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[Model] Add Wan2.2 I2V and TI2V pipeline support#329

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hsliuustc0106 merged 11 commits intovllm-project:mainfrom
linyueqian:feat/wan2.2-i2v
Dec 25, 2025
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[Model] Add Wan2.2 I2V and TI2V pipeline support#329
hsliuustc0106 merged 11 commits intovllm-project:mainfrom
linyueqian:feat/wan2.2-i2v

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@linyueqian linyueqian commented Dec 16, 2025

PLEASE FILL IN THE PR DESCRIPTION HERE ENSURING ALL CHECKLIST ITEMS (AT THE BOTTOM) HAVE BEEN CONSIDERED.

Purpose

Add support for Wan2.2 Image-to-Video (I2V) and Text-Image-to-Video (TI2V) pipelines.

Test Plan

Test 1: I2V-A14B (Image-to-Video with MoE)
python examples/offline_inference/image_to_video/image_to_video.py \ --model Wan-AI/Wan2.2-I2V-A14B-Diffusers \ --image input.jpg --num_frames 17 --num_inference_steps 10 \ --output i2v_a14b_output.mp4

Test 2: TI2V-5B I2V mode (Image-to-Video with unified model)
python examples/offline_inference/image_to_video/image_to_video.py \ --model Wan-AI/Wan2.2-TI2V-5B-Diffusers \ --image input.jpg --num_frames 17 --num_inference_steps 10 \ --output ti2v_5b_i2v_output.mp4

Test 3: TI2V-5B T2V mode (Text-only, no image)
python examples/offline_inference/text_to_video/text_to_video.py \ --model Wan-AI/Wan2.2-TI2V-5B-Diffusers \ --prompt "A cat walking in the garden" \ --num_frames 17 --num_inference_steps 10 \ --output ti2v_5b_t2v_output.mp4

Test Result

i2v_a14b_output.mp4
ti2v_5b_i2v_output.mp4
ti2v_5b_t2v_output.mp4

Essential Elements of an Effective PR Description Checklist
  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
  • The test plan, such as providing test command.
  • The test results, such as pasting the results comparison before and after, or e2e results
  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.
  • (Optional) Release notes update. If your change is user facing, please update the release notes draft.

BEFORE SUBMITTING, PLEASE READ https://github.com/vllm-project/vllm-omni/blob/main/CONTRIBUTING.md (anything written below this line will be removed by GitHub Actions)

Signed-off-by: linyueqian <linyueqian@outlook.com>
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@ZJY0516 ZJY0516 linked an issue Dec 16, 2025 that may be closed by this pull request
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please update supported model list as well

Signed-off-by: linyueqian <linyueqian@outlook.com>
Signed-off-by: linyueqian <linyueqian@outlook.com>
Signed-off-by: linyueqian <linyueqian@outlook.com>
@@ -1,8 +1,6 @@
from typing import Any
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why we need to move the imports?

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i didnt install the cache dependency at that time. i can revert it.

| `QwenImageEditPipeline` | Qwen-Image-Edit | `Qwen/Qwen-Image-Edit` |
|`ZImagePipeline` | Z-Image | `Tongyi-MAI/Z-Image-Turbo` |
| `WanPipeline` | Wan2.2 | `Wan-AI/Wan2.2-T2V-A14B-Diffusers` |
| `Wan22Pipeline` | Wan2.2-T2V | `Wan-AI/Wan2.2-T2V-A14B-Diffusers` |
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use WAN22Pipeline for all t2v, i2v and ti2v models?

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The three variants have different architectures (I2V-A14B uses CLIP encoder + MoE, TI2V-5B uses single transformer with VAE conditioning). Consolidation is possible but adds some model selection complexity in one pipeline. I'm leaning toward keeping separate pipelines, which follows diffusers' convention where T2V and I2V also have different pipeline classes. Let me know if you prefer otherwise.

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@ZJY0516 WDYT

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For the pipeline name, i think we should follow the identifier in Wan2.2-T2V-A14B-Diffusers/
model_index.json

"_class_name": "WanPipeline"

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let's get it done asap

linyueqian and others added 4 commits December 17, 2025 15:26
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
Signed-off-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com>
Signed-off-by: linyueqian <linyueqian@outlook.com>
Signed-off-by: linyueqian <linyueqian@outlook.com>
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@SamitHuang @hsliuustc0106 Please review again. I use the identifier name from their corresponding model_index.json file.

@hsliuustc0106 hsliuustc0106 added the ready label to trigger buildkite CI label Dec 22, 2025
Signed-off-by: linyueqian <linyueqian@outlook.com>
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could you please submit a relevant recpie to vllm/recipe?

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ZJY0516 commented Dec 24, 2025

could you please submit a relevant recpie to vllm/recipe?

Currently, we only support Cache-DiT acceleration for wan, so a recipe briefly mentioning this would be perfect.

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could you please submit a relevant recpie to vllm/recipe?

Currently, we only support Cache-DiT acceleration for wan, so a recipe briefly mentioning this would be perfect.

vllm-project/recipes#184

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lgtm, later we are going to test USP&CFG parallel when the feature is ready.

@hsliuustc0106 hsliuustc0106 merged commit 3ec35e5 into vllm-project:main Dec 25, 2025
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yenuo26 pushed a commit to yenuo26/vllm-omni that referenced this pull request Dec 29, 2025
Signed-off-by: linyueqian <linyueqian@outlook.com>
Signed-off-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
Signed-off-by: wangyu31577 <wangyu31577@hundsun.com>
princepride pushed a commit to princepride/vllm-omni that referenced this pull request Jan 10, 2026
Signed-off-by: linyueqian <linyueqian@outlook.com>
Signed-off-by: Yueqian Lin <70319226+linyueqian@users.noreply.github.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
@david6666666 david6666666 mentioned this pull request Jan 16, 2026
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[New Model]: Wan-AI/Wan2.2-I2V-A14B-Diffusers

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