diff --git a/tests/diffusion/models/qwen_image/test_qwen_image_pipeline_device.py b/tests/diffusion/models/qwen_image/test_qwen_image_pipeline_device.py
index 7f0ce51c8dc..c65fb1731db 100644
--- a/tests/diffusion/models/qwen_image/test_qwen_image_pipeline_device.py
+++ b/tests/diffusion/models/qwen_image/test_qwen_image_pipeline_device.py
@@ -64,7 +64,7 @@ def temperal_downsample(self):
         return [True, True, True]
 
 
-def _run_pipeline_init(monkeypatch, *, enable_cpu_offload, loader_device):
+def _run_pipeline_init(monkeypatch, *, enable_cpu_offload, loader_device, diffusion_offload_config=None):
     import vllm_omni.diffusion.models.qwen_image.pipeline_qwen_image as pipe_mod
     from vllm_omni.diffusion.models.qwen_image.pipeline_qwen_image import QwenImagePipeline
 
@@ -110,6 +110,7 @@ def _prefetch(factory, *args, **kwargs):
         tf_model_config={},
         quantization_config=None,
         enable_cpu_offload=enable_cpu_offload,
+        diffusion_offload_config=diffusion_offload_config,
         enable_diffusion_pipeline_profiler=False,
     )
     return QwenImagePipeline(od_config=od_config)
@@ -129,3 +130,19 @@ def test_pipeline_dit_follows_loader_cpu_without_override(monkeypatch):
     assert pipe.transformer.probe_device_type == "cpu"
     assert pipe.text_encoder.placed_device.type == "cuda"
     assert pipe.vae.placed_device.type == "cuda"
+
+
+@pytest.mark.parametrize(
+    ("mode", "loader_device", "expected_device"),
+    [("module", "cuda", "cpu"), ("layer", "cpu", "cuda")],
+)
+def test_pipeline_compact_offload_places_encoder_vae(monkeypatch, mode, loader_device, expected_device):
+    pipe = _run_pipeline_init(
+        monkeypatch,
+        enable_cpu_offload=False,
+        loader_device=loader_device,
+        diffusion_offload_config={"mode": mode, "components": ["dit"]},
+    )
+    assert pipe.text_encoder.placed_device.type == expected_device
+    assert pipe.vae.placed_device.type == expected_device
+    assert pipe.transformer.probe_device_type == loader_device
diff --git a/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image.py b/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image.py
index 5e262ff1e01..6d7a2a7d359 100644
--- a/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image.py
+++ b/vllm_omni/diffusion/models/qwen_image/pipeline_qwen_image.py
@@ -37,6 +37,7 @@
     QwenImageTransformer2DModel,
 )
 from vllm_omni.diffusion.models.qwen_image.rope_utils import txt_seq_lens_from_embeds
+from vllm_omni.diffusion.offloader.config import OffloadStrategy, resolve_offload_strategy
 from vllm_omni.diffusion.profiler.diffusion_pipeline_profiler import DiffusionPipelineProfilerMixin
 from vllm_omni.diffusion.utils.prompt_utils import (
     validate_prompt_sequence_lengths,
@@ -341,7 +342,7 @@ def __init__(
         # do not share VRAM with DiT construction (#7555). The DiT follows the
         # loader's default-device context (CUDA for online / AutoRound INT under
         # offload, CPU for layerwise / unquantized HSDP defer).
-        cpu_offload = bool(getattr(self.od_config, "enable_cpu_offload", False))
+        cpu_offload = resolve_offload_strategy(self.od_config) is OffloadStrategy.MODEL_LEVEL
         enc_vae_device = torch.device("cpu") if cpu_offload else self.device
         self.text_encoder = self.text_encoder.to(enc_vae_device)
         self.vae = from_pretrained_with_prefetch(