diff --git a/test/external/process_replay/process_replay.py b/test/external/process_replay/process_replay.py
index 15fa660ced..351945a29c 100755
--- a/test/external/process_replay/process_replay.py
+++ b/test/external/process_replay/process_replay.py
@@ -53,7 +53,9 @@ def replay_get_rangeify_map(ret:dict[UOp, UOp], big_sink:UOp) -> tuple[str, str,
 
 def replay_get_program(p:ProgramSpec, ast:UOp, renderer:Renderer, opts:list[Opt]|None=None) -> tuple[str, str, tuple[Any, ...]]:
   # the ast.arg is non None if we are inside of search.py
-  sink_arg = ast.arg or KernelInfo(opts_to_apply=tuple(opts) if opts is not None else p.applied_opts if BEAM>=1 else None)
+  sink_arg = ast.arg or KernelInfo()
+  if opts is not None: sink_arg = replace(sink_arg, opts_to_apply=tuple(opts))
+  elif BEAM >= 1 and sink_arg.opts_to_apply is None: sink_arg = replace(sink_arg, opts_to_apply=p.applied_opts)
   input_ast = ast if ast.op is Ops.PROGRAM else ast.replace(arg=replace(sink_arg, name=p.name))
   p2 = get_program(input_ast, renderer=renderer)
   def to_str(ret:ProgramSpec) -> str:
diff --git a/test/null/test_process_replay.py b/test/null/test_process_replay.py
new file mode 100644
index 0000000000..e2fc5db108
--- /dev/null
+++ b/test/null/test_process_replay.py
@@ -0,0 +1,34 @@
+import unittest
+from tinygrad import Tensor, Device
+from tinygrad.engine.realize import get_program
+from tinygrad.codegen.opt import Opt, OptOps
+from test.external.process_replay.process_replay import replay_get_program
+
+N = 16
+class TestProcessReplay(unittest.TestCase):
+  @classmethod
+  def setUpClass(cls):
+    cls.ast = (Tensor.empty(N, N) @ Tensor.empty(N, N)).schedule()[-1].ast
+    cls.renderer = Device[Device.DEFAULT].renderer
+
+  def test_replay_no_opts(self):
+    # opts=None means use default heuristic path
+    p = get_program(self.ast, self.renderer)
+    good, compare, _ = replay_get_program(p, self.ast, self.renderer)
+    self.assertEqual(good, compare)
+
+  def test_replay_empty_opts(self):
+    # opts=[] means explicitly apply zero opts (unoptimized)
+    p = get_program(self.ast, self.renderer, opts=[])
+    good, compare, _ = replay_get_program(p, self.ast, self.renderer, opts=[])
+    self.assertEqual(good, compare)
+
+  def test_replay_with_opt(self):
+    # opts=[Opt(...)] means apply a specific opt
+    opts = [Opt(OptOps.UPCAST, 0, 4)]
+    p = get_program(self.ast, self.renderer, opts=opts)
+    good, compare, _ = replay_get_program(p, self.ast, self.renderer, opts=opts)
+    self.assertEqual(good, compare)
+
+if __name__ == '__main__':
+  unittest.main(verbosity=2)