diff --git a/problems/nvidia/eval_better_bench_grouped_gemm.py b/problems/nvidia/eval_better_bench_grouped_gemm.py
index 09b5279..3e9b552 100644
--- a/problems/nvidia/eval_better_bench_grouped_gemm.py
+++ b/problems/nvidia/eval_better_bench_grouped_gemm.py
@@ -1,6 +1,7 @@
 import base64
 import dataclasses
 import multiprocessing
+import random
 import re
 import time
 import os
@@ -242,10 +243,14 @@ def _run_single_benchmark(
     data_list = []
     # generate input data once
 
+    local_seed = test.args.get("seed", None)
     for i in range(NUM_ITERATIONS_PER_BENCHMARK):
-        if "seed" in test.args:
-            test.args["seed"] += 42
-        data = generate_input(**test.args)
+        if local_seed is not None:
+            local_seed += 42
+            args = {**test.args, "seed": local_seed}
+        else:
+            args = test.args
+        data = generate_input(**args)
         data_list.append(data)
 
     check_copy = _clone_data(data_list)
@@ -270,6 +275,13 @@ def _run_single_benchmark(
 
     bm_start_time = time.perf_counter_ns()
     for i in range(max_repeats):
+        # Clone and shuffle data before timing to prevent both
+        # object-identity caching and call-order caching exploits
+        iteration_data = _clone_data(data_list)
+        shuffle_order = list(range(len(iteration_data)))
+        random.shuffle(shuffle_order)
+        iteration_data = [iteration_data[j] for j in shuffle_order]
+
         torch.cuda.synchronize()
 
         outputs = []
@@ -277,7 +289,7 @@ def _run_single_benchmark(
         start_event = torch.cuda.Event(enable_timing=True)
         end_event = torch.cuda.Event(enable_timing=True)
         start_event.record()
-        for data in data_list:
+        for data in iteration_data:
             output = custom_kernel(data)
             outputs.append(output)
         end_event.record()
@@ -287,10 +299,10 @@ def _run_single_benchmark(
         ) * 1e6  # Convert ms to ns
 
         if recheck:
-            for reference_output, custom_output in zip(check_copy, outputs):
-                good, message = check_implementation(reference_output, custom_output)
-            if not good:
-                return message
+            for j, custom_output in zip(shuffle_order, outputs):
+                good, message = check_implementation(check_copy[j], custom_output)
+                if not good:
+                    return message
 
         durations.append(duration)