diff --git a/code/evaluation/logical_error_rate.py b/code/evaluation/logical_error_rate.py
index 54b65e9..db06dec 100644
--- a/code/evaluation/logical_error_rate.py
+++ b/code/evaluation/logical_error_rate.py
@@ -501,6 +501,17 @@ def map_grid_to_stabilizer_tensor(grid_btdd, stab_indices_1d):
     return flat_bdt.index_select(dim=1, index=stab_indices_1d)
 
 
+def _maybe_warmup_compile(pipeline_module, stim_dets, device, trt_context, applied_compile):
+    """Fire one forward pass to trigger torch.compile JIT before the timing loop."""
+    if trt_context is not None or not applied_compile:
+        return
+    with torch.no_grad():
+        _warmup_tensor = torch.as_tensor(stim_dets[:1], dtype=torch.float32, device=device)
+        pipeline_module(_warmup_tensor)
+        if device.type == "cuda":
+            torch.cuda.synchronize()
+
+
 class PreDecoderMemoryEvalModule(nn.Module):
     """
     nn.Module that encapsulates the full pre-decoder eval path: batch input -> trainX,
@@ -1316,6 +1327,8 @@ def run_inference_and_decode_pre_decoder_memory(model, device, dist, cfg) -> dic
     else:
         data_iter = test_dataloader
 
+    _maybe_warmup_compile(pipeline_module, stim_dets, device, trt_context, _applied_compile)
+
     # Timing instrumentation accumulators (used when timing_rank0 is True)
     residual_syndrome_density_sum = 0.0
     predecoder_batch_times = [] if timing_rank0 else None
diff --git a/code/tests/test_inference_latency_timing.py b/code/tests/test_inference_latency_timing.py
index d537412..cfba0a2 100644
--- a/code/tests/test_inference_latency_timing.py
+++ b/code/tests/test_inference_latency_timing.py
@@ -15,11 +15,12 @@
 
 import math
 import unittest
-from unittest.mock import patch
+from unittest.mock import MagicMock, call, patch
 
 import numpy as np
+import torch
 
-from evaluation.logical_error_rate import _time_single_shot_latency_stim
+from evaluation.logical_error_rate import _maybe_warmup_compile, _time_single_shot_latency_stim
 
 
 class _FakeMatcher:
@@ -84,5 +85,59 @@ def test_time_single_shot_latency_handles_empty(self) -> None:
         self.assertEqual(len(matcher.calls), 0)
 
 
+class TestMaybeWarmupCompile(unittest.TestCase):
+
+    def _cpu_device(self):
+        return torch.device("cpu")
+
+    def test_calls_pipeline_module_when_compile_active(self):
+        pipeline = MagicMock(return_value=torch.zeros(1))
+        dets = np.zeros((4, 8), dtype=np.uint8)
+        _maybe_warmup_compile(
+            pipeline, dets, self._cpu_device(), trt_context=None, applied_compile=True
+        )
+        self.assertEqual(pipeline.call_count, 1)
+        tensor_arg = pipeline.call_args[0][0]
+        self.assertEqual(tensor_arg.shape[0], 1)
+        self.assertEqual(tensor_arg.dtype, torch.float32)
+
+    def test_skipped_when_compile_not_applied(self):
+        pipeline = MagicMock()
+        dets = np.zeros((4, 8), dtype=np.uint8)
+        _maybe_warmup_compile(
+            pipeline, dets, self._cpu_device(), trt_context=None, applied_compile=False
+        )
+        pipeline.assert_not_called()
+
+    def test_skipped_when_trt_context_present(self):
+        pipeline = MagicMock()
+        dets = np.zeros((4, 8), dtype=np.uint8)
+        _maybe_warmup_compile(
+            pipeline, dets, self._cpu_device(), trt_context=object(), applied_compile=True
+        )
+        pipeline.assert_not_called()
+
+    def test_cuda_sync_called_on_gpu_device(self):
+        pipeline = MagicMock(return_value=torch.zeros(1))
+        dets = np.zeros((4, 8), dtype=np.uint8)
+        gpu_device = MagicMock(spec=torch.device)
+        gpu_device.type = "cuda"
+        with patch("evaluation.logical_error_rate.torch.as_tensor", return_value=torch.zeros(1)) as _mock_tensor, \
+             patch("evaluation.logical_error_rate.torch.cuda.synchronize") as mock_sync:
+            _maybe_warmup_compile(
+                pipeline, dets, gpu_device, trt_context=None, applied_compile=True
+            )
+        mock_sync.assert_called_once()
+
+    def test_cuda_sync_not_called_on_cpu_device(self):
+        pipeline = MagicMock(return_value=torch.zeros(1))
+        dets = np.zeros((4, 8), dtype=np.uint8)
+        with patch("evaluation.logical_error_rate.torch.cuda.synchronize") as mock_sync:
+            _maybe_warmup_compile(
+                pipeline, dets, self._cpu_device(), trt_context=None, applied_compile=True
+            )
+        mock_sync.assert_not_called()
+
+
 if __name__ == "__main__":
     unittest.main()