diff --git a/test/runtests.jl b/test/runtests.jl
index aee01b5..1f816ae 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -35,57 +35,4 @@ else
 end
 
 include("transform.jl")
-include("utils.jl")
-
-# Benchmark the transform function
-@testset "Benchmarks" begin
-    s = 10 # number of samples
-    e = 1 # number of evals
-
-    # Create an array of input sizes to benchmark for 2D
-    sizes_2D = [2^i for i in 3:4]
-
-    # Create DataFrames to store the benchmark results
-    df_dt_2D = DataFrame(
-        os_info = os_info,
-        gpu_info = gpu_info,
-        sizes = sizes_2D,
-        dt_proposed = Float64[]
-    )
-
-    for n in sizes_2D
-        f = Float32.(rand([0, 1], n, n))
-
-        if dev != Array
-            f_dev = dev(f)
-            dt = @benchmark(transform($boolean_indicator($f_dev)); samples=s, evals=e)
-            push!(df_dt_2D, [os_info, gpu_info, n, minimum(dt).time])
-        end
-    end
-
-    # Create an array of input sizes to benchmark for 3D
-    sizes_3D = [2^i for i in 0:2]
-
-    # Create DataFrames to store the benchmark results
-    df_dt_3D = DataFrame(
-        os_info = os_info,
-        gpu_info = gpu_info,
-        sizes = sizes_3D,
-        dt_proposed = Float64[]
-    )
-
-    for n in sizes_3D
-        f = Float32.(rand([0, 1], n, n, n))
-
-        if dev != Array
-            f_dev = dev(f)
-            dt = @benchmark(transform($boolean_indicator($f_dev)); samples=s, evals=e)
-            push!(df_dt_3D, [os_info, gpu_info, n, minimum(dt).time])
-        end
-    end
-
-    # Show the dataframes
-    @info df_dt_2D
-    @info df_dt_3D
-    @test 1 == 1
-end
\ No newline at end of file
+include("utils.jl")
\ No newline at end of file