diff --git a/tests/entrypoints/offline_mode/test_offline_mode.py b/tests/entrypoints/offline_mode/test_offline_mode.py
index a606eeab5887..dd8d63ad319a 100644
--- a/tests/entrypoints/offline_mode/test_offline_mode.py
+++ b/tests/entrypoints/offline_mode/test_offline_mode.py
@@ -1,6 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 """Tests for HF_HUB_OFFLINE mode"""
+import dataclasses
 import importlib
 import sys
 
@@ -9,6 +10,7 @@ import urllib3
 
 from vllm import LLM
 from vllm.distributed import cleanup_dist_env_and_memory
+from vllm.engine.arg_utils import EngineArgs
 
 MODEL_CONFIGS = [
     {
@@ -108,3 +110,36 @@ def _re_import_modules():
     # Error this test if reloading a module failed
     if reload_exception is not None:
         raise reload_exception
+
+
+@pytest.mark.skip_global_cleanup
+@pytest.mark.usefixtures("cache_models")
+def test_model_from_huggingface_offline(monkeypatch: pytest.MonkeyPatch):
+    # Set HF to offline mode and ensure we can still construct an LLM
+    with monkeypatch.context() as m:
+        try:
+            m.setenv("HF_HUB_OFFLINE", "1")
+            m.setenv("VLLM_NO_USAGE_STATS", "1")
+
+            def disable_connect(*args, **kwargs):
+                raise RuntimeError("No http calls allowed")
+
+            m.setattr(
+                urllib3.connection.HTTPConnection,
+                "connect",
+                disable_connect,
+            )
+            m.setattr(
+                urllib3.connection.HTTPSConnection,
+                "connect",
+                disable_connect,
+            )
+            # Need to re-import huggingface_hub
+            # and friends to setup offline mode
+            _re_import_modules()
+            engine_args = EngineArgs(model="facebook/opt-125m")
+            LLM(**dataclasses.asdict(engine_args))
+        finally:
+            # Reset the environment after the test
+            # NB: Assuming tests are run in online mode
+            _re_import_modules()
diff --git a/vllm/engine/arg_utils.py b/vllm/engine/arg_utils.py
index 679905aed9ec..48d9cd08af03 100644
--- a/vllm/engine/arg_utils.py
+++ b/vllm/engine/arg_utils.py
@@ -15,6 +15,7 @@ from typing import (TYPE_CHECKING, Annotated, Any, Callable, Dict, List,
                     Literal, Optional, Type, TypeVar, Union, cast, get_args,
                     get_origin)
 
+import huggingface_hub
 import regex as re
 import torch
 from pydantic import TypeAdapter, ValidationError
@@ -39,7 +40,7 @@ from vllm.plugins import load_general_plugins
 from vllm.ray.lazy_utils import is_ray_initialized
 from vllm.reasoning import ReasoningParserManager
 from vllm.test_utils import MODEL_WEIGHTS_S3_BUCKET, MODELS_ON_S3
-from vllm.transformers_utils.config import is_interleaved
+from vllm.transformers_utils.config import get_model_path, is_interleaved
 from vllm.transformers_utils.utils import check_gguf_file
 from vllm.utils import (STR_DUAL_CHUNK_FLASH_ATTN_VAL, FlexibleArgumentParser,
                         GiB_bytes, get_ip, is_in_ray_actor)
@@ -457,6 +458,13 @@ class EngineArgs:
         # Setup plugins
         from vllm.plugins import load_general_plugins
         load_general_plugins()
+        # when use hf offline,replace model id to local model path
+        if huggingface_hub.constants.HF_HUB_OFFLINE:
+            model_id = self.model
+            self.model = get_model_path(self.model, self.revision)
+            logger.info(
+                "HF_HUB_OFFLINE is True, replace model_id [%s] " \
+                "to model_path [%s]",model_id, self.model)
 
     @staticmethod
     def add_cli_args(parser: FlexibleArgumentParser) -> FlexibleArgumentParser:
diff --git a/vllm/transformers_utils/config.py b/vllm/transformers_utils/config.py
index d8c964fb2a4a..fe345bd8f0a2 100644
--- a/vllm/transformers_utils/config.py
+++ b/vllm/transformers_utils/config.py
@@ -14,7 +14,7 @@ from huggingface_hub import get_safetensors_metadata, hf_hub_download
 from huggingface_hub import list_repo_files as hf_list_repo_files
 from huggingface_hub import try_to_load_from_cache
 from huggingface_hub.utils import (EntryNotFoundError, HfHubHTTPError,
-                                   HFValidationError, LocalEntryNotFoundError,
+                                   LocalEntryNotFoundError,
                                    RepositoryNotFoundError,
                                    RevisionNotFoundError)
 from transformers import GenerationConfig, PretrainedConfig
@@ -335,6 +335,7 @@ def maybe_override_with_speculators_target_model(
         gguf_model_repo = Path(model).parent
     else:
         gguf_model_repo = None
+    kwargs["local_files_only"] = huggingface_hub.constants.HF_HUB_OFFLINE
     config_dict, _ = PretrainedConfig.get_config_dict(
         model if gguf_model_repo is None else gguf_model_repo,
         revision=revision,
@@ -400,6 +401,7 @@ def get_config(
             raise ValueError(error_message) from e
 
     if config_format == ConfigFormat.HF:
+        kwargs["local_files_only"] = huggingface_hub.constants.HF_HUB_OFFLINE
         config_dict, _ = PretrainedConfig.get_config_dict(
             model,
             revision=revision,
@@ -532,7 +534,7 @@ def try_get_local_file(model: Union[str, Path],
                                                      revision=revision)
             if isinstance(cached_filepath, str):
                 return Path(cached_filepath)
-        except HFValidationError:
+        except ValueError:
             ...
     return None
 
@@ -908,3 +910,20 @@ def _maybe_retrieve_max_pos_from_hf(model, revision, **kwargs) -> int:
             exc_info=e)
 
     return max_position_embeddings
+
+
+def get_model_path(model: Union[str, Path], revision: Optional[str] = None):
+    if os.path.exists(model):
+        return model
+    assert huggingface_hub.constants.HF_HUB_OFFLINE
+    common_kwargs = {
+        "local_files_only": huggingface_hub.constants.HF_HUB_OFFLINE,
+        "revision": revision,
+    }
+
+    if envs.VLLM_USE_MODELSCOPE:
+        from modelscope.hub.snapshot_download import snapshot_download
+        return snapshot_download(model_id=model, **common_kwargs)
+
+    from huggingface_hub import snapshot_download
+    return snapshot_download(repo_id=model, **common_kwargs)