diff --git a/keras_rs/src/layers/embedding/jax/distributed_embedding.py b/keras_rs/src/layers/embedding/jax/distributed_embedding.py
index 1f5916fa..bd69a0be 100644
--- a/keras_rs/src/layers/embedding/jax/distributed_embedding.py
+++ b/keras_rs/src/layers/embedding/jax/distributed_embedding.py
@@ -9,6 +9,7 @@
 import numpy as np
 from jax import numpy as jnp
 from jax.experimental import layout as jax_layout
+from jax.experimental import multihost_utils
 from jax_tpu_embedding.sparsecore.lib.nn import embedding
 from jax_tpu_embedding.sparsecore.lib.nn import embedding_spec
 from jax_tpu_embedding.sparsecore.lib.nn import (
@@ -600,31 +601,26 @@ def _sparsecore_preprocess(
             # underlying stacked tables specs in the feature specs.
 
             # Aggregate stats across all processes/devices via pmax.
-            num_local_cpu_devices = jax.local_device_count("cpu")
-
-            def pmax_aggregate(x: Any) -> Any:
-                if not hasattr(x, "ndim"):
-                    x = np.array(x)
-                tiled_x = np.tile(x, (num_local_cpu_devices, *([1] * x.ndim)))
-                return jax.pmap(
-                    lambda y: jax.lax.pmax(y, "all_cpus"),  # type: ignore[no-untyped-call]
-                    axis_name="all_cpus",
-                    backend="cpu",
-                )(tiled_x)[0]
-
-            full_stats = jax.tree.map(pmax_aggregate, stats)
+            all_stats = multihost_utils.process_allgather(stats)
+            aggregated_stats = jax.tree.map(
+                lambda x: jnp.max(x, axis=0), all_stats
+            )
 
             # Check if stats changed enough to warrant action.
             stacked_table_specs = embedding.get_stacked_table_specs(
                 self._config.feature_specs
             )
             changed = any(
-                np.max(full_stats.max_ids_per_partition[stack_name])
+                np.max(aggregated_stats.max_ids_per_partition[stack_name])
                 > spec.max_ids_per_partition
-                or np.max(full_stats.max_unique_ids_per_partition[stack_name])
+                or np.max(
+                    aggregated_stats.max_unique_ids_per_partition[stack_name]
+                )
                 > spec.max_unique_ids_per_partition
                 or (
-                    np.max(full_stats.required_buffer_size_per_sc[stack_name])
+                    np.max(
+                        aggregated_stats.required_buffer_size_per_sc[stack_name]
+                    )
                     * num_sc_per_device
                 )
                 > (spec.suggested_coo_buffer_size_per_device or 0)
@@ -634,7 +630,9 @@ def pmax_aggregate(x: Any) -> Any:
             # Update configuration and repeat preprocessing if stats changed.
             if changed:
                 embedding.update_preprocessing_parameters(
-                    self._config.feature_specs, full_stats, num_sc_per_device
+                    self._config.feature_specs,
+                    aggregated_stats,
+                    num_sc_per_device,
                 )
 
                 # Re-execute preprocessing with consistent input statistics.