diff --git a/src/factorization.jl b/src/factorization.jl
index 695909ae1..7c261ec6b 100644
--- a/src/factorization.jl
+++ b/src/factorization.jl
@@ -1010,7 +1010,7 @@ function init_cacheval(alg::NormalCholeskyFactorization, A, b, u, Pl, Pr,
     maxiters::Int, abstol, reltol, verbose::Bool,
     assumptions::OperatorAssumptions)
     A_ = convert(AbstractMatrix, A)
-    return ArrayInterface.cholesky_instance(Symmetric((A)' * A), alg.pivot)
+    return ArrayInterface.cholesky_instance(Symmetric(Matrix{eltype(A)}(undef,0,0)), alg.pivot)
 end
 
 function init_cacheval(alg::NormalCholeskyFactorization,
diff --git a/test/default_algs.jl b/test/default_algs.jl
index 431e2d155..11d536136 100644
--- a/test/default_algs.jl
+++ b/test/default_algs.jl
@@ -45,24 +45,25 @@ solve(prob)
 prob = LinearProblem(sprand(11000, 11000, 0.5), zeros(11000))
 solve(prob)
 
-@static if VERSION >= v"v1.9-"
-    # Test inference 
-    A = rand(4, 4)
-    b = rand(4)
-    prob = LinearProblem(A, b)
-    VERSION ≥ v"1.10-" && JET.@test_opt init(prob, nothing)
-    JET.@test_opt solve(prob, LUFactorization())
-    JET.@test_opt solve(prob, GenericLUFactorization())
-    @test_skip JET.@test_opt solve(prob, QRFactorization())
-    JET.@test_opt solve(prob, DiagonalFactorization())
-    #JET.@test_opt solve(prob, SVDFactorization())
-    #JET.@test_opt solve(prob, KrylovJL_GMRES())
+# Test inference
+A = rand(4, 4)
+b = rand(4)
+prob = LinearProblem(A, b)
+VERSION ≥ v"1.10-" && JET.@test_opt init(prob, nothing)
+JET.@test_opt solve(prob, LUFactorization())
+JET.@test_opt solve(prob, GenericLUFactorization())
+@test_skip JET.@test_opt solve(prob, QRFactorization())
+JET.@test_opt solve(prob, DiagonalFactorization())
+#JET.@test_opt solve(prob, SVDFactorization())
+#JET.@test_opt solve(prob, KrylovJL_GMRES())
 
-    prob = LinearProblem(sparse(A), b)
-    #JET.@test_opt solve(prob, UMFPACKFactorization())
-    #JET.@test_opt solve(prob, KLUFactorization())
-    #JET.@test_opt solve(prob, SparspakFactorization())
-    #JET.@test_opt solve(prob)
-    @inferred solve(prob)
-    @inferred init(prob, nothing)
-end
+prob = LinearProblem(sparse(A), b)
+#JET.@test_opt solve(prob, UMFPACKFactorization())
+#JET.@test_opt solve(prob, KLUFactorization())
+#JET.@test_opt solve(prob, SparspakFactorization())
+#JET.@test_opt solve(prob)
+@inferred solve(prob)
+@inferred init(prob, nothing)
+
+prob = LinearProblem(big.(rand(10, 10)), big.(zeros(10)))
+solve(prob)