diff --git a/vllm/config/load.py b/vllm/config/load.py
index e4999e36b49bf..68253359fc567 100644
--- a/vllm/config/load.py
+++ b/vllm/config/load.py
@@ -51,6 +51,15 @@ class LoadConfig:
     download_dir: Optional[str] = None
     """Directory to download and load the weights, default to the default
     cache directory of Hugging Face."""
+    safetensors_load_strategy: Optional[str] = "lazy"
+    """Specifies the loading strategy for safetensors weights.
+    - "lazy" (default): Weights are memory-mapped from the file. This enables
+      on-demand loading and is highly efficient for models on local storage.
+    - "eager": The entire file is read into CPU memory upfront before loading.
+      This is recommended for models on network filesystems (e.g., Lustre, NFS)
+      as it avoids inefficient random reads, significantly speeding up model
+      initialization. However, it uses more CPU RAM.
+    """
     model_loader_extra_config: Union[dict, TensorizerConfig] = field(
         default_factory=dict)
     """Extra config for model loader. This will be passed to the model loader
diff --git a/vllm/engine/arg_utils.py b/vllm/engine/arg_utils.py
index 87d90f5147cd8..d9a29511eb529 100644
--- a/vllm/engine/arg_utils.py
+++ b/vllm/engine/arg_utils.py
@@ -289,6 +289,8 @@ class EngineArgs:
     trust_remote_code: bool = ModelConfig.trust_remote_code
     allowed_local_media_path: str = ModelConfig.allowed_local_media_path
     download_dir: Optional[str] = LoadConfig.download_dir
+    safetensors_load_strategy: Optional[
+        str] = LoadConfig.safetensors_load_strategy
     load_format: Union[str, LoadFormats] = LoadConfig.load_format
     config_format: str = ModelConfig.config_format
     dtype: ModelDType = ModelConfig.dtype
@@ -587,6 +589,8 @@ class EngineArgs:
         load_group.add_argument("--load-format", **load_kwargs["load_format"])
         load_group.add_argument("--download-dir",
                                 **load_kwargs["download_dir"])
+        load_group.add_argument("--safetensors-load-strategy",
+                                **load_kwargs["safetensors_load_strategy"])
         load_group.add_argument("--model-loader-extra-config",
                                 **load_kwargs["model_loader_extra_config"])
         load_group.add_argument("--ignore-patterns",
@@ -1023,6 +1027,7 @@ class EngineArgs:
         return LoadConfig(
             load_format=self.load_format,
             download_dir=self.download_dir,
+            safetensors_load_strategy=self.safetensors_load_strategy,
             device="cpu"
             if is_online_quantization(self.quantization) else None,
             model_loader_extra_config=self.model_loader_extra_config,
diff --git a/vllm/model_executor/model_loader/default_loader.py b/vllm/model_executor/model_loader/default_loader.py
index f883e1e739102..d1bdec21fd974 100644
--- a/vllm/model_executor/model_loader/default_loader.py
+++ b/vllm/model_executor/model_loader/default_loader.py
@@ -189,6 +189,7 @@ class DefaultModelLoader(BaseModelLoader):
                     weights_iterator = safetensors_weights_iterator(
                         hf_weights_files,
                         self.load_config.use_tqdm_on_load,
+                        self.load_config.safetensors_load_strategy,
                     )
         else:
             if extra_config.get("enable_multithread_load"):
diff --git a/vllm/model_executor/model_loader/weight_utils.py b/vllm/model_executor/model_loader/weight_utils.py
index 0de8dbbca9c7f..c6ca9cd48d009 100644
--- a/vllm/model_executor/model_loader/weight_utils.py
+++ b/vllm/model_executor/model_loader/weight_utils.py
@@ -19,7 +19,7 @@ import huggingface_hub.constants
 import numpy as np
 import torch
 from huggingface_hub import HfFileSystem, hf_hub_download, snapshot_download
-from safetensors.torch import load_file, safe_open, save_file
+from safetensors.torch import load, load_file, safe_open, save_file
 from tqdm.auto import tqdm
 
 from vllm import envs
@@ -519,18 +519,28 @@ def np_cache_weights_iterator(
 def safetensors_weights_iterator(
     hf_weights_files: list[str],
     use_tqdm_on_load: bool,
+    safetensors_load_strategy: Optional[str] = "lazy",
 ) -> Generator[tuple[str, torch.Tensor], None, None]:
     """Iterate over the weights in the model safetensor files."""
+    loading_desc = "Loading safetensors checkpoint shards"
+    if safetensors_load_strategy == "eager":
+        loading_desc += " (eager)"
+
     for st_file in tqdm(
             hf_weights_files,
-            desc="Loading safetensors checkpoint shards",
+            desc=loading_desc,
             disable=not enable_tqdm(use_tqdm_on_load),
             bar_format=_BAR_FORMAT,
     ):
-        with safe_open(st_file, framework="pt") as f:
-            for name in f.keys():  # noqa: SIM118
-                param = f.get_tensor(name)
-                yield name, param
+        if safetensors_load_strategy == "eager":
+            with open(st_file, "rb") as f:
+                state_dict = load(f.read())
+            yield from state_dict.items()
+        else:
+            with safe_open(st_file, framework="pt") as f:
+                for name in f.keys():  # noqa: SIM118
+                    param = f.get_tensor(name)
+                    yield name, param
 
 
 def multi_thread_safetensors_weights_iterator(