diff --git a/tests/unit/conftest.py b/tests/unit/conftest.py
index 2eb08c88..e88bc41f 100644
--- a/tests/unit/conftest.py
+++ b/tests/unit/conftest.py
@@ -1,8 +1,31 @@
+import random
+
+import numpy as np
 import pytest
+import torch
 
 from tests.unit.helpers import TINYSTORIES_MODEL, load_model_cached
 
 
+@pytest.fixture(autouse=True)
+def reproducibility():
+    """Apply various mechanisms to try to prevent nondeterminism in test runs."""
+    # I have not in general attempted to verify that the below are necessary
+    # for reproducibility, only that they are likely to help and unlikely to
+    # hurt.
+    # https://pytorch.org/docs/stable/notes/randomness.html#reproducibility
+    seed = 0x1234_5678_9ABC_DEF0
+    torch.manual_seed(seed)
+    torch.cuda.manual_seed_all(seed)
+    torch.use_deterministic_algorithms(True)
+    torch.backends.cudnn.benchmark = False
+    # Python native RNG; docs don't give any limitations on seed range
+    random.seed(seed)
+    # this is a "legacy" method that operates on a global RandomState
+    # sounds like the argument must be in [0, 2**32)
+    np.random.seed(seed & 0xFFFF_FFFF)
+
+
 @pytest.fixture
 def ts_model():
     return load_model_cached(TINYSTORIES_MODEL)