diff --git a/src/diffusers/loaders/lora_base.py b/src/diffusers/loaders/lora_base.py
index 898eae0ca36b..dc01475ac8de 100644
--- a/src/diffusers/loaders/lora_base.py
+++ b/src/diffusers/loaders/lora_base.py
@@ -277,15 +277,14 @@ def _fetch_state_dict(
 def _best_guess_weight_name(
     pretrained_model_name_or_path_or_dict, file_extension=".safetensors", local_files_only=False
 ):
-    if local_files_only or HF_HUB_OFFLINE:
-        raise ValueError("When using the offline mode, you must specify a `weight_name`.")
-
     targeted_files = []
 
     if os.path.isfile(pretrained_model_name_or_path_or_dict):
         return
     elif os.path.isdir(pretrained_model_name_or_path_or_dict):
         targeted_files = [f for f in os.listdir(pretrained_model_name_or_path_or_dict) if f.endswith(file_extension)]
+    elif local_files_only or HF_HUB_OFFLINE:
+        raise ValueError("When using the offline mode, you must specify a `weight_name`.")
     else:
         files_in_repo = model_info(pretrained_model_name_or_path_or_dict).siblings
         targeted_files = [f.rfilename for f in files_in_repo if f.rfilename.endswith(file_extension)]
diff --git a/tests/lora/test_lora_base.py b/tests/lora/test_lora_base.py
new file mode 100644
index 000000000000..7789846b8945
--- /dev/null
+++ b/tests/lora/test_lora_base.py
@@ -0,0 +1,88 @@
+# coding=utf-8
+# Copyright 2026 HuggingFace Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import os
+import tempfile
+import unittest
+from pathlib import Path
+from unittest.mock import patch
+
+import torch
+from safetensors.torch import save_file
+
+from diffusers.loaders import StableDiffusionLoraLoaderMixin
+from diffusers.loaders.lora_base import _best_guess_weight_name
+
+
+class LoraBaseBestGuessWeightNameTests(unittest.TestCase):
+    def test_local_file_with_local_files_only_returns_none(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            weight_path = Path(tmpdir) / "adapter.safetensors"
+            save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))
+
+            weight_name = _best_guess_weight_name(str(weight_path), local_files_only=True)
+            self.assertIsNone(weight_name)
+
+    def test_local_directory_with_local_files_only_discovers_weight(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            weight_path = Path(tmpdir) / "adapter.safetensors"
+            save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))
+
+            weight_name = _best_guess_weight_name(tmpdir, local_files_only=True)
+            self.assertEqual(weight_name, "adapter.safetensors")
+
+    def test_local_directory_with_hf_hub_offline_discovers_weight(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            weight_path = Path(tmpdir) / "adapter.safetensors"
+            save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))
+
+            with patch("diffusers.loaders.lora_base.HF_HUB_OFFLINE", True):
+                weight_name = _best_guess_weight_name(tmpdir)
+            self.assertEqual(weight_name, "adapter.safetensors")
+
+    def test_remote_repo_with_local_files_only_raises(self):
+        with self.assertRaises(ValueError) as cm:
+            _best_guess_weight_name("some/repo", local_files_only=True)
+        self.assertIn("offline mode", str(cm.exception).lower())
+
+
+class LoraBaseOfflineLoadingTests(unittest.TestCase):
+    def test_lora_state_dict_local_directory_with_local_files_only(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            weight_path = Path(tmpdir) / "adapter.safetensors"
+            save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))
+
+            state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(tmpdir, local_files_only=True)
+            self.assertIn("unet.test.lora_A.weight", state_dict)
+
+    def test_lora_state_dict_local_file_with_local_files_only(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            weight_path = Path(tmpdir) / "adapter.safetensors"
+            save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))
+
+            state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(str(weight_path), local_files_only=True)
+            self.assertIn("unet.test.lora_A.weight", state_dict)
+
+    @patch.dict(os.environ, {"HF_HUB_OFFLINE": "1"})
+    def test_lora_state_dict_local_directory_with_hf_hub_offline(self):
+        with tempfile.TemporaryDirectory() as tmpdir:
+            weight_path = Path(tmpdir) / "adapter.safetensors"
+            save_file({"unet.test.lora_A.weight": torch.ones(1)}, str(weight_path))
+
+            state_dict, _ = StableDiffusionLoraLoaderMixin.lora_state_dict(tmpdir)
+            self.assertIn("unet.test.lora_A.weight", state_dict)
+
+
+if __name__ == "__main__":
+    unittest.main()