##
Image-Text to Text

Image-text-to-text models take in an image and text prompt and output text. These models are also called vision-language models, or VLMs. The difference from image-to-text models is that these models take an additional text input, not restricting the model to certain use cases like image captioning, and may also be trained to accept a conversation as input.

> For more details about the `image-text-to-text` task, check out its dedicated page! You will find examples and related materials.

###
Recommended models

- zai-org/GLM-4.5V: Cutting-edge reasoning vision language model.

Explore all available models and find the one that suits you best here.

###
Using the API

Language

Client

Provider

Settings

    import os
    from openai import OpenAI

    client = OpenAI(
        base_url="https://router.huggingface.co/v1",
        api_key=os.environ["HF_TOKEN"],
    )

    completion = client.chat.completions.create(
        model="meta-llama/Llama-4-Scout-17B-16E-Instruct:cerebras",
        messages=[
            {
                "role": "user",
                "content": [
                    {
                        "type": "text",
                        "text": "Describe this image in one sentence."
                    },
                    {
                        "type": "image_url",
                        "image_url": {
                            "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
                        }
                    }
                ]
            }
        ],
    )

    print(completion.choices[0].message)

###
API specification

For the API specification of conversational image-text-to-text models, please refer to the Chat Completion API documentation.

Update on GitHub