diff --git a/test/enzyme.jl b/test/enzyme.jl
index dbacb70f1..e00553d69 100644
--- a/test/enzyme.jl
+++ b/test/enzyme.jl
@@ -6,10 +6,8 @@ A = rand(n, n);
 dA = zeros(n, n);
 b1 = rand(n);
 db1 = zeros(n);
-b2 = rand(n);
-db2 = zeros(n);
 
-function f(A, b1, b2; alg = LUFactorization())
+function f(A, b1; alg = LUFactorization())
     prob = LinearProblem(A, b1)
 
     sol1 = solve(prob, alg)
@@ -18,16 +16,15 @@ function f(A, b1, b2; alg = LUFactorization())
     norm(s1)
 end
 
-f(A, b1, b2) # Uses BLAS
+f(A, b1) # Uses BLAS
 
-Enzyme.autodiff(Reverse, f, Duplicated(copy(A), dA), Duplicated(copy(b1), db1), Duplicated(copy(b2), db2))
+Enzyme.autodiff(Reverse, f, Duplicated(copy(A), dA), Duplicated(copy(b1), db1))
 
 dA2 = FiniteDiff.finite_difference_gradient(x->f(x,b1, b2), copy(A))
 db12 = FiniteDiff.finite_difference_gradient(x->f(A,x, b2), copy(b1))
 
 @test dA ≈ dA2
 @test db1 ≈ db12
-@test db2 == zeros(4)
 
 A = rand(n, n);
 dA = zeros(n, n);
@@ -36,9 +33,6 @@ b1 = rand(n);
 db1 = zeros(n);
 db12 = zeros(n);
 
-b2 = rand(n);
-db2 = zeros(n);
-db22 = zeros(n);
-
-@test_broken Enzyme.autodiff(Reverse, f, Duplicated(copy(A), dA), BatchDuplicated(copy(b1), (db1, db12)), BatchDuplicated(copy(b2), (db2, db22)))
-@test_broken Enzyme.autodiff(Reverse, f, BatchDuplicated(copy(A), (dA, dA2)), Duplicated(copy(b1), db1), Duplicated(copy(b2), db2))
\ No newline at end of file
+# This is not legal, all args need to be batch'd at the same size
+@test_broken Enzyme.autodiff(Reverse, f, Duplicated(copy(A), dA), BatchDuplicated(copy(b1), (db1, db12)))
+@test_broken Enzyme.autodiff(Reverse, f, BatchDuplicated(copy(A), (dA, dA2)), Duplicated(copy(b1), db1))