google/diffusiongemma-26b-a4b-it

Served on two routes. On chat completions it behaves like the Gateway’s other chat models. On POST /typesafe/v1/systemone it powers System One, answering typed questions with a probability per label, read in one denoise step rather than generated, so an answer can never be off-schema.

Capabilities


Routes	`POST /v1/openai/chat/completions`, `POST /typesafe/v1/systemone`, and `WS /typesafe/ws`
Method	`chat`
Accepted inputs	`text`, `image_url`. On the decisions route also a `file` or `document_url` part (one PDF), carried in `content`.
Max images	8 per request, 5 MB each, JPEG / PNG / WebP / GIF
Video	Not supported
Streaming	Token streaming on chat completions. A read is a single response; `WS /typesafe/ws` answers per frame.

On the decisions route, detail sets the vision budget per image or page:

`detail`	Vision tokens
`auto` (default)	280, the same as `high`
`high`	280
`low`	70

This model rejects temperature and seed with a 400 rather than ignoring them, which differs from the other chat models on the Gateway. Omit both.

Typed decisions

On POST /typesafe/v1/systemone the same model answers typed questions with a probability per label, read in one denoise step rather than generated, so an answer can never be off-schema. It is the default engine there, and the most sharply calibrated.


Question types	`noul` (yes/no), `choice` (one of 2 to 128 labels), `score` (a 2 to 10 level rubric)
Media	`image_url` parts, or one `file` / `document_url` PDF, on `content`
`reasoning_effort`	Not supported on a diffusion engine; a request carrying it is a `422`
Output tokens	Always `0`. Nothing is generated

See System One for the request shape and a worked example in four languages, and Models for how this engine compares with the generative ones.

Chat completions

The same model on the OpenAI-compatible route, for when you want generated text rather than a typed decision.

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.vlm.run/v1/openai",
    api_key="<VLMRUN_API_KEY>",
)

response = client.chat.completions.create(
    model="google/diffusiongemma-26b-a4b-it",
    messages=[{"role": "user", "content": [
        {"type": "text", "text": "What is this page and what is the amount due?"},
        {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{page}"}},
    ]}],
    extra_body={"method": "chat"},
)

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

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://gateway.vlm.run/v1/openai",
  apiKey: process.env.VLMRUN_API_KEY,
});

const response = await client.chat.completions.create({
  model: "google/diffusiongemma-26b-a4b-it",
  messages: [{ role: "user", content: [
    { type: "text", text: "What is this page and what is the amount due?" },
    { type: "image_url", image_url: { url: `data:image/jpeg;base64,${page}` } },
  ]}],
  // @ts-expect-error gateway extension
  method: "chat",
});

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

vlmrun gw chat invoice-page.jpg \
  -m google/diffusiongemma-26b-a4b-it --method chat

IMAGE=$(base64 -w0 invoice-page.jpg)

curl https://gateway.vlm.run/v1/openai/chat/completions \
  -H "Authorization: Bearer $VLMRUN_API_KEY" \
  -H "Content-Type: application/json" \
  -d @- <<JSON
{
  "model": "google/diffusiongemma-26b-a4b-it",
  "method": "chat",
  "messages": [{"role": "user", "content": [
    {"type": "text", "text": "What is this page and what is the amount due?"},
    {"type": "image_url", "image_url": {"url": "data:image/jpeg;base64,$IMAGE"}}
  ]}]
}
JSON

Sampling fields are not interchangeable with the other chat models: temperature and seed return a 400 here instead of being ignored.

System One

Question types, inputs, confidence, and cost levers.

System One API

Request and response reference.

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google/diffusiongemma-26b-a4b-it

Capabilities

Typed decisions

Chat completions

System One

System One API

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​Typed decisions

​Chat completions

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System One

System One API

Capabilities

Typed decisions

Chat completions

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