diff --git a/test/Polar/api.jl b/test/Polar/api.jl
index 0c6d5691..c5e5dc28 100644
--- a/test/Polar/api.jl
+++ b/test/Polar/api.jl
@@ -135,8 +135,7 @@ function test_polar_api(polar, device, M)
 
     ## Cost Production
     cost_production = ExaPF.CostFunction(polar)
-    c2 = CUDA.@allowscalar cost_production(stack)[1]
-    @test isa(c2, Real)
+    @test isa(cost_production(stack), M)
     # Test display
     println(devnull, cost_production)
     println(devnull, basis)
diff --git a/test/Polar/second_order.jl b/test/Polar/second_order.jl
index 947d55f1..ede47d6e 100644
--- a/test/Polar/second_order.jl
+++ b/test/Polar/second_order.jl
@@ -121,7 +121,7 @@ function test_full_space_hessian(polar, device, MT)
     Hd = FiniteDiff.finite_difference_jacobian(grad_fd_x, x)
 
     # Test that both Hessian match
-    if isa(device, ROCBackend)
+    if startswith(string(device), "ROCBackend")
         @test_broken myisapprox(Hd, H, rtol=1e-5)
     else
         @test myisapprox(Hd, H, rtol=1e-5)
diff --git a/test/quickstart.jl b/test/quickstart.jl
index 001e8fb5..7a7c3da1 100644
--- a/test/quickstart.jl
+++ b/test/quickstart.jl
@@ -72,7 +72,7 @@ const LS = ExaPF.LinearSolvers
     @test convergence.n_iterations == 5
     @test convergence.norm_residuals <= pf_algo.tol
 
-    if CUDA.has_cuda_gpu()
+    if test_cuda
         polar_gpu = ExaPF.PolarForm(pf, CUDABackend())
         stack_gpu = ExaPF.NetworkStack(polar_gpu)
 
diff --git a/test/runtests.jl b/test/runtests.jl
index d1b9ca57..f064b841 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -1,8 +1,7 @@
-using Test
-
-using Random
 using LinearAlgebra
+using Random
 using SparseArrays
+using Test
 
 using AMDGPU
 using CUDA
@@ -16,15 +15,21 @@ const BENCHMARK_DIR = joinpath(dirname(@__FILE__), "..", "benchmark")
 const EXAMPLES_DIR = joinpath(dirname(@__FILE__), "..", "examples")
 const CASES = ["case9.m", "case30.m"]
 
-# ARCHS = Any[(CPU(), Array, SparseMatrixCSC)]
-ARCHS = []
-if CUDA.has_cuda()
+is_package_installed(name::String) = !isnothing(Base.find_package(name))
+
+ARCHS = Any[(CPU(), Array, SparseMatrixCSC)]
+
+test_cuda = CUDA.functional()
+test_rocm = AMDGPU.functional()
+
+# Setup CUDA
+if test_cuda
     using CUDA.CUSPARSE
     CUDA.allowscalar(false)
     CUDA_ARCH = (CUDABackend(), CuArray, CuSparseMatrixCSR)
     push!(ARCHS, CUDA_ARCH)
 end
-if AMDGPU.has_rocm_gpu()
+if test_rocm
     using AMDGPU.rocSPARSE
     AMDGPU.allowscalar(false)
     ROC_ARCH = (ROCBackend(), ROCArray, ROCSparseMatrixCSR)