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Vision-capable models accept images alongside text in the same message. Pass a list of content parts — one text part, one or more image_url parts — instead of a plain string. The current vision-capable model is microsoft/phi-4-multimodal-instruct. Any model with vision in its capabilities list accepts the same request shape.

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Example

curl https://tokens.flex.ai/v1/chat/completions \
  -H "Authorization: Bearer $FLEXAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "microsoft/phi-4-multimodal-instruct",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "What is in this image?"},
        {"type": "image_url", "image_url": {"url": "https://example.com/photo.jpg"}}
      ]
    }]
  }'

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Image sources

The image_url.url field accepts either a public HTTPS URL or a base64 data URL. Data URLs are the right choice when the image isn’t already hosted somewhere — no pre-upload step required.
Python
import base64
with open("photo.jpg", "rb") as f:
    b64 = base64.b64encode(f.read()).decode()

data_url = f"data:image/jpeg;base64,{b64}"
# pass data_url as image_url.url in the request above
Supported formats: JPEG, PNG, WebP, non-animated GIF.

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Multiple images

Pass more than one image_url part in the same content list to ask the model to reason across several images at once. The order is preserved in the model’s context.

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Usage accounting

Vision tokens count against your key’s budget the same way text tokens do — the usage block in the response includes any vision-encoded tokens in prompt_tokens. There’s no separate “per image” charge for vision input (unlike image generation, which is priced per output image).