diff --git a/vllm_ascend/patch/worker/__init__.py b/vllm_ascend/patch/worker/__init__.py
index faa57b61..9e37f1ec 100644
--- a/vllm_ascend/patch/worker/__init__.py
+++ b/vllm_ascend/patch/worker/__init__.py
@@ -28,4 +28,5 @@ import vllm_ascend.patch.worker.patch_weight_loader  # noqa
 import vllm_ascend.patch.worker.patch_multimodal_merge  # noqa
 import vllm_ascend.patch.worker.patch_minicpm  # noqa
 import vllm_ascend.patch.worker.patch_qwen2_5_vl  # noqa
+import vllm_ascend.patch.worker.patch_qwen2_5_omni  # noqa
 import vllm_ascend.patch.worker.patch_rope  # noqa
diff --git a/vllm_ascend/patch/worker/patch_qwen2_5_omni.py b/vllm_ascend/patch/worker/patch_qwen2_5_omni.py
new file mode 100644
index 00000000..bd91a33e
--- /dev/null
+++ b/vllm_ascend/patch/worker/patch_qwen2_5_omni.py
@@ -0,0 +1,72 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# This file is a part of the vllm-ascend project.
+#
+# 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 torch
+import torch.nn as nn
+from vllm.model_executor.models.qwen2_5_omni_thinker import (
+    Qwen2_5_VLImageInputs, Qwen2_5_VLVideoInputs,
+    Qwen2_5OmniThinkerForConditionalGeneration)
+
+from vllm_ascend.ascend_forward_context import set_ascend_forward_context
+
+
+class AscendQwen2_5OmniThinkerForConditionalGeneration(nn.Module):
+
+    def _process_image_input(
+            self,
+            image_input: Qwen2_5_VLImageInputs) -> tuple[torch.Tensor, ...]:
+        if image_input["type"] == "image_embeds":
+            return image_input["image_embeds"].type(self.visual.dtype)
+
+        grid_thw = image_input["image_grid_thw"]
+        assert grid_thw.ndim == 2
+
+        pixel_values = image_input["pixel_values"].type(self.visual.dtype)
+        with set_ascend_forward_context(None, self.vllm_config):
+            image_embeds = self.visual(pixel_values, grid_thw=grid_thw)
+        # Split concatenated embeddings for each image item.
+        merge_size = self.visual.spatial_merge_size
+        sizes = grid_thw.prod(-1) // merge_size // merge_size
+
+        return image_embeds.split(sizes.tolist())
+
+    def _process_video_input(
+        self,
+        video_input: Qwen2_5_VLVideoInputs,
+        video_hashes: list[str] | None = None,
+        cached_video_embeds: torch.Tensor | None = None,
+    ) -> torch.Tensor:
+        if video_input["type"] == "video_embeds":
+            return video_input["video_embeds"].type(self.visual.dtype)
+
+        grid_thw = video_input["video_grid_thw"]
+        assert grid_thw.ndim == 2
+
+        pixel_values_videos = video_input["pixel_values_videos"].type(
+            self.visual.dtype)
+        with set_ascend_forward_context(None, self.vllm_config):
+            video_embeds = self.visual(pixel_values_videos, grid_thw=grid_thw)
+        # Split concatenated embeddings for each video item.
+        merge_size = self.visual.spatial_merge_size
+        sizes = grid_thw.prod(-1) // merge_size // merge_size
+
+        return video_embeds.split(sizes.tolist())
+
+
+# NOTE: These will be removed after https://github.com/vllm-project/vllm/pull/29388 is merged.
+Qwen2_5OmniThinkerForConditionalGeneration._process_image_input = AscendQwen2_5OmniThinkerForConditionalGeneration._process_image_input
+Qwen2_5OmniThinkerForConditionalGeneration._process_video_input = AscendQwen2_5OmniThinkerForConditionalGeneration._process_video_input