[Doc] Update ViT CUDA graph doc for mixed (image+video) inputs

[shen-shanshan]

Purpose

Following #35963 and #38061, we have supported ViT CUDA graph image/video inference for Qwen3-VL respectively. Now we have demonstrated that it's also compatible for mixed (image+video) inputs (per prompt).

Since we have grouped and batched multi-modal inputs in _execute_mm_encoder() through group_and_batch_mm_kwargs(), each call for model.embed_multimodal() or encoder_cudagraph_manager.execute() will only contain single modality.

# vllm/vllm/v1/worker/gpu_model_runner.py
def _execute_mm_encoder(...):
    # ...
    for modality, num_items, mm_kwargs_batch in group_and_batch_mm_kwargs(...):
        # ...
        if enable_vit_cuda_graph:
            batch_outputs = self.encoder_cudagraph_manager.execute(mm_kwargs_batch)
        else:
            batch_outputs = model.embed_multimodal(**mm_kwargs_batch)


# vllm/vllm/multimodal/utils.py
def group_and_batch_mm_kwargs(mm_kwargs, ...):
    for modality, group in groupby(mm_kwargs, key=lambda x: x[0]):
        ...
        for num_items, mm_kwargs_batch in group_and_batch_mm_items(...):
            yield modality, num_items, mm_kwargs_batch

Thus, mixed inputs will be separated to different ViT processes (i.e., it's compatible for our CUDA graph implementation).

Test Plan

Based on #40335.

# Pass compilation_config to EngineArgs in run_qwen3_vl()
# compilation_config={
#     "cudagraph_mm_encoder": True,
#     "encoder_cudagraph_token_budgets": [512, 1024, 1536, 2048, 2560, 3072, 3584, 4096, 4864],
#     "encoder_cudagraph_max_vision_items_per_batch": 8,
#     "encoder_cudagraph_max_frames_per_batch": 64,
# }
python examples/offline_inference/vision_language.py -m qwen3_vl --modality "image+video"

Test Result

--------------------------------------------------
The image shows a baby girl sitting on a bed, wearing glasses and reading a book. She is focused on the book, turning the pages with her small hands. The room appears to be a bedroom, with a crib and some clothes visible in the background.

In the video, the baby girl continues to read the book, occasionally looking up and smiling. She seems to be enjoying her reading time, and her glasses add a touch of charm to her appearance. The video captures a sweet and innocent moment of a child engaging in a quiet activity.
--------------------------------------------------
The image shows a baby girl sitting on a bed, wearing glasses, and reading a book.

The video shows the same baby girl continuing to read the book, turning the pages, and occasionally looking up. She appears to be very focused on the book and is enjoying her reading time.
--------------------------------------------------
The image shows a baby girl sitting on a bed, wearing glasses, and reading a book. She is focused on the book, turning the pages with her small hands. The background includes a crib and some clothes, suggesting a cozy and comfortable setting.

In the video, the baby girl continues to read the book, occasionally looking up and smiling. She seems to be enjoying the activity and is fully engaged in the story. The video captures the innocence and curiosity of a young child exploring the world of books.
--------------------------------------------------
The image shows a baby sitting on a bed, wearing glasses, and reading a book. The baby is dressed in a light blue shirt and pink pants. The background includes a crib and some clothes on the bed.

In the video, the baby continues to read the book, turning the pages and occasionally looking up. The baby seems to be enjoying the activity and is focused on the book. The video captures the baby's concentration and curiosity as they explore the book.
--------------------------------------------------

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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.

[claude]

Claude Code Review

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[mergify]

Documentation preview: https://vllm--40355.org.readthedocs.build/en/40355/

[gemini-code-assist]

Code Review

This pull request updates the documentation for CUDA graphs in multimodal models to reflect that video inference support is no longer experimental and that mixed image and video inputs per prompt are now supported. Examples and notes recommending the limitation of multi-modal inputs have been removed accordingly. I have no feedback to provide as there were no review comments.