Google

Gemma 4 26B-A4B Instruct

About

Gemma 4 26B-A4B Instruct is an open-weight model from Google. Google Gemma 4 26B MoE (4B active), instruction-tuned. Text, up to 64 images, or one video per request. It accepts text, images, and video. Context window is 80K. Released May 1, 2026.

Context window
80K
Tokens of context on a request.
License
—
License on the weights.

Pricing

Token rates are US dollars per 1M tokens. Image rates are per 1K images. Audio rates are per 1M audio seconds.

Rate	Price
Input / 1M	$0.10
Cached input / 1M	$0.05
Output / 1M	$0.30

Compare

Gemma 4 26B-A4B Instruct is one of the catalog's chat models. The table is each model's published price, size, and context.

Model	What it does	Price	Parameters	Context
Gemma 4 26B-A4B Instruct	Google Gemma 4 26B MoE (4B active), instruction-tuned. Text, up to 64 images, or one video per request.	$0.10 / 1M input	—	80K
Qwen3.5 0.8B	Multimodal chat model with up to 64 images or one video per request.	$0.08 / 1M input	0.8B	80K
Gemini 3.5 Flash Lite	Fastest and cheapest Gemini tier. Multimodal chat; emits no reasoning tokens.	$0.30 / 1M input	—	1M
Gemini 3.7 Flash	Newest Gemini Flash tier with extended reasoning. Multimodal chat + native video.	$0.75 / 1M input	—	1M

Benchmarks

No published eval is on file for this model.

Reading	Example
Qualitative	Clear structure, grounded in the input
Quantitative	No published score on file.
Cost and performance	Lower listed rate, mid-pack latency

Methods

Methods this model serves. Payload shapes are in the docs.

Method	Returns
detection	Boxes around objects
chat	The model's reply

Estimate cost

Estimate. An hour of video is 15 frames a minute at 256 tokens a frame, plus the audio in that request, and 500 output tokens a minute.

Hours of video

$43.56

Quick start

Call this model on the OpenAI-compatible gateway. The model id is already filled in.

from openai import OpenAI

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

response = client.chat.completions.create(
    model="google/gemma4-26b-a4b-it",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What is happening in this image?"},
                {"type": "image_url", "image_url": {"url": "https://storage.googleapis.com/vlm-data-public-prod/hub/examples/image.caption/car.jpg"}},
            ],
        }
    ],
)

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