Images and vision

Several catalog models accept images alongside text. Send a screenshot, a scanned document, a chart, or a product photo and ask about it — the same request shape works on /v1/chat/completions, /v1/responses, and /v1/messages.

Which models accept images

Sending an image

Base64 data URL

The portable form — works everywhere, no upload step:

import base64, os
from openai import OpenAI

client = OpenAI(base_url="https://api.sference.com/v1", api_key=os.environ["SFERENCE_API_KEY"])

with open("invoice.png", "rb") as f:
    b64 = base64.b64encode(f.read()).decode()

response = client.chat.completions.create(
    model="zai-org/GLM-5.3-Flash",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What is the total on this invoice?"},
            {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64}"}},
        ],
    }],
)

Remote URL

If the image is already reachable over HTTPS, pass the URL directly:

{"type": "image_url", "image_url": {"url": "https://example.com/chart.png"}}

Responses API

On /v1/responses, images are content parts of an input item:

response = client.responses.create(
    model="zai-org/GLM-5.3-Flash",
    input=[{
        "role": "user",
        "content": [
            {"type": "input_text", "text": "Summarize this chart."},
            {"type": "input_image", "image_url": f"data:image/png;base64,{b64}"},
        ],
    }],
)

Anthropic Messages API

On /v1/messages, images are Anthropic content blocks:

{
    "role": "user",
    "content": [
        {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": b64}},
        {"type": "text", "text": "What does this show?"},
    ],
}

Practical limits

• Formats: PNG, JPEG, WebP, GIF. Convert exotic formats (HEIC, TIFF) before sending.
• Size: keep images under ~5 MB. Large images are downscaled before tokenization, so sending a 20 MP photo costs bandwidth without improving accuracy.
• Resolution and tokens: an image is converted to tokens, and the count scales with resolution. A full-page screenshot can cost more tokens than a page of text. Downscale to the smallest resolution that still answers your question — for a receipt, 1024 px on the long edge is usually plenty.
• Multiple images: supported. Put the text instruction after the images it refers to, or the model may describe them without answering.

Cost

Images bill as input tokens at the model's normal input rate — there is no separate image surcharge. Because token count scales with resolution, image-heavy workloads are sensitive to the resolution you send. See Pricing.

Common patterns

Document extraction. Screenshot or scan → vision model → structured output with a schema for the fields you need. This is the highest-value use of vision in production: invoices, receipts, forms, IDs.

UI and screenshot understanding. Feed a screenshot to an agent so it can reason about layout without a browser tool. Note that coding models in the catalog are text-only — see Claude Code for how that is handled in an agent loop.

Chart and table reading. Works well at moderate resolution; ask for the values explicitly rather than "describe this", and request JSON if you intend to compute on them.

Quality control. Compare two images, or an image against a spec, with a yes/no or enum answer.