gemma-4-26B-A4B-it

by google

Mixture-of-experts VLM delivering 97% of 31B quality at 8x less compute

1.1Mdl/month

26B total / 4B activeparams

HuggingFace Use in Pipeline

Identifiers

Model ID

google/gemma-4-26B-A4B-it

Feature URI

mixpeek://image_extractor@v1/google_gemma4_26b_a4b_v1

Overview

Gemma 4 27B-A4B is Google's MoE vision-language model that activates only 4B parameters per token from a total of 26B. It ranked #6 on the Arena AI leaderboard at launch while using a fraction of the compute of dense models its size.

The model handles both text and image input with a 256K context window, making it suitable for long-document visual understanding. Its efficiency profile makes it the best choice when you need high-quality VLM capabilities at manageable cost.

Architecture

Mixture-of-Experts architecture with 26B total parameters, 4B active per token. Vision encoder processes image patches alongside text tokens. 256K context window. Supports optional 'thinking' mode for chain-of-thought reasoning.

Mixpeek SDK Integration

from mixpeek import Mixpeek
mx = Mixpeek(api_key="YOUR_KEY")

mx.ingest(
    collection_id="visual-docs",
    source="s3://reports/",
    extractors=[
        {
            "type": "scene_caption",
            "model": "google/gemma-4-26B-A4B-it",
            "output_feature": "caption"
        },
        {
            "type": "text_embedding",
            "model": "BAAI/bge-m3",
            "input_field": "caption",
            "output_feature": "caption_embedding"
        }
    ]
)