[New Model] Support Command-A-Vision

[dongluw]

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.

Purpose

Issue: #22648

Support Command-A-Vision https://huggingface.co/CohereLabs/command-a-vision-07-2025/blob/main/config.json

Test Plan

python examples/offline_inference/vision_language_multi_image.py --model-type command_a_vision

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The first image shows a **Mallard duck** swimming in calm blue water. The duck has a vibrant green head, a yellow bill, and a body with brown, white, and black feathers. Its reflection is visible in the water, and the surface has gentle ripples.

The second image features a **lion** sitting in a field of tall, golden-brown grass. The lion has a thick, dark mane and a focused expression, looking slightly to the side. The background is softly blurred, emphasizing the lion's majestic presence in its natural habitat.
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python examples/offline_inference/vision_language.py --model-type command_a_vision

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The image captures a stunning view of the Tokyo Tower, a prominent landmark in Tokyo, Japan, framed by the delicate pink blossoms of cherry trees. The tower, with its white and orange structure, stands tall against a clear blue sky, creating a striking contrast. The cherry blossoms, in full bloom, dominate the foreground
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The image captures a stunning view of the Tokyo Tower, a prominent landmark in Tokyo, Japan, framed by cherry blossoms in full bloom. The tower, with its distinctive white and orange color scheme, stands tall against a clear blue sky. The cherry blossom trees, or sakura, are in the foreground, their delicate
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The image captures a stunning view of the Tokyo Tower, a prominent landmark in Tokyo, Japan, framed by the delicate blossoms of cherry trees in full bloom. The cherry blossoms, known as *sakura* in Japanese, are a quintessential symbol of spring and are celebrated for their fleeting beauty. The contrast between the soft
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The image captures a stunning view of the Tokyo Tower, a prominent landmark in Tokyo, Japan, framed by the delicate blossoms of cherry trees. The tower, with its distinctive white and orange color scheme, stands tall against a clear blue sky. The cherry blossoms, in full bloom, are a vibrant pink and dominate the
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online chat

vllm serve CohereLabs/command-a-vision-07-2025 --disable-log-requests  --tensor-parallel-size 4 --max_model_len 32000 --max-num-seqs 32

python examples/online_serving/openai_chat_completion_client_for_multimodal.py --chat-type multi-image


Chat completion output: The images feature two animals: a mallard duck and an African lion. 

1. **Mallard Duck**: The first image shows a mallard duck swimming in water. Mallards are one of the most recognizable and widespread duck species, known for their iridescent green heads (in males), white collars, and

Test Result

(Optional) Documentation Update

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[gemini-code-assist]

Code Review

This pull request introduces support for the Command-A-Vision model. The changes include a new model implementation file, along with additions to example scripts and model registries. The core logic seems sound and follows existing patterns in the codebase. However, I've identified a critical bug in the new model implementation related to an incorrect function call that will cause a runtime error. Additionally, there's a high-severity issue where a value is hardcoded, which compromises the code's generality and maintainability. Addressing these points will improve the robustness and quality of the new model support.

[DarkLight1337]

Thanks, LGTM!

cc @hmellor can you measure the perf difference compared to Transformers backend? In the future we may be able to switch fully to Transformers backend if the performance becomes on par with the custom implementation.

[hmellor]

can you measure the perf difference compared to Transformers backend?

Sure, testing now

[hmellor]

Looks like running Command A Vision in the Transformers backend will require #22673 and a change on the Transformers side