diff --git a/thunder/tests/test_examine_memory.py b/thunder/tests/test_examine_memory.py
index 80c0b5b83..4a7b40d19 100644
--- a/thunder/tests/test_examine_memory.py
+++ b/thunder/tests/test_examine_memory.py
@@ -115,5 +115,5 @@ def test_nanogpt_block():
     # We are checking the estimated memory against a fixed value for consistency.
     assert max_mem_fw[0] == 262183936
     assert sum(max_mem_fw[1].values()) == 135306240
-    assert max_mem_bw[0] == 484833280
-    assert sum(max_mem_bw[1].values()) == 169915392
+    assert max_mem_bw[0] == 375516160
+    assert sum(max_mem_bw[1].values()) == 40934400
diff --git a/thunder/tests/test_grad.py b/thunder/tests/test_grad.py
index 37c211a01..406af2994 100644
--- a/thunder/tests/test_grad.py
+++ b/thunder/tests/test_grad.py
@@ -1943,7 +1943,8 @@ def test_backward_recomputation_decomposed_ops(device):
     def fn(a):
         return torch.nn.functional.gelu(a)
 
-    jfn = thunder.jit(fn, enable_saved_for_backward_recomputation=False)
+    # rematerialization will also trigger recomputation here.
+    jfn = thunder.jit(fn, executors=(), enable_saved_for_backward_recomputation=False)
     jfn2 = thunder.jit(fn, enable_saved_for_backward_recomputation=True)
     a = torch.randn(2, 2, device=device, requires_grad=True)
     res = jfn(a)