diff --git a/tests/lora/test_lora_layers_wan.py b/tests/lora/test_lora_layers_wan.py
deleted file mode 100644
index c1077d509238..000000000000
--- a/tests/lora/test_lora_layers_wan.py
+++ /dev/null
@@ -1,112 +0,0 @@
-# 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 sys
-import unittest
-
-import torch
-from transformers import AutoTokenizer, T5EncoderModel
-
-from diffusers import AutoencoderKLWan, FlowMatchEulerDiscreteScheduler, WanPipeline, WanTransformer3DModel
-
-from ..testing_utils import floats_tensor, require_peft_backend, skip_mps
-
-
-sys.path.append(".")
-
-from .utils import PeftLoraLoaderMixinTests  # noqa: E402
-
-
-@require_peft_backend
-@skip_mps
-class WanLoRATests(unittest.TestCase, PeftLoraLoaderMixinTests):
-    pipeline_class = WanPipeline
-    scheduler_cls = FlowMatchEulerDiscreteScheduler
-    scheduler_kwargs = {}
-
-    transformer_kwargs = {
-        "patch_size": (1, 2, 2),
-        "num_attention_heads": 2,
-        "attention_head_dim": 12,
-        "in_channels": 16,
-        "out_channels": 16,
-        "text_dim": 32,
-        "freq_dim": 256,
-        "ffn_dim": 32,
-        "num_layers": 2,
-        "cross_attn_norm": True,
-        "qk_norm": "rms_norm_across_heads",
-        "rope_max_seq_len": 32,
-    }
-    transformer_cls = WanTransformer3DModel
-    vae_kwargs = {
-        "base_dim": 3,
-        "z_dim": 16,
-        "dim_mult": [1, 1, 1, 1],
-        "num_res_blocks": 1,
-        "temperal_downsample": [False, True, True],
-    }
-    vae_cls = AutoencoderKLWan
-    has_two_text_encoders = True
-    tokenizer_cls, tokenizer_id = AutoTokenizer, "hf-internal-testing/tiny-random-t5"
-    text_encoder_cls, text_encoder_id = T5EncoderModel, "hf-internal-testing/tiny-random-t5"
-
-    text_encoder_target_modules = ["q", "k", "v", "o"]
-
-    supports_text_encoder_loras = False
-
-    @property
-    def output_shape(self):
-        return (1, 9, 32, 32, 3)
-
-    def get_dummy_inputs(self, with_generator=True):
-        batch_size = 1
-        sequence_length = 16
-        num_channels = 4
-        num_frames = 9
-        num_latent_frames = 3  # (num_frames - 1) // temporal_compression_ratio + 1
-        sizes = (4, 4)
-
-        generator = torch.manual_seed(0)
-        noise = floats_tensor((batch_size, num_latent_frames, num_channels) + sizes)
-        input_ids = torch.randint(1, sequence_length, size=(batch_size, sequence_length), generator=generator)
-
-        pipeline_inputs = {
-            "prompt": "",
-            "num_frames": num_frames,
-            "num_inference_steps": 1,
-            "guidance_scale": 6.0,
-            "height": 32,
-            "width": 32,
-            "max_sequence_length": sequence_length,
-            "output_type": "np",
-        }
-        if with_generator:
-            pipeline_inputs.update({"generator": generator})
-
-        return noise, input_ids, pipeline_inputs
-
-    def test_simple_inference_with_text_lora_denoiser_fused_multi(self):
-        super().test_simple_inference_with_text_lora_denoiser_fused_multi(expected_atol=9e-3)
-
-    def test_simple_inference_with_text_denoiser_lora_unfused(self):
-        super().test_simple_inference_with_text_denoiser_lora_unfused(expected_atol=9e-3)
-
-    @unittest.skip("Not supported in Wan.")
-    def test_simple_inference_with_text_denoiser_block_scale(self):
-        pass
-
-    @unittest.skip("Not supported in Wan.")
-    def test_simple_inference_with_text_denoiser_block_scale_for_all_dict_options(self):
-        pass
diff --git a/tests/pipelines/wan/test_wan.py b/tests/pipelines/wan/test_wan.py
index de4d1a6654b1..4f5e819bf92b 100644
--- a/tests/pipelines/wan/test_wan.py
+++ b/tests/pipelines/wan/test_wan.py
@@ -19,7 +19,13 @@
 from diffusers import AutoencoderKLWan, FlowMatchEulerDiscreteScheduler, WanPipeline, WanTransformer3DModel
 
 from ...testing_utils import assert_tensors_close, torch_device
-from ..testing_utils import BasePipelineTesterConfig, MemoryTesterMixin, PipelineTesterMixin
+from ..testing_utils import (
+    BasePipelineTesterConfig,
+    LoraMemoryTesterMixin,
+    LoraTesterMixin,
+    MemoryTesterMixin,
+    PipelineTesterMixin,
+)
 
 
 class WanPipelineTesterConfig(BasePipelineTesterConfig):
@@ -142,3 +148,11 @@ def test_save_load_optional_components(self, tmp_path, expected_max_difference=1
 
 class TestWanPipelineMemory(WanPipelineTesterConfig, MemoryTesterMixin):
     pass
+
+
+class TestWanPipelineLoRA(WanPipelineTesterConfig, LoraTesterMixin):
+    """LoRA tests for the Wan pipeline."""
+
+
+class TestWanPipelineLoRAMemory(WanPipelineTesterConfig, LoraMemoryTesterMixin):
+    """LoRA offloading tests for the Wan pipeline."""