diff --git a/thursday/go_benchmark_it.py b/thursday/go_benchmark_it.py
index ccd720c..aa99414 100644
--- a/thursday/go_benchmark_it.py
+++ b/thursday/go_benchmark_it.py
@@ -159,25 +159,6 @@ def main(argv, display=True):
     from tqdm import tqdm
     import sys
 
-    def optimizer_filter(name):
-        # worst scoring optimizers: (awards=(5, 3, 2, 1)) (obj=146, opt=389) (dims=2, evals=80)
-        #   evosax_pbt                       with (score:   0, price: 593) -593
-        # worst scoring optimizers: (awards=(5, 3, 2, 1)) (obj=70, opt=389) (dims=3, evals=1440)
-        #   evosax_pbt                       with (score:   0, price: 315) -315
-        return not (
-            False
-            # or name.startswith("freelunch_krillherd_")  # too buggy
-            or name == "ng_fcma_cube"  # WTF HOW ARE YOU NAN'ING ON HYPERSPHERE
-            or name == "ngx_fcmas03_cube"  # same thing but quintic
-            or name == "ngx_zero_cube"  # 0 score, high price
-            # or name == "ngx_microcma_cube"  # 0 score, high price
-            # or name == "ng_multiscalecma_cube"  # 0 score, high price
-            or name == "evosax_pbt_cube"  # 0 score, high price
-            or name == "evosax_guidedes_cube"  # does get *a little* score...
-            or name == "freelunch_sa_ps04_cube"
-            or name == "ngx_microcma_cube"
-        )
-
     def stfu(please_be_quiet=None):
         if please_be_quiet is None:
             please_be_quiet = (
@@ -287,15 +268,7 @@ def main(argv, display=True):
     size = abs(size)
     place_scores = (5, 3, 2, 1)
     objectives = GO_BENCHMARKS[size]  # * multiple
-
     optimizers = list(which)  # copy
-    before = len(optimizers)
-    # if which is not parties["everything"]:
-    optimizers = [opt for opt in optimizers if optimizer_filter(opt.__name__)]
-    after = len(optimizers)
-    s = "s" if before - after != 1 else ""
-    print(f"Pruned {before - after} unwanted optimizer{s}.")
-
     ms = f" ({multiple}+{run_anyway-multiple} times)" if multiple != 1 else ""
     n_obj = len(objectives)
     n_opt = len(optimizers)