diff --git a/src/jacobian.jl b/src/jacobian.jl
index bd4575fcc..fe12d7a86 100644
--- a/src/jacobian.jl
+++ b/src/jacobian.jl
@@ -119,8 +119,10 @@ __init_JᵀJ(J::StaticArray) = MArray{Tuple{size(J, 2), size(J, 2)}, eltype(J)}(
 
 ## Special Handling for Scalars
 function jacobian_caches(alg::AbstractNonlinearSolveAlgorithm, f, u::Number, p,
-    ::Val{false}; kwargs...)
+    ::Val{false}; linsolve_with_JᵀJ::Val{needsJᵀJ} = Val(false),
+    kwargs...) where {needsJᵀJ}
     # NOTE: Scalar `u` assumes scalar output from `f`
     uf = JacobianWrapper{false}(f, p)
+    needsJᵀJ && return uf, nothing, u, nothing, nothing, u, u, u 
     return uf, nothing, u, nothing, nothing, u
 end
diff --git a/test/basictests.jl b/test/basictests.jl
index acfeff6c8..1e1ded563 100644
--- a/test/basictests.jl
+++ b/test/basictests.jl
@@ -50,8 +50,8 @@ end
         end
 
         precs = [
-            NonlinearSolve.DEFAULT_PRECS,
-            (args...) -> (Diagonal(rand!(similar(u0))), nothing),
+            (u0) -> NonlinearSolve.DEFAULT_PRECS,
+            u0 -> ((args...) -> (Diagonal(rand!(similar(u0))), nothing)),
         ]
 
         @testset "[IIP] u0: $(typeof(u0)) precs: $(_nameof(prec)) linsolve: $(_nameof(linsolve))" for u0 in ([
@@ -60,13 +60,13 @@ end
             if prec === :Random
                 prec = (args...) -> (Diagonal(randn!(similar(u0))), nothing)
             end
-            sol = benchmark_nlsolve_iip(quadratic_f!, u0; linsolve, precs = prec,
+            sol = benchmark_nlsolve_iip(quadratic_f!, u0; linsolve, precs = prec(u0),
                 linesearch)
             @test SciMLBase.successful_retcode(sol)
             @test all(abs.(sol.u .* sol.u .- 2) .< 1e-9)
 
             cache = init(NonlinearProblem{true}(quadratic_f!, u0, 2.0),
-                NewtonRaphson(; linsolve, precs = prec), abstol = 1e-9)
+                NewtonRaphson(; linsolve, precs = prec(u0)), abstol = 1e-9)
             @test (@ballocated solve!($cache)) ≤ 64
         end
     end
@@ -91,8 +91,7 @@ end
                 res.u ≈ res_true
             end
             @test ForwardDiff.derivative(p -> benchmark_nlsolve_oop(quadratic_f, 1.0, p).u,
-                p) ≈
-                  1 / (2 * sqrt(p))
+                p) ≈ 1 / (2 * sqrt(p))
         end
     end
 
@@ -189,8 +188,7 @@ end
                 res.u ≈ res_true
             end
             @test ForwardDiff.derivative(p -> benchmark_nlsolve_oop(quadratic_f,
-                    oftype(p, 1.0),
-                    p; radius_update_scheme).u, p) ≈ 1 / (2 * sqrt(p))
+                    oftype(p, 1.0), p; radius_update_scheme).u, p) ≈ 1 / (2 * sqrt(p))
         end
     end