diff --git a/src/refiners/foundationals/latent_diffusion/__init__.py b/src/refiners/foundationals/latent_diffusion/__init__.py
index b301aac..42bdaf8 100644
--- a/src/refiners/foundationals/latent_diffusion/__init__.py
+++ b/src/refiners/foundationals/latent_diffusion/__init__.py
@@ -4,6 +4,7 @@ from refiners.foundationals.latent_diffusion.auto_encoder import (
 from refiners.foundationals.clip.text_encoder import (
     CLIPTextEncoderL,
 )
+from refiners.foundationals.latent_diffusion.freeu import SDFreeUAdapter
 from refiners.foundationals.latent_diffusion.schedulers import Scheduler, DPMSolver
 from refiners.foundationals.latent_diffusion.stable_diffusion_1 import (
     StableDiffusion_1,
@@ -36,4 +37,5 @@ __all__ = [
     "Scheduler",
     "CLIPTextEncoderL",
     "LatentDiffusionAutoencoder",
+    "SDFreeUAdapter",
 ]
diff --git a/tests/e2e/test_diffusion.py b/tests/e2e/test_diffusion.py
index fca8dfa..3ef40d3 100644
--- a/tests/e2e/test_diffusion.py
+++ b/tests/e2e/test_diffusion.py
@@ -17,6 +17,7 @@ from refiners.foundationals.latent_diffusion import (
     SD1T2IAdapter,
     SDXLIPAdapter,
     SDXLT2IAdapter,
+    SDFreeUAdapter,
 )
 from refiners.foundationals.latent_diffusion.lora import SD1LoraAdapter
 from refiners.foundationals.latent_diffusion.multi_diffusion import DiffusionTarget
@@ -227,6 +228,11 @@ def expected_restart(ref_path: Path) -> Image.Image:
     return Image.open(fp=ref_path / "expected_restart.png").convert(mode="RGB")
 
 
+@pytest.fixture
+def expected_freeu(ref_path: Path) -> Image.Image:
+    return Image.open(fp=ref_path / "expected_freeu.png").convert(mode="RGB")
+
+
 @pytest.fixture
 def text_embedding_textual_inversion(test_textual_inversion_path: Path) -> torch.Tensor:
     return torch.load(test_textual_inversion_path / "gta5-artwork" / "learned_embeds.bin")["<gta5-artwork>"]  # type: ignore
@@ -1604,3 +1610,37 @@ def test_restart(
     predicted_image = sd15.lda.decode_latents(x)
 
     ensure_similar_images(predicted_image, expected_restart, min_psnr=35, min_ssim=0.98)
+
+
+@torch.no_grad()
+def test_freeu(
+    sd15_std: StableDiffusion_1,
+    expected_freeu: Image.Image,
+):
+    sd15 = sd15_std
+    n_steps = 50
+    first_step = 1
+
+    prompt = "best quality, high quality cute cat"
+    negative_prompt = "monochrome, lowres, bad anatomy, worst quality, low quality"
+    clip_text_embedding = sd15.compute_clip_text_embedding(text=prompt, negative_text=negative_prompt)
+
+    sd15.set_num_inference_steps(n_steps)
+
+    SDFreeUAdapter(
+        sd15.unet, backbone_scales=[1.2, 1.2, 1.2, 1.4, 1.4, 1.4], skip_scales=[0.9, 0.9, 0.9, 0.2, 0.2, 0.2]
+    ).inject()
+
+    manual_seed(9752)
+    x = sd15.init_latents(size=(512, 512), first_step=first_step).to(device=sd15.device, dtype=sd15.dtype)
+
+    for step in sd15.steps[first_step:]:
+        x = sd15(
+            x,
+            step=step,
+            clip_text_embedding=clip_text_embedding,
+            condition_scale=7.5,
+        )
+    predicted_image = sd15.lda.decode_latents(x)
+
+    ensure_similar_images(predicted_image, expected_freeu)
diff --git a/tests/e2e/test_diffusion_ref/README.md b/tests/e2e/test_diffusion_ref/README.md
index 62cf504..2402be5 100644
--- a/tests/e2e/test_diffusion_ref/README.md
+++ b/tests/e2e/test_diffusion_ref/README.md
@@ -45,6 +45,7 @@ Special cases:
     - `expected_image_sdxl_ip_adapter_plus_woman.png`
     - `expected_cutecat_sdxl_ddim_random_init_sag.png`
     - `expected_restart.png`
+    - `expected_freeu.png`
 
 ## Other images
 
diff --git a/tests/e2e/test_diffusion_ref/expected_freeu.png b/tests/e2e/test_diffusion_ref/expected_freeu.png
new file mode 100644
index 0000000..01efceb
Binary files /dev/null and b/tests/e2e/test_diffusion_ref/expected_freeu.png differ
diff --git a/tests/foundationals/latent_diffusion/test_freeu.py b/tests/foundationals/latent_diffusion/test_freeu.py
new file mode 100644
index 0000000..786cfe3
--- /dev/null
+++ b/tests/foundationals/latent_diffusion/test_freeu.py
@@ -0,0 +1,41 @@
+from typing import Iterator
+
+import pytest
+
+from refiners.foundationals.latent_diffusion import SD1UNet, SDXLUNet
+from refiners.foundationals.latent_diffusion.freeu import SDFreeUAdapter, FreeUResidualConcatenator
+
+
+@pytest.fixture(scope="module", params=[True, False])
+def unet(request: pytest.FixtureRequest) -> Iterator[SD1UNet | SDXLUNet]:
+    xl: bool = request.param
+    unet = SDXLUNet(in_channels=4) if xl else SD1UNet(in_channels=4)
+    yield unet
+
+
+def test_freeu_adapter(unet: SD1UNet | SDXLUNet) -> None:
+    freeu = SDFreeUAdapter(unet, backbone_scales=[1.2, 1.2], skip_scales=[0.9, 0.9])
+
+    assert len(list(unet.walk(FreeUResidualConcatenator))) == 0
+
+    with pytest.raises(AssertionError) as exc:
+        freeu.eject()
+    assert "could not find" in str(exc.value)
+
+    freeu.inject()
+    assert len(list(unet.walk(FreeUResidualConcatenator))) == 2
+
+    freeu.eject()
+    assert len(list(unet.walk(FreeUResidualConcatenator))) == 0
+
+
+def test_freeu_adapter_too_many_scales(unet: SD1UNet | SDXLUNet) -> None:
+    num_blocks = len(unet.UpBlocks)
+
+    with pytest.raises(AssertionError):
+        SDFreeUAdapter(unet, backbone_scales=[1.2] * (num_blocks + 1), skip_scales=[0.9] * (num_blocks + 1))
+
+
+def test_freeu_adapter_inconsistent_scales(unet: SD1UNet | SDXLUNet) -> None:
+    with pytest.raises(AssertionError):
+        SDFreeUAdapter(unet, backbone_scales=[1.2, 1.2], skip_scales=[0.9, 0.9, 0.9])