Vision

Send images and videos alongside text to vision-capable models

Model APIs support both text and vision inputs, but multimodal capability depends on the underlying model. Vision-capable models accept images alongside text in the same request, using the OpenAI-compatible image_url content type. The model processes both modalities together, so it can answer questions about image content, compare multiple images, or extract structured data from screenshots.

Not all models support vision. Check the table below before sending image inputs.

Supported models

Model	Slug
Kimi K2.5	moonshotai/Kimi-K2.5
Kimi K2.6	moonshotai/Kimi-K2.6

Send a vision request

Use the image_url content type to include images in your messages.

Baseten retrieves image URLs from the inference service, so the URL must be reachable over HTTPS from Baseten’s environment (for example your own object storage, Hugging Face artifact links, or other hosts that allow server-side fetches). Prefer stable, direct HTTPS links.

Optional image_url.detail controls preprocessing resolution: low, high, original, or auto (OpenAI-compatible). When in doubt, use auto.

Python

from openai import OpenAI
import os

client = OpenAI(
    base_url="https://inference.baseten.co/v1",
    api_key=os.environ["BASETEN_API_KEY"],
)

response = client.chat.completions.create(
    model="moonshotai/Kimi-K2.6",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Describe the natural environment in the image.",
                },
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/seashore.png",
                        "detail": "auto",
                    },
                },
            ],
        }
    ],
)

print(response.choices[0].message.content)

JavaScript

import OpenAI from "openai";

const client = new OpenAI({
    baseURL: "https://inference.baseten.co/v1",
    apiKey: process.env.BASETEN_API_KEY,
});

const response = await client.chat.completions.create({
    model: "moonshotai/Kimi-K2.6",
    messages: [
        {
            role: "user",
            content: [
                {
                    type: "text",
                    text: "Describe the natural environment in the image.",
                },
                {
                    type: "image_url",
                    image_url: {
                        url: "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/seashore.png",
                        detail: "auto",
                    },
                },
            ],
        },
    ],
});

console.log(response.choices[0].message.content);

cURL

curl https://inference.baseten.co/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $BASETEN_API_KEY" \
  -d '{
    "model": "moonshotai/Kimi-K2.6",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Describe the natural environment in the image."
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/seashore.png",
              "detail": "auto"
            }
          }
        ]
      }
    ]
  }'

Image and video limits (Model APIs)

Each vision-capable model enforces its own per-request limits on media count and size. The current limits for Kimi are:

Limit	Kimi K2.5	Kimi K2.6
Max images per request	96	96
Max videos per request	12	12
Max total media size per request (URL)	240 MB	240 MB
Max size per image (URL)	90 MB	80 MB
Max request body (base64)	8 MB	8 MB

Pass images by URL whenever you can. The model’s vision encoder fetches each URL and enforces the per-image and total-media caps directly, while the request body stays small. Base64-encoded images travel inside the request body and hit the 8 MB cap quickly.

Other Model APIs models set their own limits. Confirm the values for a given slug in the Baseten app or via /v1/models.

Pricing

There is no additional per-image fee. Images are converted to input tokens and priced at the model’s standard input rate. Higher resolution images produce more tokens and cost more to process.

The exact conversion from pixels to tokens depends on the model. Kimi K2.5 and Kimi K2.6 divide each image into 14×14 pixel tiles where each tile becomes one input token. The cost table below uses Kimi K2.5’s uncached input rate ($0.60 per million tokens); for Kimi K2.6 and other models, use the rates on the Model APIs pricing page.

Image resolution	Tiles	Input tokens	Cost at $0.60/M
256×256	324	324	$0.0002
512×512	1,296	1,296	$0.0008
1024×1024	5,329	5,329	$0.0032
1920×1080	10,234	10,234	$0.0061

For videos, token count scales with both resolution and the number of sampled frames.