diff --git a/checkpoint/orbax/checkpoint/experimental/v1/_src/layout/safetensors_layout.py b/checkpoint/orbax/checkpoint/experimental/v1/_src/layout/safetensors_layout.py
index 693c4dec9..574e2a05b 100644
--- a/checkpoint/orbax/checkpoint/experimental/v1/_src/layout/safetensors_layout.py
+++ b/checkpoint/orbax/checkpoint/experimental/v1/_src/layout/safetensors_layout.py
@@ -556,11 +556,11 @@ async def load_multi_host(
         restored_pytree[name] = _build_array_on_single_device(info, owner, ctx)
       else:
         global_transient_array = _build_transient_array(name, info, owner, ctx)
-        t0 = time.time()
-        restored_pytree[name] = _reshard_transient_array(
-            global_transient_array, target_sharding, global_mesh
-        )
-        reshard_time += time.time() - t0
+        restored_pytree[name] = {
+            "transient_array": global_transient_array, 
+            "target_sharding": target_sharding,
+            "global_mesh": global_mesh,
+        }
 
     return restored_pytree, {"io_time": io_time, "reshard_time": reshard_time}
 
@@ -631,28 +631,42 @@ async def _load_multi_host(
 
     loaders = await self._get_loaders()
 
-    # Call load_multi_host on each loader concurrently.
+    # Phase 1: Call load_multi_host on each loader concurrently for parallel IO.
     # Each loader handles loading from a single file.
     start = time.time()
     load_ops = []
     for loader in loaders:
       load_ops.append(loader.load_multi_host(abstract_state))
 
-    restored_pytree = {}
+    restored_pytree_partial = {}
     total_io_time = 0.0
-    total_reshard_time = 0.0
     for file_tensors, metrics in await asyncio.gather(*load_ops):
       total_io_time += metrics["io_time"]
-      total_reshard_time += metrics["reshard_time"]
-      for name, arr in file_tensors.items():
-        if name in restored_pytree:
+      for name, arr_dict in file_tensors.items():
+        if name in restored_pytree_partial:
           raise ValueError(f"Duplicate tensor {name} found in multiple files.")
-        restored_pytree[name] = arr
+        restored_pytree_partial[name] = arr_dict
 
-    # Validate that all requested tensors were found in at least one file.
-    for k in abstract_state:
-      if k not in restored_pytree:
+    restored_pytree = {}
+    total_reshard_time = 0.0
+
+    # Phase 2: Process JAX collectives completely sequentially!
+    # To ensure exact uniform ordering across all hosts to prevent deadlock, we
+    # iterate deterministically.
+    for k in sorted(abstract_state.keys()):
+      if k not in restored_pytree_partial:
         raise KeyError(f"Tensor '{k}' not found in Safetensors checkpoint.")
+      item = restored_pytree_partial[k]
+      if context_lib.get_context().safetensors_options.ignore_load_sharding:
+        restored_pytree[k] = item
+      else:
+        t0 = time.time()
+        restored_pytree[k] = _reshard_transient_array(
+            item["transient_array"],
+            item["target_sharding"],
+            item["global_mesh"],
+        )
+        total_reshard_time += time.time() - t0
 
     logging.info(
         "[safetensors][multi-host] Loaded and resharded %d tensors from %d"