a/test/newton_neural_ode_tests.jl b/test/newton_neural_ode_tests.jl
index 35ec5aab9..62e429237 100644
--- a/test/newton_neural_ode_tests.jl
+++ b/test/newton_neural_ode_tests.jl
@@ -34,10 +34,10 @@
     optprob = Optimization.OptimizationProblem(optf, psd)
 
     res = Optimization.solve(optprob, NewtonTrustRegion(); maxiters = 100, callback = cb)
-    @test loss_function(res.minimizer) < l1
+    @test loss_function(res.u) < l1
     res = Optimization.solve(optprob, OptimizationOptimJL.Optim.KrylovTrustRegion();
         maxiters = 100, callback = cb)
-    @test loss_function(res.minimizer) < l1
+    @test loss_function(res.u) < l1
 
     @info "ROCK2"
     nODE = NeuralODE(NN, tspan, ROCK2(); reltol = 1.0f-4, saveat = [tspan[end]])
@@ -55,8 +55,8 @@
     optprob = Optimization.OptimizationProblem(optfunc, psd)
 
     res = Optimization.solve(optprob, NewtonTrustRegion(); maxiters = 100, callback = cb)
-    @test loss_function(res.minimizer) < l1
+    @test loss_function(res.u) < l1
     res = Optimization.solve(optprob, OptimizationOptimJL.Optim.KrylovTrustRegion();
         maxiters = 100, callback = cb)
-    @test loss_function(res.minimizer) < l1
+    @test loss_function(res.u) < l1
 end
diff --git a/test/second_order_ode_tests.jl b/test/second_order_ode_tests.jl
index 45641dbe3..5078afa01 100644
--- a/test/second_order_ode_tests.jl
+++ b/test/second_order_ode_tests.jl
@@ -39,7 +39,7 @@
         (x, p) -> loss_n_ode(x), Optimization.AutoZygote())
     optprob = Optimization.OptimizationProblem(optfunc, p)
     res = Optimization.solve(optprob, Adam(0.01f0); callback = callback, maxiters = 100)
-    l2 = loss_n_ode(res.minimizer)
+    l2 = loss_n_ode(res.u)
     @test l2 < l1
 
     function predict(p)
@@ -59,7 +59,7 @@
         (x, p) -> loss_n_ode(x), Optimization.AutoZygote())
     optprob = Optimization.OptimizationProblem(optfunc, p)
     res = Optimization.solve(optprob, Adam(0.01f0); callback = callback, maxiters = 100)
-    l2 = loss_n_ode(res.minimizer)
+    l2 = loss_n_ode(res.u)
     @test l2 < l1
 
     function predict(p)
@@ -79,6 +79,6 @@
         (x, p) -> loss_n_ode(x), Optimization.AutoZygote())
     optprob = Optimization.OptimizationProblem(optfunc, p)
     res = Optimization.solve(optprob, Adam(0.01f0); callback = callback, maxiters = 100)
-    l2 = loss_n_ode(res.minimizer)
+    l2 = loss_n_ode(res.u)
     @test l2 < l1
 end
diff --git a/test/stiff_nested_ad_tests.jl b/test/stiff_nested_ad_tests.jl
index 4742936f4..697300563 100644
--- a/test/stiff_nested_ad_tests.jl
+++ b/test/stiff_nested_ad_tests.jl
@@ -39,7 +39,7 @@
         optprob = Optimization.OptimizationProblem(optfunc, ps)
         res = Optimization.solve(
             optprob, Adam(0.1); callback = callback(solver), maxiters = 100)
-        loss2 = loss_n_ode(lux_model, res.minimizer)
+        loss2 = loss_n_ode(lux_model, res.u)
         @test loss2 < loss1
     end
 end