diff --git a/jax_privacy/experimental/training.py b/jax_privacy/experimental/training.py
index dd95f96b..8cca4eee 100644
--- a/jax_privacy/experimental/training.py
+++ b/jax_privacy/experimental/training.py
@@ -135,7 +135,8 @@ class DPTrainer:
     optimizer: An ``AugmentedGradientTransformation`` or a plain
       ``optax.GradientTransformation``.
     padding_multiple: If set, batch sizes are padded to a multiple of this
-      value.
+      value. Padding reduces JIT recompilations from variable Poisson batch
+      sizes, since each unique batch shape triggers a separate XLA compilation.
   """
 
   plan: execution_plan.DPExecutionPlan
@@ -144,7 +145,7 @@ class DPTrainer:
       aug_optimizers.AugmentedGradientTransformation
       | optax.GradientTransformation
   )
-  padding_multiple: int = 1
+  padding_multiple: int = 32
 
   def train_step(
       self,
diff --git a/tests/experimental/training_test.py b/tests/experimental/training_test.py
index 6d18fa4d..aaf0956c 100644
--- a/tests/experimental/training_test.py
+++ b/tests/experimental/training_test.py
@@ -126,6 +126,16 @@ def test_padding_multiple(self):
 
     self.assertEqual(int(state.step), 2)
 
+  def test_default_padding_multiple(self):
+    """Default padding_multiple should be 32 to prevent JIT recompilation."""
+    plan = _make_plan(iterations=1)
+    trainer = training.DPTrainer(
+        plan=plan,
+        loss_fn=_quadratic_loss,
+        optimizer=optax.sgd(0.01),
+    )
+    self.assertEqual(trainer.padding_multiple, 32)
+
   def test_zero_iterations_config_raises(self):
     """BandMFConfig requires iterations >= 1."""
     with self.assertRaises(Exception):