From a5bc04696b187d444366a1dc64fc33c16adc09f4 Mon Sep 17 00:00:00 2001
From: Sayak Paul <spsayakpaul@gmail.com>
Date: Thu, 30 Apr 2026 15:17:04 +0530
Subject: [PATCH] NucleusMoE docs (#13661)

up
---
 docs/source/en/_toctree.yml                   |  2 ++
 .../en/api/pipelines/nucleusmoe_image.md      | 30 +++++++++++++++++++
 2 files changed, 32 insertions(+)
 create mode 100644 docs/source/en/api/pipelines/nucleusmoe_image.md

diff --git a/docs/source/en/_toctree.yml b/docs/source/en/_toctree.yml
index 1db7a7cc3e..07742fc4e8 100644
--- a/docs/source/en/_toctree.yml
+++ b/docs/source/en/_toctree.yml
@@ -580,6 +580,8 @@
         title: Lumina-T2X
       - local: api/pipelines/marigold
         title: Marigold
+      - local: api/pipelines/nucleusmoe_image
+        title: NucleusMoE-Image
       - local: api/pipelines/omnigen
         title: OmniGen
       - local: api/pipelines/ovis_image
diff --git a/docs/source/en/api/pipelines/nucleusmoe_image.md b/docs/source/en/api/pipelines/nucleusmoe_image.md
new file mode 100644
index 0000000000..ba2a820044
--- /dev/null
+++ b/docs/source/en/api/pipelines/nucleusmoe_image.md
@@ -0,0 +1,30 @@
+<!-- Copyright 2025 The HuggingFace Team. All rights reserved.
+#
+# 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. -->
+
+# NucleusMoE-Image
+
+[NucleusMoE-Image](https://huggingface.co/NucleusAI/NucleusMoE-Image) is a text-to-image model that pairs a single-stream DiT with Mixture-of-Experts feed-forward layers, cross-attention to a Qwen3-VL text encoder, and a flow-matching Euler discrete scheduler.
+
+> [!TIP]
+> Make sure to check out the Schedulers [guide](../../using-diffusers/schedulers) to learn how to explore the tradeoff between scheduler speed and quality, and see the [reuse components across pipelines](../../using-diffusers/loading#reuse-a-pipeline) section to learn how to efficiently load the same components into multiple pipelines.
+
+## NucleusMoEImagePipeline
+
+[[autodoc]] NucleusMoEImagePipeline
+  - all
+  - __call__
+
+## NucleusMoEImagePipelineOutput
+
+[[autodoc]] pipelines.nucleusmoe_image.pipeline_output.NucleusMoEImagePipelineOutput